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Journal articles on the topic 'Optical sensing and motion control'
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1
Lin, P. D., and K. F. Ehmann. "Sensing of Motion Related Errors in Multiaxis Machines." Journal of Dynamic Systems, Measurement, and Control 118, no. 3 (September 1, 1996): 425–33. http://dx.doi.org/10.1115/1.2801162.
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The aim of this paper is the formulation of the principles for the development of optical measurement systems for the measurement of motion related errors in multiaxis machines. Basic system configurations for rotary and prismatic joints are discussed, and their governing linearized equations derived in explicit analytical form.
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Lu, Dasheng, Francisco Gámez, and Patricia Haro-González. "Temperature Effects on Optical Trapping Stability." Micromachines 12, no. 8 (August 12, 2021): 954. http://dx.doi.org/10.3390/mi12080954.
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In recent years, optically trapped luminescent particles have emerged as a reliable probe for contactless thermal sensing because of the dependence of their luminescence on environmental conditions. Although the temperature effect in the optical trapping stability has not always been the object of study, the optical trapping of micro/nanoparticles above room temperature is hindered by disturbances caused by temperature increments of even a few degrees in the Brownian motion that may lead to the release of the particle from the trap. In this report, we summarize recent experimental results on thermal sensing experiments in which micro/nanoparticles are used as probes with the aim of providing the contemporary state of the art about temperature effects in the stability of potential trapping processes.
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Wang, Xia, Qi Zhu, Mengzhu Hu, Wenqiang Li, Xingfan Chen, Nan Li, Xunmin Zhu, and Huizhu Hu. "Analysis and Suppression of Laser Intensity Fluctuation in a Dual-Beam Optical Levitation System." Micromachines 13, no. 7 (June 22, 2022): 984. http://dx.doi.org/10.3390/mi13070984.
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Levitated micro-resonators in vacuums have attracted widespread attention due to their application potential in precision force sensing, acceleration sensing, mass measurement and gravitational wave sensing. The optically levitated microsphere in a counter-propagating dual-beam optical trap has been of particular interest because of its large measurement range and flexible manipulation. In this system, laser intensity fluctuation directly influences the trap stability and measurement sensitivity, which makes it a crucial factor in improving trapping performance. In this paper, a time-varying optical force (TVOF) model is established to characterize the influence of laser intensity fluctuation in a dual-beam optical trap. The model describes the relationship between the laser intensity fluctuation, optical force and the dynamic motion of the micro-sized sphere. In addition, an external laser intensity control method is proposed, which achieved a 16.9 dB laser power stability control at the relaxation oscillation frequency. The long-term laser intensity fluctuation was suppressed from 3% to 0.4% in a one-hour period. Experiments showed that the particle’s position detection sensitivity and the stability of the relaxation oscillation could be improved by laser intensity fluctuation suppression.
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Delić, Uroš, Manuel Reisenbauer, Kahan Dare, David Grass, Vladan Vuletić, Nikolai Kiesel, and Markus Aspelmeyer. "Cooling of a levitated nanoparticle to the motional quantum ground state." Science 367, no. 6480 (January 30, 2020): 892–95. http://dx.doi.org/10.1126/science.aba3993.
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Quantum control of complex objects in the regime of large size and mass provides opportunities for sensing applications and tests of fundamental physics. The realization of such extreme quantum states of matter remains a major challenge. We demonstrate a quantum interface that combines optical trapping of solids with cavity-mediated light-matter interaction. Precise control over the frequency and position of the trap laser with respect to the optical cavity allowed us to laser-cool an optically trapped nanoparticle into its quantum ground state of motion from room temperature. The particle comprises 108 atoms, similar to current Bose-Einstein condensates, with the density of a solid object. Our cooling technique, in combination with optical trap manipulation, may enable otherwise unachievable superposition states involving large masses.
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Khawaja, Fahad Iqbal, Akira Kanazawa, Jun Kinugawa, and Kazuhiro Kosuge. "A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction." Sensors 21, no. 24 (December 9, 2021): 8229. http://dx.doi.org/10.3390/s21248229.
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Human–Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist human workers in their tasks and improve their efficiency. However, the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC)-based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.
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Popescu, Mihaela, Dennis Mronga, Ivan Bergonzani, Shivesh Kumar, and Frank Kirchner. "Experimental Investigations into Using Motion Capture State Feedback for Real-Time Control of a Humanoid Robot." Sensors 22, no. 24 (December 15, 2022): 9853. http://dx.doi.org/10.3390/s22249853.
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Regardless of recent advances, humanoid robots still face significant difficulties in performing locomotion tasks. Among the key challenges that must be addressed to achieve robust bipedal locomotion are dynamically consistent motion planning, feedback control, and state estimation of such complex systems. In this paper, we investigate the use of an external motion capture system to provide state feedback to an online whole-body controller. We present experimental results with the humanoid robot RH5 performing two different whole-body motions: squatting with both feet in contact with the ground and balancing on one leg. We compare the execution of these motions using state feedback from (i) an external motion tracking system and (ii) an internal state estimator based on inertial measurement unit (IMU), forward kinematics, and contact sensing. It is shown that state-of-the-art motion capture systems can be successfully used in the high-frequency feedback control loop of humanoid robots, providing an alternative in cases where state estimation is not reliable.
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Wang Chong, 王翀, 尤政 You Zheng, 邢飞 Xing Fei, and 张高飞 Zhang Gaofei. "Image Motion Velocity Field for Wide View Remote Sensing Camera and Detectors Exposure Integration Control." Acta Optica Sinica 33, no. 5 (2013): 0511002. http://dx.doi.org/10.3788/aos201333.0511002.
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Jensen-McMullin, Cynthia, Henry P. Lee, and Edward R. Lyons. "Demonstration of trapping, motion control, sensing and fluorescence detection of polystyrene beads in a multi-fiber optical trap." Optics Express 13, no. 7 (2005): 2634. http://dx.doi.org/10.1364/opex.13.002634.
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Gorchakov, S. Yu. "Synthesis of program angular motions of the Earth remote sensing spacecraft with high spatial resolution." Russian Technological Journal 9, no. 3 (June 28, 2021): 78–87. http://dx.doi.org/10.32362/2500-316x-2021-9-3-78-87.
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The article considers a spacecraft for remote sensing of the Earth with high-resolution or ultra-high-resolution optical-electronic equipment. During the shooting process, the recorded image constantly moves through the photodetector matrix at a non-constant and/or excessive velocity, which is not suitable for this photodetector. The purpose of the article is to synthesize a method for the control of the orientation and stabilization of the remote sensing spacecraft, which will provide a strictly specified velocity of the image motion on the photodetector. It is proposed to find such a law of motion (functional dependences of the angular rate of the remote sensing spacecraft on time), which will allow, when applied in the control loop, to compensate for the image motion velocities that are unsuitable for this photodetector. The method used consists in time differentiation of the fundamental equation of space photogrammetry in the guiding cosines, as well as in differentiation of the matrix of guiding cosines. This provides a transition between the guiding cosines in the space of images and the space of objects. The result obtained in the article is the derived equation of space photogrammetry in kinematic form, as well as the functional dependences of angular rate on time. In the present article, a mathematical model of scanning images of the Earth’s landscapes with the help of remote sensing spacecraft is compiled. The obtained functional dependences can be applied in the development of on-board algorithms for controlling the orientation and stabilization of the remote sensing spacecraft. When implementing orientation and stabilization control in the on-board computer based on the obtained functional dependencies, a strictly specified speed of image movement in the focal plane of the on-board shooting equipment can be provided, and, consequently, the quality of the scanned image is improved by improving the function of transmitting the modulation of the kinematic “smudge” (blurring) of the image.
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Raghunathareddy, M. V., G. Indumathi, and K. R. Niranjan. "Highly sensitive optical MEMS based photonic biosensor for colon tissue detection." AIMS Electronics and Electrical Engineering 6, no. 3 (2022): 285–95. http://dx.doi.org/10.3934/electreng.2022017.
