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Academic literature on the topic 'Robotic sensors and control'
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Journal articles on the topic "Robotic sensors and control"
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Kramer, Kathleen A., and Stephen C. Stubberud. "Control Loop Sensor Calibration Using Neural Networks for Robotic Control." Journal of Robotics 2011 (2011): 1–8. http://dx.doi.org/10.1155/2011/845685.
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Whether sensor model’s inaccuracies are a result of poor initial modeling or from sensor damage or drift, the effects can be just as detrimental. Sensor modeling errors result in poor state estimation. This, in turn, can cause a control system relying upon the sensor’s measurements to become unstable, such as in robotics where the control system is applied to allow autonomous navigation. A technique referred to as a neural extended Kalman filter (NEKF) is developed to provide both state estimation in a control loop and to learn the difference between the true sensor dynamics and the sensor model. The technique requires multiple sensors on the control system so that the properly operating and modeled sensors can be used as truth. The NEKF trains a neural network on-line using the same residuals as the state estimation. The resulting sensor model can then be reincorporated fully into the system to provide the added estimation capability and redundancy.
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Kazerooni, H., Mark S. Evans, and J. Jones. "Hydrostatic Force Sensor for Robotic Applications." Journal of Dynamic Systems, Measurement, and Control 119, no. 1 (1997): 115–19. http://dx.doi.org/10.1115/1.2801201.
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This article presents a theoretical and experimental investigation of a new kind of force sensor which detects forces by measuring an induced pressure change in a material of large Poisson’s ratio. In this investigation, we develop mathematical expressions for the sensor’s sensitivity and bandwidth, and show that its sensitivity can be much larger and its bandwidth is usually smaller than those of existing strain-gage-type sensors. This force sensor is well-suited for measuring large but slowly varying forces. It can be installed in a space smaller than that required for existing sensors. This paper also discusses the effects of various parameters on the sensor’s performance and on failure modes. To verify the theoretical derivation, a prototype force sensor was designed and built. This prototype hydrostatic force sensor can measure the compressive forces up to 7200 lbf and tensile forces up to 3500 lbf.
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Cheng, Teddy M., and Andrey V. Savkin. "Decentralized control for mobile robotic sensor network self-deployment: barrier and sweep coverage problems." Robotica 29, no. 2 (2010): 283–94. http://dx.doi.org/10.1017/s0263574710000147.
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SUMMARYThis paper addresses the problems of barrier coverage and sweep coverage in a corridor environment with a network of self-deployed mobile autonomous robotic sensors. Using the ideas of nearest neighbor rules and information consensus, we propose a decentralized control law for the robotic sensors to solve the coverage problems. Numerical simulations illustrate the effectiveness of the proposed algorithm. The results in this paper demonstrate that such simple motion coordination rules can play a significant role in addressing the issue of coverage in a mobile robotic sensor network.
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Zhu, Lingfeng, Yancheng Wang, Deqing Mei, and Chengpeng Jiang. "Development of Fully Flexible Tactile Pressure Sensor with Bilayer Interlaced Bumps for Robotic Grasping Applications." Micromachines 11, no. 8 (2020): 770. http://dx.doi.org/10.3390/mi11080770.
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Flexible tactile sensors have been utilized in intelligent robotics for human-machine interaction and healthcare monitoring. The relatively low flexibility, unbalanced sensitivity and sensing range of the tactile sensors are hindering the accurate tactile information perception during robotic hand grasping of different objects. This paper developed a fully flexible tactile pressure sensor, using the flexible graphene and silver composites as the sensing element and stretchable electrodes, respectively. As for the structural design of the tactile sensor, the proposed bilayer interlaced bumps can be used to convert external pressure into the stretching of graphene composites. The fabricated tactile sensor exhibits a high sensing performance, including relatively high sensitivity (up to 3.40% kPa−1), wide sensing range (200 kPa), good dynamic response, and considerable repeatability. Then, the tactile sensor has been integrated with the robotic hand finger, and the grasping results have indicated the capability of using the tactile sensor to detect the distributed pressure during grasping applications. The grasping motions, properties of the objects can be further analyzed through the acquired tactile information in time and spatial domains, demonstrating the potential applications of the tactile sensor in intelligent robotics and human-machine interfaces.
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Brüggenwirth, Stefan, and Fernando Rial. "Robotic control for cognitive UWB radar." Encyclopedia with Semantic Computing and Robotic Intelligence 02, no. 01 (2018): 1850009. http://dx.doi.org/10.1142/s2529737618500090.
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In the paper, we describe a trajectory planning problem for a six-DoF robotic manipulator arm that carries an ultra-wideband (UWB) radar sensor with synthetic aperture (SAR). The resolution depends on the trajectory and velocity profile of the sensor head. The constraints can be modeled as an optimization problem to obtain a feasible, collision-free target trajectory of the end-effector of the manipulator arm in Cartesian coordinates that minimizes observation time. For 3D reconstruction, the target is observed in multiple height slices. For through-the-wall radar the sensor can be operated in sliding mode for scanning larger