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<abstract> <p>Biological component of cells, protein has been effectively studied and investigated using biological sensors. Photonic crystal-based sensor is highly sensitive optical nanostructure it can be manipulated to affect the motion of photon for users' application. In the proposed work microcavity based photonic crystal biosensor has been designed and investigated for its different optical sensing evaluation parameters such as transmission efficiency, sensitivity, Q factor and peak resonant wavelengths. Sensor is designed and analyzed for early detection of colon cancer tissues in blood. Radius of defect micropillar has been increased from 0.16 µm to 0.19 µm. High Quality factor 10232 has been achieved with the micro pillar radius of 0.17 µm and sensitivity 700nm/RIU. Similarly, radius of 0.16 µm, 0.18 µm and 0.19 µm has attained quality factor and sensitivity such as 5324, 7232, 8343 and 111 nm/RIU, 320 nm/RIU and 340 nm/RIU respectively. Compared other work in literature, proposed work has shown better sensing capability. Designed sensor has shown remarkable output and feasibility for future fabrication.</p> </abstract>
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Balakarim Huseynov, Tarana Zeynalova, Balakarim Huseynov, Tarana Zeynalova. "DEVELOPMENT OF THE "SMART HOUSE" CONTROL SYSTEM." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 10, no. 06 (October 10, 2021): 80–86. http://dx.doi.org/10.36962/pahtei1006202180.
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The proposed system allows you to control the parameters of the house using a remote control system. Changes in temperature and humidity in the house are monitored by telephone. The entire lighting system of the house is controlled. If a gas leak or fire occurs in the house, an alarm is triggered and a notification is sent to the phone. If there is unauthorized access to the house, this is detected by a motion sensor and a notification is sent to the phone. Changes in the apartment, which is "under the control" of the system, can be monitored and managed in the "Serial Monitor" section. Selected optical sensors are sensors that capture an optical image and work by analyzing the darkest and brightest parts of the image using algorithms. The level of security increases depending on the sensor's sensing element, so the higher the sensor's resolution, the better the image details. The ultrasonic signal is transmitted to the finger located on the scanner. Due to the presence of pores and other details that are characteristic of each fingerprint, part of this signal is absorbed, and part is returned to the sensor. As a result, the sensor can recognize fingerprints. Password authorization. A password based door lock system is an access control system that allows only authorized persons to enter a restricted area. When an authorized person enters the user ID and password from the keyboard, the door opens and after a few minutes the door closes again. If the code is entered incorrectly three times in a row, the code lock will go into blocking mode. Keywords: "smart house", control system, temperature sensor, motion sensor, telediagnostics, telecontrol.
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Yang, Sibo, Neha P. Garg, Ruobin Gao, Meng Yuan, Bernardo Noronha, Wei Tech Ang, and Dino Accoto. "Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots." Sensors 23, no. 6 (March 10, 2023): 2998. http://dx.doi.org/10.3390/s23062998.
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The lack of intuitive and active human–robot interaction makes it difficult to use upper-limb-assistive devices. In this paper, we propose a novel learning-based controller that intuitively uses onset motion to predict the desired end-point position for an assistive robot. A multi-modal sensing system comprising inertial measurement units (IMUs), electromyographic (EMG) sensors, and mechanomyography (MMG) sensors was implemented. This system was used to acquire kinematic and physiological signals during reaching and placing tasks performed by five healthy subjects. The onset motion data of each motion trial were extracted to input into traditional regression models and deep learning models for training and testing. The models can predict the position of the hand in planar space, which is the reference position for low-level position controllers. The results show that using IMU sensor with the proposed prediction model is sufficient for motion intention detection, which can provide almost the same prediction performance compared with adding EMG or MMG. Additionally, recurrent neural network (RNN)-based models can predict target positions over a short onset time window for reaching motions and are suitable for predicting targets over a longer horizon for placing tasks. This study’s detailed analysis can improve the usability of the assistive/rehabilitation robots.
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Ju, Zhiyang, Hui Zhang, Ying Tan, and Xiang Chen. "Coverage control of mobile sensor networks with directional sensing." Mathematical Biosciences and Engineering 19, no. 3 (2022): 2913–34. http://dx.doi.org/10.3934/mbe.2022134.
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<abstract><p>Control design of mobile sensors for coverage problem is addressed in this paper. The mobile sensors have non-linear dynamics and directional sensing properties which mean the sensing performance is also affected by the pointing directions of the sensors. Different from the standard optimal coverage problem where sensors are assumed to be omni-directional ones, orientation angles of the directional sensors should also be controlled, other than the position control, to achieve the coverage purpose. Considering also the non-linear dynamics of the mobile sensors, new control methodology is necessarily developed for the coverage problem with directional sensors. In the approach proposed, an innovative gradient based non-smooth motion controller is designed for the mobile sensors with unicycle dynamics. With the proposed controllers, the states of sensors will always stay in an positive invariant set where the gradient of the performance valuation function is well-defined if they are initialized within this set. Moreover, the sensors' states are proved to converge to some critical point where the gradient is zero. Simulation results are provided to illustrate the performance of the proposed coverage control strategy.</p></abstract>
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Montiel, Holman, Fernando Martínez, and Fredy Martínez. "Parallel control model for navigation tasks on service robots." Journal of Physics: Conference Series 2135, no. 1 (December 1, 2021): 012002. http://dx.doi.org/10.1088/1742-6596/2135/1/012002.
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Abstract Autonomous mobility remains an open research problem in robotics. This is a complex problem that has its characteristics according to the type of task and environment intended for the robot’s activity. Service robotics has in this sense problems that have not been solved satisfactorily. These robots must interact with human beings in environments designed for human beings, which implies that one of the basic sensors for structuring motion control and navigation schemes are those that replicate the human optical sense. In their normal activity, robots are expected to interpret visual information in the environment while following a certain motion policy that allows them to move from one point to another in the environment, consistent with their tasks. A good optical sensing system can be structured around digital cameras, with which it can apply visual identification routines of both the trajectory and its environment. This research proposes a parallel control scheme (with two loops) for the definition of movements of a service robot from images. On the one hand, there is a control loop based on a visual memory strategy using a convolutional neural network. This system contemplates a deep learning model that is trained from images of the environment containing characteristic elements of the navigation environment (various types of obstacles and different cases of free trajectories with and without navigation path). To this first loop is connected in parallel a second loop in charge of defining the specific distances to the obstacles using a stereo vision system. The objective of this parallel loop is to quickly identify the obstacle points in front of the robot from the images using a bacterial interaction model. These two loops form an information feedback motion control framework that quickly analyzes the environment and defines motion strategies from digital images, achieving real-time control driven by visual information. Among the advantages of our scheme are the low processing and memory costs in the robot, and the no need to modify the environment to facilitate the navigation of the robot. The performance of the system is validated by simulation and laboratory experiments.
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Lu, Chao, Jianwei Gong, Chen Lv, Xin Chen, Dongpu Cao, and Yimin Chen. "A Personalized Behavior Learning System for Human-Like Longitudinal Speed Control of Autonomous Vehicles." Sensors 19, no. 17 (August 23, 2019): 3672. http://dx.doi.org/10.3390/s19173672.
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As the main component of an autonomous driving system, the motion planner plays an essential role for safe and efficient driving. However, traditional motion planners cannot make full use of the on-board sensing information and lack the ability to efficiently adapt to different driving scenes and behaviors of different drivers. To overcome this limitation, a personalized behavior learning system (PBLS) is proposed in this paper to improve the performance of the traditional motion planner. This system is based on the neural reinforcement learning (NRL) technique, which can learn from human drivers online based on the on-board sensing information and realize human-like longitudinal speed control (LSC) through the learning from demonstration (LFD) paradigm. Under the LFD framework, the desired speed of human drivers can be learned by PBLS and converted to the low-level control commands by a proportion integration differentiation (PID) controller. Experiments using driving simulator and real driving data show that PBLS can adapt to different drivers by reproducing their driving behaviors for LSC in different scenes. Moreover, through a comparative experiment with the traditional adaptive cruise control (ACC) system, the proposed PBLS demonstrates a superior performance in maintaining driving comfort and smoothness.
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Doumanidis, Charalabos, and Eleni Skordeli. "Distributed-Parameter Modeling for Geometry Control of Manufacturing Processes With Material Deposition." Journal of Dynamic Systems, Measurement, and Control 122, no. 1 (July 9, 1998): 71–77. http://dx.doi.org/10.1115/1.482430.
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Recent solid freeform fabrication methods generate 3D solid objects by material deposition in successive layers made of adjacent beads. Besides numerical simulation, this article introduces an analytical model of such material addition, using superposition of unit deposition distributions, composed of elementary spherical primitives consistent with the mass transfer physics. This real-time surface geometry model, with its parameters identified by in-process profile measurements, is used for Smith-prediction of the material shape in the unobservable deposition region. The model offers the basis for a distributed-parameter geometry control scheme to obtain a desired surface topology, by modulating the feed and motion of a moving mass source. The model was experimentally tested on a fused wire deposition welding station, using optical sensing by a scanning laser stripe. Its applications to other rapid prototyping methods are discussed. [S0022-0434(00)02301-7]
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Mokhiamar, O., and M. Abe. "Examination of different models following types of yaw moment control strategy for improving handling safety of a car-caravan combination." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 217, no. 7 (July 1, 2003): 561–71. http://dx.doi.org/10.1243/095440703322114942.
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This paper examines the effect of two model responses on the performance of model following types of direct yaw control (DYC). The model responses are the side-slip angle and yaw rate vehicle response of two-degree-of-freedom vehicle motion (bicycle model). The controls aim primarily at stabilizing the handling behaviour of a car-caravan combination as well as making its handling characteristics close to those of a single vehicle. Sensing of the lateral force exerted on a hitch point is essential for the control systems proposed. The estimated side-slip angle using the model observer was compared with the real side-slip angle measured by optical side-slip sensors. The effect of the model response is proved by computer simulations of a closed-loop driver-vehicle system subjected to evasive lane change with braking. It is found that the influence of the model response has a significant effect on the control performance.
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Boubekri, Rachida, Edmond Cambril, L. Couraud, Lorenzo Bernardi, Ali Madouri, David Martrou, and Sébastien Gauthier. "High Frequency 3C-SiC AFM Cantilever Using Thermal Actuation and Metallic Piezoresistive Detection." Materials Science Forum 711 (January 2012): 80–83. http://dx.doi.org/10.4028/www.scientific.net/msf.711.80.
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One way to improve the force sensitivity of Atomic Force Microscopy (AFM) cantilevers is to increase their resonance frequency. SiC is an excellent material for that purpose due to its high Young’s modulus and low mass density. This size reduction makes conventional optical motion detection methods inappropriate. Here, we introduce self-sensing, self-excited high frequency AFM cantilevers. The motion detection is based on the measurement of a metallic piezoresistor incorporated in the cantilever. The motion excitation is performed by electrothermal actuation using another metallic circuit. Cantilevers with sizes as low as 4 μm in length, 1.2 μm in width and 0.5 μm in thickness were realized by using different steps of e-beam lithography, deposition of thin gold films to pattern the piezoresistor and the electrothermal actuation electrode. Dry etching SF6plasma was used for etching the SiC cantilever and TMAH solution heated to 80°C to release the cantilever. In this case, a thigh control of underetching, which reduces the cantilever resonance frequency was required.
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Lin, Yi-Jen, Po-Huan Chou, and Shih-Chin Yang. "High-Resolution Permanent Magnet Drive Using Separated Observers for Acceleration Estimation and Control." Sensors 22, no. 3 (January 18, 2022): 725. http://dx.doi.org/10.3390/s22030725.
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This paper proposes a high-resolution permanent magnet (PM) motor drive based on acceleration estimation and control. The PM motor is widely implemented in the printed circuit board (PCB) manufacturing process. To achieve the demanded 1 μm drilling resolution, a sine/cosine incremental encoder is usually installed for motion control. In this paper, several improvements are developed to increase the motion control steady-state accuracy balancing transient response. First, the interpolation of every two encoder counts is proposed to increase the position sensing resolution. In this case, the transient response is improved through the high-resolution position feedback. Second, a closed-loop observer with two independent bandwidths is proposed for acceleration estimation. By using the interpolated position for acceleration estimation, the vibration-reflected high-frequency torque harmonics can be compensated through the acceleration closed-loop control. It reduces the steady-state error under the same sensing hardware. According to experimental results, both transient response and steady-state error can be improved on a PM motor using the proposed position interpolation and acceleration control.
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Tripicchio, Paolo, Salvatore D’Avella, Carlo Alberto Avizzano, and Philippe Velha. "Towards robust grasping: An analysis of in-hand object motion with FBG optical fibers as force sensing technology." Mechatronics 93 (August 2023): 102990. http://dx.doi.org/10.1016/j.mechatronics.2023.102990.
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Diederichs, Claas, and Sergej Fatikow. "FPGA-Based Object Detection and Motion Tracking in Micro- and Nanorobotics." International Journal of Intelligent Mechatronics and Robotics 3, no. 1 (January 2013): 27–37. http://dx.doi.org/10.4018/ijimr.2013010103.
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Object-detection and classification is a key task in micro- and nanohandling. The microscopic imaging is often the only available sensing technique to detect information about the positions and orientations of objects. FPGA-based image processing is superior to state of the art PC-based image processing in terms of achievable update rate, latency and jitter. A connected component labeling algorithm is presented and analyzed for its high speed object detection and classification feasibility. The features of connected components are discussed and analyzed for their feasibility with a single-pass connected component labeling approach, focused on principal component analysis-based features. It is shown that an FPGA implementation of the algorithm can be used for high-speed tool tracking as well as object classification inside optical microscopes. Furthermore, it is shown that an FPGA implementation of the algorithm can be used to detect and classify carbon-nanotubes (CNTs) during image acquisition in a scanning electron microscope, allowing fast object detection before the whole image is captured.
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Li, Yiqun, Zong Chen, Tao Wang, Xiangrui Zeng, and Zhouping Yin. "Apollo: Adaptive Polar Lattice-Based Local Obstacle Avoidance and Motion Planning for Automated Vehicles." Sensors 23, no. 4 (February 6, 2023): 1813. http://dx.doi.org/10.3390/s23041813.
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The motion planning module is the core module of the automated vehicle software system, which plays a key role in connecting its preceding element, i.e., the sensing module, and its following element, i.e., the control module. The design of an adaptive polar lattice-based local obstacle avoidance (APOLLO) algorithm proposed in this paper takes full account of the characteristics of the vehicle’s sensing and control systems. The core of our approach mainly consists of three phases, i.e., the adaptive polar lattice-based local search space design, the collision-free path generation and the path smoothing. By adjusting a few parameters, the algorithm can be adapted to different driving environments and different kinds of vehicle chassis. Simulations show that the proposed method owns strong environmental adaptability and low computation complexity.
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Li, Chong, Robert N. Dean, and George T. Flowers. "Nonlinear Observability Analysis of Micro-machined Electrostatic Actuators Using Self-Sensing." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2016, DPC (January 1, 2016): 001632–62. http://dx.doi.org/10.4071/2016dpc-wp36.
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Micro-machined electrostatic actuators (MEA) like parallel plate actuators (PPAs) and comb drive actuators (GCAs) are commonly used in many applications, including gyroscopes, resonators and RF switches. The detection of an actuators' mechanical motion is desired when they are combined with feedback control techniques, especially when the application requires high performance or is affected by disturbances. The motion can be detected by a variety of sensing techniques, including capacitive, piezoresistive and optical. Electrostatic parallel plate actuators can be modeled as a type of variable capacitor, which depends on the gap between a fixed electrode and a movable electrode. Thus, the displacement of the actuator can be obtained by measuring the capacitance. However, this practical method often requires high frequency excitation signal sources or additional sensing structures. The excitation power source not only affects the performance in the actuator's steady state, but it may also generate harmonics that distort the measurement signals due to the nonlinear characteristics of the actuator. In addition, the information about velocity may not be obtained without specific sensing structures. The additional structures occupy more space in each die, which could increase the cost and size, or decrease the performance. In this study, an estimator with a series resistor configuration is proposed. The estimator can estimate the displacement and velocity by measuring the voltage of the power supply and the voltage across the actuator itself. To evaluate the feasibility, a nonlinear observability analysis is applied. The analysis shows the observability index among different system states. A simulation study verified the proposed theories.
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Michaeli, Linus, Ján Šaliga, Pavol Dolinský, and Imrich Andráš. "Optimization Paradigm in the Signal Recovery after Compressive Sensing." Measurement Science Review 19, no. 1 (February 1, 2019): 35–42. http://dx.doi.org/10.2478/msr-2019-0006.
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Abstract Compressive sensing is a processing approach aiming to reduce the data stream from the observed object with the inherent sparsity using the optimal signal models. The compression of the sparse input signal in time or in the transform domain is performed in the transmitter by the Analog to Information Converter (AIC). The recovery of the compressed signal using optimization based on the differential evolution algorithm is presented in the article as an alternative to the faster pseudoinverse algorithm. Pseudoinverse algorithm results in an unambiguous solution associated with lower compression efficiency. The selection of the mathematically appropriate signal model affects significantly the compression efficiency. On the other hand, the signal model influences the complexity of the algorithm in the receiving block. The suitability of both recovery methods is studied on examples of the signal compression from the passive infrared (PIR) motion sensors or the ECG bioelectric signals.
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Sabo, Chelsea, and Kelly Cohen. "Fuzzy Logic Unmanned Air Vehicle Motion Planning." Advances in Fuzzy Systems 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/989051.
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There are a variety of scenarios in which the mission objectives rely on an unmanned aerial vehicle (UAV) being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. With an appropriate dynamic motion planning algorithm, UAVs would be able to maneuver in any unknown environment towards a target in real time. This paper presents a methodology for two-dimensional motion planning of a UAV using fuzzy logic. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range) and target location and outputs a change in heading angle and speed. The FL controller was validated, and Monte Carlo testing was completed to evaluate the performance. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the fuzzy logic controller (FLC) feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an artificial potential field (APF) solution, a commonly used intelligent control method, had an average of 18% failure rate. These results highlighted one of the advantages of the FLC method: its adaptability to complex scenarios while maintaining low control effort.
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Qin, Jianwei, Jeehwa Hong, Hyunjeong Cho, Jo Ann S. Van Kessel, Insuck Baek, Kuanglin Chao, and Moon Sung Kim. "A Multimodal Optical Sensing System for Automated and Intelligent Food Safety Inspection." Journal of the ASABE 66, no. 4 (2023): 839–49. http://dx.doi.org/10.13031/ja.15526.
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Highlights A multimodal optical sensing system was developed for food safety applications. The prototype system can conduct dual-band Raman spectroscopy at 785 and 1064 nm. The system can automatically measure samples in Petri dishes or well plates. The system with AI software is promising for identifying species of foodborne bacteria. Abstract. A novel multimodal optical sensing system was developed for automated and intelligent food safety inspection. The system uses two pairs of compact point lasers and dispersive spectrometers at 785 and 1064 nm to realize dual-band Raman spectroscopy and imaging, which is suitable to measure samples generating low- and high-fluorescence interference signals, respectively. Automated spectral acquisition can be performed using a direct-drive XY moving stage for solid, powder, and liquid samples placed in customized well plates or randomly scattered in standard Petri dishes (e.g., bacterial colonies). Three LED lights (white backlight, UV ring light, and white ring light) and two miniature color cameras are used for machine vision measurements of samples in the Petri dishes using different combinations of illuminations and imaging modalities (e.g., transmission, fluorescence, and color). Real-time image processing and motion control techniques are used to implement automated sample counting, positioning, sampling, and synchronization functions. System software was developed using LabVIEW with integrated artificial intelligence functions able to identify and label interesting targets instantly. The system capability was demonstrated by an example application for rapid identification of five common foodborne bacteria, including Bacillus cereus, E. coli, Listeria monocytogenes, Staphylococcus aureus, and Salmonella spp.. Using a machine learning model based on a linear support vector machine, a classification accuracy of 98.6% was achieved using Raman spectra automatically collected from 222 bacterial colonies of the five species grown on nutrient nonselective agar in 90 mm Petri dishes. The entire system was built on a 30×45 cm2 breadboard, enabling it compact and portable and its use for field and on-site biological and chemical food safety inspection in regulatory and industrial applications. Keywords: Artificial intelligence, Automated sampling, Bacteria, Food safety, Machine learning, Machine vision, Raman, Sensing.
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Finke, Jorge, and Kevin M. Passino. "Stable Cooperative Vehicle Distributions for Surveillance." Journal of Dynamic Systems, Measurement, and Control 129, no. 5 (January 17, 2007): 597–608. http://dx.doi.org/10.1115/1.2767656.
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A mathematical model for the study of the behavior of a spatially distributed group of heterogeneous vehicles is introduced. We present a way to untangle the coupling between the assignment of any vehicle’s position and the assignment of all other vehicle positions by defining general sensing and moving conditions that guarantee that even when the vehicles’ motion and sensing are highly constrained, they ultimately achieve a stable emergent distribution. The achieved distribution is optimal in the sense that the proportion of vehicles allocated over each area matches the relative importance of being assigned to that area. Based on these conditions, we design a cooperative control scheme for a multivehicle surveillance problem and show how the vehicles’ maneuvering and sensing abilities, and the spatial characteristics of the region under surveillance, affect the desired distribution and the rate at which it is achieved.
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Fishel, Idan, Yoni Amit, Neta Shvil, Anton Sheinin, Amir Ayali, Yossi Yovel, and Ben M. Maoz. "Ear-Bot: Locust Ear-on-a-Chip Bio-Hybrid Platform." Sensors 21, no. 1 (January 1, 2021): 228. http://dx.doi.org/10.3390/s21010228.
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During hundreds of millions of years of evolution, insects have evolved some of the most efficient and robust sensing organs, often far more sensitive than their man-made equivalents. In this study, we demonstrate a hybrid bio-technological approach, integrating a locust tympanic ear with a robotic platform. Using an Ear-on-a-Chip method, we manage to create a long-lasting miniature sensory device that operates as part of a bio-hybrid robot. The neural signals recorded from the ear in response to sound pulses, are processed and used to control the robot’s motion. This work is a proof of concept, demonstrating the use of biological ears for robotic sensing and control.
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Bai, Dorothy, Mu-Chieh Ho, Bhekumuzi M. Mathunjwa, and Yeh-Liang Hsu. "Deriving Multiple-Layer Information from a Motion-Sensing Mattress for Precision Care." Sensors 23, no. 3 (February 3, 2023): 1736. http://dx.doi.org/10.3390/s23031736.
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Bed is often the personal care unit in hospitals, nursing homes, and individuals’ homes. Rich care-related information can be derived from the sensing data from bed. Patient fall is a significant issue in hospitals, many of which are related to getting in and/or out of bed. To prevent bed falls, a motion-sensing mattress was developed for bed-exit detection. A machine learning algorithm deployed on the chip in the control box of the mattress identified the in-bed postures based on the on/off pressure pattern of 30 sensing areas to capture the users’ bed-exit intention. This study aimed to explore how sleep-related data derived from the on/off status of 30 sensing areas of this motion-sensing mattress can be used for multiple layers of precision care information, including wellbeing status on the dashboard and big data analysis for living pattern clustering. This study describes how multiple layers of personalized care-related information are further derived from the motion-sensing mattress, including real-time in-bed/off-bed status, daily records, sleep quality, prolonged pressure areas, and long-term living patterns. Twenty-four mattresses and the smart mattress care system (SMCS) were installed in a dementia nursing home in Taiwan for a field trial. Residents’ on-bed/off-bed data were collected for 12 weeks from August to October 2021. The SMCS was developed to display care-related information via an integrated dashboard as well as sending reminders to caregivers when detecting events such as bed exits and changes in patients’ sleep and living patterns. The ultimate goal is to support caregivers with precision care, reduce their care burden, and increase the quality of care. At the end of the field trial, we interviewed four caregivers for their subjective opinions about whether and how the SMCS helped their work. The caregivers’ main responses included that the SMCS helped caregivers notice the abnormal situation for people with dementia, communicate with family members of the residents, confirm medication adjustments, and whether the standard care procedure was appropriately conducted. Future studies are suggested to focus on integrated care strategy recommendations based on users’ personalized sleep-related data.
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Ceron, Steven, Itai Cohen, Robert Shepherd, James Pikul, and Cindy Harnett. "Fiber Embroidery of Self-Sensing Soft Actuators." Biomimetics 3, no. 3 (September 4, 2018): 24. http://dx.doi.org/10.3390/biomimetics3030024.
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Natural organisms use a combination of contracting muscles and inextensible fibers to transform into controllable shapes, camouflage into their surrounding environment, and catch prey. Replicating these capabilities with engineered materials is challenging because of the difficulty in manufacturing and controlling soft material actuators with embedded fibers. In addition, while linear and bending motions are common in soft actuators, rotary motions require three-dimensional fiber wrapping or multiple bending or linear elements working in coordination that are challenging to design and fabricate. In this work, an automatic embroidery machine patterned Kevlar™ fibers and stretchable optical fibers into inflatable silicone membranes to control their inflated shape and enable sensing. This embroidery-based fabrication technique is simple, low cost, and allows for precise and custom patterning of fibers in elastomers. Using this technique, we developed inflatable elastomeric actuators embedded with a planar spiral pattern of high-strength Kevlar™ fibers that inflate into radially symmetric shapes and achieve nearly 180° angular rotation and 10 cm linear displacement.
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Wei, Yan, Wei Jiang, Ahmed Rahmani, and Qiang Zhan. "Motion Planning for a Humanoid Mobile Manipulator System." International Journal of Humanoid Robotics 16, no. 02 (April 2019): 1950006. http://dx.doi.org/10.1142/s0219843619500063.
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A high redundant non-holonomic humanoid mobile dual-arm manipulator system (MDAMS) is presented in this paper, where the motion planning to realize “human-like” autonomous navigation and manipulation tasks is studied. First, an improved MaxiMin NSGA-II algorithm, which optimizes five objective functions to solve the problems of singularity, redundancy and coupling between mobile base and manipulator simultaneously, is proposed to design the optimal pose to manipulate the target object. Then, in order to link the initial pose and that optimal pose, an off-line motion planning algorithm is designed. In detail, an efficient direct-connect bidirectional RRT and gradient descent algorithm is proposed to reduce the sampled nodes largely, and a geometric optimization method is proposed for path pruning. Besides, head forward behaviors are realized by calculating the reasonable orientations and assigning them to the mobile base to improve the quality of human-robot interaction. Third, the extension to online planning is done by introducing real-time sensing, collision-test and control cycles to update robotic motion in dynamic environments. Fourth, an EEs’ via-point-based multi-objective genetic algorithm (MOGA) is proposed to design the “human-like” via-poses by optimizing four objective functions. Finally, numerous simulations are presented to validate the effectiveness of proposed algorithms.
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Yue, Wenchao, Jiaming Qi, Xiao Song, Shicheng Fan, Giancarlo Fortino, Chia-Hung Chen, Chenjie Xu, and Hongliang Ren. "Origami-Inspired Structure with Pneumatic-Induced Variable Stiffness for Multi-DOF Force-Sensing." Sensors 22, no. 14 (July 19, 2022): 5370. http://dx.doi.org/10.3390/s22145370.
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With the emerging need for human–machine interactions, multi-modal sensory interaction is gradually pursued rather than satisfying common perception forms (visual or auditory), so developing flexible, adaptive, and stiffness-variable force-sensing devices is the key to further promoting human–machine fusion. However, current sensor sensitivity is fixed and nonadjustable after fabrication, limiting further development. To solve this problem, we propose an origami-inspired structure to achieve multiple degrees of freedom (DoFs) motions with variable stiffness for force-sensing, which combines the ductility and flexibility of origami structures. In combination with the pneumatic actuation, the structure can achieve and adapt the compression, pitch, roll, diagonal, and array motions (five motion modes), which significantly increase the force adaptability and sensing diversity. To achieve closed-loop control and avoid excessive gas injection, the ultra-flexible microfiber sensor is designed and seamlessly embedded with an approximately linear sensitivity of ∼0.35 Ω/kPa at a relative pressure of 0–100 kPa, and an exponential sensitivity at a relative pressure of 100–350 kPa, which can render this device capable of working under various conditions. The final calibration experiment demonstrates that the pre-pressure value can affect the sensor’s sensitivity. With the increasing pre-pressure of 65–95 kPa, the average sensitivity curve shifts rightwards around 9 N intervals, which highly increases the force-sensing capability towards the range of 0–2 N. When the pre-pressure is at the relatively extreme air pressure of 100 kPa, the force sensitivity value is around 11.6 Ω/N. Therefore, our proposed design (which has a low fabrication cost, high integration level, and a suitable sensing range) shows great potential for applications in flexible force-sensing development.
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Kometani, Reo, and Sunao Ishihara. "Special Issue on Nanosensing and Microsensing." International Journal of Automation Technology 12, no. 1 (January 5, 2018): 3. http://dx.doi.org/10.20965/ijat.2018.p0003.
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Sensors, which are transducer-type devices, are indispensable to today’s advanced information society. A huge number of sensors are used not only in everyday devices but also in advanced industrial systems. They are used in Internet of things (IoT) services to gather external information, intelligent robots to recognize the world around them and control their movements, and all advanced vehicle technologies to operate safely and automatically. Sensors detect light, motion, force, fluid flow, electric/magnetic fields, and other physical, chemical, and biological aspects of the external environment. To improve the performances of these sensors, such as their sensitivity, sensing resolution, and power consumption, extensive R&D is conducted in industry and academia. Recent technological progress in MEMS technology has allowed sensors to be manufactured on scales that are increasingly microscopic. More recently, the extreme downsizing of structures to nanometer scale has led to innovative sensing devices called NEMS. This special issue addresses the latest research advances in nanosensing and microsensing science and engineering. It covers a wide range of topics, including novel sensing devices and technologies; small structures fabrication technologies for sensors; MEMS/NEMS sensing devices; physical, chemical, optical and biological sensing devices; and nanoscale science and engineering for sensors. All papers were refereed through careful peer reviews. We would like to express our sincere thanks to the authors for their submissions and to the reviewers for their invaluable efforts. Lastly, we hope this special issue provides valuable and useful information to our interested readers and researchers.
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Haque, Md Rejwanul, Masudul H. Imtiaz, Samuel T. Kwak, Edward Sazonov, Young-Hui Chang, and Xiangrong Shen. "A Lightweight Exoskeleton-Based Portable Gait Data Collection System." Sensors 21, no. 3 (January 24, 2021): 781. http://dx.doi.org/10.3390/s21030781.
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For the controller of wearable lower-limb assistive devices, quantitative understanding of human locomotion serves as the basis for human motion intent recognition and joint-level motion control. Traditionally, the required gait data are obtained in gait research laboratories, utilizing marker-based optical motion capture systems. Despite the high accuracy of measurement, marker-based systems are largely limited to laboratory environments, making it nearly impossible to collect the desired gait data in real-world daily-living scenarios. To address this problem, the authors propose a novel exoskeleton-based gait data collection system, which provides the capability of conducting independent measurement of lower limb movement without the need for stationary instrumentation. The basis of the system is a lightweight exoskeleton with articulated knee and ankle joints. To minimize the interference to a wearer’s natural lower-limb movement, a unique two-degrees-of-freedom joint design is incorporated, integrating a primary degree of freedom for joint motion measurement with a passive degree of freedom to allow natural joint movement and improve the comfort of use. In addition to the joint-embedded goniometers, the exoskeleton also features multiple positions for the mounting of inertia measurement units (IMUs) as well as foot-plate-embedded force sensing resistors to measure the foot plantar pressure. All sensor signals are routed to a microcontroller for data logging and storage. To validate the exoskeleton-provided joint angle measurement, a comparison study on three healthy participants was conducted, which involves locomotion experiments in various modes, including overground walking, treadmill walking, and sit-to-stand and stand-to-sit transitions. Joint angle trajectories measured with an eight-camera motion capture system served as the benchmark for comparison. Experimental results indicate that the exoskeleton-measured joint angle trajectories closely match those obtained through the optical motion capture system in all modes of locomotion (correlation coefficients of 0.97 and 0.96 for knee and ankle measurements, respectively), clearly demonstrating the accuracy and reliability of the proposed gait measurement system.
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Tohari, Mariam M. "Near-infrared switching between slow and fast light in the metal nanoparticles-graphene nanodisks-quantum dots hybrid systems." Physica Scripta 97, no. 4 (March 15, 2022): 045808. http://dx.doi.org/10.1088/1402-4896/ac5af2.
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Abstract Graphene-based nanocomposites have recently attracted much interest due to the unique properties of graphene plasmons paving the way to promising potential applications. We study the near-infrared linear optical properties of the metal nanoparticle-graphene nanodisk- quantum dot hybrid system by numerically solving the equation of motion for the density matrix elements that describe the dynamics of the system where the quantum dot is modeled as a three-level atomic system of Λ configuration interacting with a weak probe field and strong control field. We obtain a strong switching between slow and fast light near resonance can be controlled by the distances between the components of the system, the size of metal nanoparticle as well as the Rabi frequency of the control field. Moreover, the proposed hybrid plasmonic system shows a significant amplification without population inversion can be effectively monitored by strength of the control field. Thus, we think that the metal nanoparticle-graphene nanodisk- quantum dot hybrid system has potential applications in communication, sensing, imaging, signal processing and optoelectronics devices.
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Ganapathy, Then Mozhi, Dhanalakshmi Kaliaperumal, and Seung-Bok Choi. "Design and Control of Monolithic Compliant Gripper Using Shape Memory Alloy Wires." Sensors 23, no. 4 (February 11, 2023): 2052. http://dx.doi.org/10.3390/s23042052.
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This paper presents the design, fabrication and testing of a shape memory alloy (SMA)-actuated monolithic compliant gripping mechanism that enables translational motion of the gripper tips for grasping operation suitable for micromanipulation and microassembly. The design is validated using a finite element analysis (FEA), and a prototype is created for experimental testing. The reported gripping structure is simple and easy to build and design. The gripper is demonstrated to have a displacement amplification gain of 3.7 that allows maximum tip displacement up to 1.2 cm to possess good handling range and geometric advantage which cannot be accomplished by conventional grippers. The position of the gripper tip is predicted from the variation in the electrical resistance of the SMA wire based on the self-sensing phenomena. Self-sensing actuation of the SMA allows the design of a compact and lightweight structure; moreover, it supports the control loop/scheme to use the same SMA element both as an actuator and sensor for position control. The geometrical dimensions of the SMA wire-actuated monolithic compliant gripper is 0.09 m × 0.04 m and can be operated to handle objects with a maximum size of 0.012 m weighing up to 35 g.
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Zhao, Chongle, Changjun Jia, Yongsheng Zhu, and Tianming Zhao. "An Effective Self-Powered Piezoelectric Sensor for Monitoring Basketball Skills." Sensors 21, no. 15 (July 29, 2021): 5144. http://dx.doi.org/10.3390/s21155144.
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Self-powered piezoelectric sensor can achieve real-time and harmless monitoring of motion processes without external power supply, which can be attached on body skin or joints to detect human motion and powered by mechanical energy. Here, a sensor for monitoring emergent motion is developed using the PVDF as active material and piezoelectric output as sensing signal. The multi-point control function enables the sensor to monitor the sequence of force order, angle change, and motion frequency of the “elbow lift, arm extension, and wrist compression” during shooting basketball. In addition, the sensor shows can simultaneously charge the capacitor to provide more power for intelligence, typically Bluetooth transmission. The sensor shows good performance in other field, such as rehabilitation monitoring and speech input systems. Therefore, the emerging application of flexible sensors have huge long-term prospects in sport big data collection and Internet of Things (IoT).
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Lutz, Oleg Viktorovich, Galina Alexandrovna Borshchova, Evgeny Dmitrievich Yarmolchuk, and Alexander Alekseevich Manoilenko. "ANGULAR MOVEMENT PROGRAM CALCULATION PROCEDURE SPACECRAFT WHEN TAKING THE SURFACE OF THE EARTH IN AREA MODE." Journal of Rocket-Space Technology 27, no. 4 (December 30, 2019): 86–100. http://dx.doi.org/10.15421/451914.
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Currently increased interest in satellite images of the Earth's surface with high resolution terrain (1 to 10 m). To obtain such images, you must use a long focus optical system (OS) having a limited field of view that does not allow the images of the large width. To increase the effectiveness of shooting in modern space systems (SS) Earth observation provides the opportunity after shooting a segment of the Earth's surface to redirect the OS to another area and spend it shooting. With sufficient speed shift OS it is possible to survey two or more adjacent parcels, which is almost equivalent to the corresponding increase in the width of the field of view of the removing apparatus. In this connection there is the task of restoring the OS, which is solved by the use of appropriate hardware and software control the angular movement of the removing apparatus. When creating the SS there is also the need to solve the following tasks: calculation of the program angular motion in a given length of the removable sections and a predetermined number of adjacent strips to be shot, with the purpose of definition of system requirements, spacecraft (SC) control and calculation under given characteristics of the system orientation of the SC possible number of the maximum length and remove adjacent portions of the surface of the Earth. To solve these tasks the mathematical model software of angular motion of the SC. Given the necessary initial data, mathematical model and method of calculation of kinematic parameters of a software angular motion of a SC in the mode of area highway shooting adjacent sections of the Earth's surface located at a predetermined distance from a trace route SC; examples and results of numerical calculations of the programmes angular motion by moving the instrument in remote sensing.
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Xu, Wenxia, Jian Huang, and Lei Cheng. "A Novel Coordinated Motion Fusion-Based Walking-Aid Robot System." Sensors 18, no. 9 (August 22, 2018): 2761. http://dx.doi.org/10.3390/s18092761.
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Human locomotion is a coordinated motion between the upper and lower limbs, which should be considered in terms of both the user’s normal walking state and abnormal walking state for a walking-aid robot system. Therefore, a novel coordinated motion fusion-based walking-aid robot system was proposed. To develop the accurate human motion intention (HMI) of such robots when the user is in normal walking state, force-sensing resistor (FSR) sensors and a laser range finder (LRF) are used to detect the two HMIs expressed by the user’s upper and lower limbs. Then, a fuzzy logic control (FLC)-Kalman filter (LF)-based coordinated motion fusion algorithm is proposed to synthesize these two segmental HMIs to obtain an accurate HMI. A support vector machine (SVM)-based fall detection algorithm is used to detect whether the user is going to fall and to distinguish the user’s falling mode when he/she is in an abnormal walking state. The experimental results verify the effectiveness of the proposed algorithms.
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Gao, Amy, and Michael S. Triantafyllou. "Independent caudal fin actuation enables high energy extraction and control in two-dimensional fish-like group swimming." Journal of Fluid Mechanics 850 (July 4, 2018): 304–35. http://dx.doi.org/10.1017/jfm.2018.456.
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We study through numerical simulation the optimal hydrodynamic interactions and basic vorticity control mechanisms for two fish-like bodies swimming in tandem. We show that for a fish swimming in the wake of an upstream fish, using independent pitch control of its caudal fin, in addition to optimized body motion, results in reduction of the energy needed for self-propulsion by more than 50 %, providing a quasi-propulsive efficiency of 90 %, up from 60 % without independent caudal fin control. Such high efficiency is found over a narrow parametric range and is possible only when the caudal fin is allowed to pitch independently from the motion of the main body. We identify the vorticity control mechanisms employed by the body and tail to achieve this remarkable performance through thrust augmentation and destructive interference with the upstream fish-generated vortices. A high sensitivity of the propulsive performance to small variations in caudal fin parameters is found, underlying the importance of accurate flow sensing and feedback control. We further demonstrate that using lateral line-like flow measurements to drive an unscented Kalman filter, the near-field vortices can be localized within 1 % of the body length, and be used with a phase-lock controller to drive the body and tail undulation of a self-propelled fish, moving within the wake of an upstream fish, to stably reach the optimal gait and fully achieve maximum energy extraction.
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Xue, Yuanfei. "Tracking System and Its Application in Unmanned Automobile Navigation Based on Sparse Photoelectric Sensor Network." Journal of Nanoelectronics and Optoelectronics 15, no. 7 (July 1, 2020): 799–809. http://dx.doi.org/10.1166/jno.2020.2806.
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Sensor tracking technology has broad prospects of application in the fields of smart home and environmental protection. The passive motion tracking method of sensor networks can realize the perception of location, temperature and other information without carrying sensor nodes. A sparse network tracking system based on infrared sensor nodes is proposed in this study, which can control the running automobiles with unmanned navigation. On the basis of the theory of diffraction, the way of spreading for wireless received signal strength (RSS) can be divided into "scattered waves" and "diffracted waves," which can be regarded as two components of infrared sensing wireless signals so as to further propose the RSS indicators of "long-term testing value" and "short-term test value." Based on these indicators, a measurement model based on diffraction effects and scattering effects is proposed, and an improved particle filter algorithm is used to update the motion tracking. The hardware design of each module in an unmanned vehicle includes the main controller, tracking circuit, serial port circuit, motor control circuit and infrared sensor control circuit of the car. In the experiment, the measurement accuracy of the tracking system based on the sparse infrared photoelectric sensor was first tested. In the simulation experiment, the long-term test value, the short-term test value and the actual measurement value were compared respectively. The test results show that the theoretical RSS value and the actual test result can be matched. Moreover, the infrared photoelectric tracking system is used to design the navigation control system of unmanned cars, helping the car to drive automatically through obstacle avoidance test and tracking obstacle avoidance test.
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Fischer, Gregory S. "Enabling Closed-Loop Surgery in MRI." Mechanical Engineering 137, no. 09 (September 1, 2015): S11—S14. http://dx.doi.org/10.1115/1.2015-sep-8.
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This article demonstrates on the use of closed-loop surgery methods in magnetic resonance imaging (MRI). MRI is a highly effective soft tissue imaging system, and the ability to utilize this procedure in-vivo coupled with precision computer controlled motion will prove to be an invaluable asset in the future development of minimally invasive surgery. Robotic assistance has been investigated for guiding instrument placement in MRI, beginning with neurosurgery and later percutaneous interventions with some examples shown in the paper. In order for a system to compatible with the MRI environment, it should: be safe in the MRI environment, preserve the image quality, and be able to operate unaffected by the scanner’s electric and magnetic fields. Closed loop control requires multiple levels of feedback. Optical encoders have proven to be successful for position sensing inside the scanner bore during imaging when coupled with differential line drivers, filtering appropriate electrical lines, and thoroughly shielding cables to minimize electromagnetic interference (EMI).
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Li, Xin, Ondrej Dyck, Sergei V. Kalinin, and Stephen Jesse. "Compressed Sensing of Scanning Transmission Electron Microscopy (STEM) With Nonrectangular Scans." Microscopy and Microanalysis 24, no. 6 (December 2018): 623–33. http://dx.doi.org/10.1017/s143192761801543x.
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AbstractScanning transmission electron microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In recent years, attention has focused on the potential of STEM to explore beam induced chemical processes and especially manipulating atomic motion, enabling atom-by-atom fabrication. These applications, as well as traditional imaging of beam sensitive materials, necessitate increasing the dynamic range of STEM in imaging and manipulation modes, and increasing the absolute scanning speed which can be achieved by combining sparse sensing methods with nonrectangular scanning trajectories. Here we have developed a general method for real-time reconstruction of sparsely sampled images from high-speed, noninvasive and diverse scanning pathways, including spiral scan and Lissajous scan. This approach is demonstrated on both the synthetic data and experimental STEM data on the beam sensitive material graphene. This work opens the door for comprehensive investigation and optimal design of dose efficient scanning strategies and real-time adaptive inference and control of e-beam induced atomic fabrication.
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Jiang, Linyi, Xiaoyan Li, Liyuan Li, Lin Yang, Lan Yang, Zhuoyue Hu, and Fansheng Chen. "On-Orbit Geometric Calibration from the Relative Motion of Stars for Geostationary Cameras." Sensors 21, no. 19 (October 7, 2021): 6668. http://dx.doi.org/10.3390/s21196668.
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Affected by the vibrations and thermal shocks during launch and the orbit penetration process, the geometric positioning model of the remote sensing cameras measured on the ground will generate a displacement, affecting the geometric accuracy of imagery and requiring recalibration. Conventional methods adopt the ground control points (GCPs) or stars as references for on-orbit geometric calibration. However, inescapable cloud coverage and discontented extraction algorithms make it extremely difficult to collect sufficient high-precision GCPs for modifying the misalignment of the camera, especially for geostationary satellites. Additionally, the number of the observed stars is very likely to be inadequate for calibrating the relative installations of the camera. In terms of the problems above, we propose a novel on-orbit geometric calibration method using the relative motion of stars for geostationary cameras. First, a geometric calibration model is constructed based on the optical system structure. Then, we analyze the relative motion transformation of the observed stars. The stellar trajectory and the auxiliary ephemeris are used to obtain the corresponding object vector for correcting the associated calibration parameters iteratively. Experimental results evaluated on the data of a geostationary experiment satellite demonstrate that the positioning errors corrected by this proposed method can be within ±2.35 pixels. This approach is able to effectively calibrate the camera and improve the positioning accuracy, which avoids the influence of cloud cover and overcomes the great dependence on the number of the observed stars.
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Fang, Zheng, Tao Yu, Qian Wang, Chao Wang, and Siyuan Chen. "Use of ant colony optimization and the Kalman filter to deduce thigh dip angle via acceleration and angular velocity sensing." Measurement and Control 51, no. 9-10 (October 8, 2018): 488–97. http://dx.doi.org/10.1177/0020294018804985.
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Background: Acceleration and angular velocity sensors are commonly used in the measurement of gait parameters. A representative application calculates the limb segment dip angle. The rotation angle is typically deduced by a conventional Kalman filter, which includes the use of two empirically derived parameters. We improved this conventional method by introducing colony algorithm to find the optimal parameter combination instead of empirically assignment. Method: To achieve optimal results, a servo motor with an inertial measurement unit was used to simulate human limb segment motion according to programmed rotation angles that was employed as the ground truth. To minimize the bias between the ground truth and the calculated result, the ant colony algorithm was employed to obtain the optimal Kalman filter parameter combination in two-dimensional space. Results: By the motor experiment, the sum of the angle squared error was only 1.9305 rad2, much better than the 6.7723 rad2 error by the conventional method. The optimal parameter combination obtained was then used in a human experiment involving a basketball player. The frames from video of a whole gait cycle period were all showed with a corresponding deduced thigh dip angle curve diagram. Conclusion: The colony algorithm for parameters optimization results in less angle errors deduced by Kalman filter using the data from inertial measurement unit. The subject experiment verified the feasibility and performance of this method.
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Cao, Yu, Xiuqin Su, Xueming Qian, Haitao Wang, Wei Hao, Meilin Xie, Xubin Feng, Junfeng Han, Mingliang Chen, and Chenglong Wang. "A Tracking Imaging Control Method for Dual-FSM 3D GISC LiDAR." Remote Sensing 14, no. 13 (July 1, 2022): 3167. http://dx.doi.org/10.3390/rs14133167.
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In this paper, a tracking and pointing control system with dual-FSM (fast steering mirror) composite axis is proposed. It is applied to the target-tracking accuracy control in a 3D GISC LiDAR (three-dimensional ghost imaging LiDAR via sparsity constraint) system. The tracking and pointing imaging control system of the dual-FSM 3D GISC LiDAR proposed in this paper is a staring imaging method with multiple measurements, which mainly solves the problem of high-resolution remote-sensing imaging of high-speed moving targets when the technology is transformed into practical applications. In the research of this control system, firstly, we propose a method that combines motion decoupling and sensor decoupling to solve the mechanical coupling problem caused by the noncoaxial sensor installation of the FSM. Secondly, we suppress the inherent mechanical resonance of the FSM in the control system. Thirdly, we propose the optical path design of a dual-FSM 3D GISC LiDAR tracking imaging system to solve the problem of receiving aperture constraint. Finally, after sufficient experimental verification, our method is shown to successfully reduce the coupling from 7% to 0.6%, and the precision tracking bandwidth reaches 300 Hz. Moreover, when the distance between the GISC system and the target is 2.74 km and the target flight speed is 7 m/s, the tracking accuracy of the system is improved from 15.7 μrad (σ) to 2.2 μrad (σ), and at the same time, the system recognizes the target contour clearly. Our research is valuable to put the GISC technology into practical applications.
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Song, Xiulan, Xiaoxin Lou, Junwei Zhu, and Defeng He. "Secure State Estimation for Motion Monitoring of Intelligent Connected Vehicle Systems." Sensors 20, no. 5 (February 25, 2020): 1253. http://dx.doi.org/10.3390/s20051253.
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This paper considers the state estimation problem of intelligent connected vehicle systems under the false data injection attack in wireless monitoring networks. We propose a new secure state estimation method to reconstruct the motion states of the connected vehicles equipped with cooperative adaptive cruise control (CACC) systems. First, the set of CACC models combined with Proportion-Differentiation (PD) controllers are used to represent the longitudinal dynamics of the intelligent connected vehicle systems. Then the notion of sparseness is employed to model the false data injection attack of the wireless networks of the monitoring platform. According to the corrupted data of the vehicles’ states, the compressed sensing principle is used to describe the secure state estimation problem of the connected vehicles. Moreover, the L1 norm optimization problem is solved to reconstruct the motion states of the vehicles based on the orthogonaldecomposition. Finally, the simulation experiments verify that the proposed method can effectively reconstruct the motion states of vehicles for remote monitoring of the intelligent connected vehicle system.
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Miller, Alexander, Boris Miller, and Gregory Miller. "On AUV Control with the Aid of Position Estimation Algorithms Based on Acoustic Seabed Sensing and DOA Measurements." Sensors 19, no. 24 (December 13, 2019): 5520. http://dx.doi.org/10.3390/s19245520.
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This article discusses various approaches to the control of autonomous underwater vehicles (AUVs) with the aid of different velocity-position estimation algorithms. Traditionally this field is considered as the area of the extended Kalman filter (EKF) application: It became a universal tool for nonlinear observation models and its use is ubiquitous. Meanwhile, the specific characteristics of underwater navigation, such as an incomplete sets of measurements, constraints on the range metering or even impossibility of range measurements, observations provided by rather specific acoustic beacons, sonar observations, and other features seriously narrow the applicability of common instruments due to a high level of uncertainty and nonlinearity. The AUV navigation system, not being able to rely on a single source of position estimation, has to take into account all available information. This leads to the necessity of various complex estimation and data fusion algorithms, which are the matter of the present article. Here we discuss some approaches to the AUV position estimation such as conditionally minimax nonlinear filtering (CMNF) and unbiased pseudo-measurement filters (UPMFs) in conjunction with velocity estimation based on the seabed profile acoustic sensing. The presented estimation algorithms serve as a basis for a locally optimal AUV motion control algorithm, which is also presented.
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Hernando-García, Jorge, Jose Luis García-Caraballo, Víctor Ruiz-Díez, and Jose Luis Sánchez-Rojas. "Motion of a Legged Bidirectional Miniature Piezoelectric Robot Based on Traveling Wave Generation." Micromachines 11, no. 3 (March 20, 2020): 321. http://dx.doi.org/10.3390/mi11030321.
Full textAbstract:
This article reports on the locomotion performance of a miniature robot that features 3D-printed rigid legs driven by linear traveling waves (TWs). The robot structure was a millimeter-sized rectangular glass plate with two piezoelectric patches attached, which allowed for traveling wave generation at a frequency between the resonant frequencies of two contiguous flexural modes. As a first goal, the location and size of the piezoelectric patches were calculated to maximize the structural displacement while preserving a standing wave ratio close to 1 (cancellation of wave reflections from the boundaries). The design guidelines were supported by an analytical 1D model of the structure and could be related to the second derivative of the modal shapes without the need to rely on more complex numerical simulations. Additionally, legs were bonded to the glass plate to facilitate the locomotion of the structure; these were fabricated using 3D stereolithography printing, with a range of lengths from 0.5 mm to 1.5 mm. The optimal location of the legs was deduced from the profile of the traveling wave envelope. As a result of integrating both the optimal patch length and the legs, the speed of the robot reached as high as 100 mm/s, equivalent to 5 body lengths per second (BL/s), at a voltage of 65 Vpp and a frequency of 168 kHz. The blocking force was also measured and results showed the expected increase with the mass loading. Furthermore, the robot could carry a load that was 40 times its weight, opening the potential for an autonomous version with power and circuits on board for communication, control, sensing, or other applications.
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Kuroda, Jin, and Gou Koutaki. "Sensing Control Parameters of Flute from Microphone Sound Based on Machine Learning from Robotic Performer." Sensors 22, no. 5 (March 7, 2022): 2074. http://dx.doi.org/10.3390/s22052074.
Full textAbstract:
When learning to play a musical instrument, it is important to improve the quality of self-practice. Many systems have been developed to assist practice. Some practice assistance systems use special sensors (pressure, flow, and motion sensors) to acquire the control parameters of the musical instrument, and provide specific guidance. However, it is difficult to acquire the control parameters of wind instruments (e.g., saxophone or flute) such as flow and angle between the player and the musical instrument, since it is not possible to place sensors into the mouth. In this paper, we propose a sensorless control parameter estimation system based on the recorded sound of a wind instrument using only machine learning. In the machine learning framework, many training samples that have both sound and correct labels are required. Therefore, we generated training samples using a robotic performer. This has two advantages: (1) it is easy to obtain many training samples with exhaustive control parameters, and (2) we can use the correct labels as the given control parameters of the robot. In addition to the samples generated by the robot, some human performance data were also used for training to construct an estimation model that enhanced the feature differences between robot and human performance. Finally, a flute control parameter estimation system was developed, and its estimation accuracy for eight novice flute players was evaluated using the Spearman’s rank correlation coefficient. The experimental results showed that the proposed system was able to estimate human control parameters with high accuracy.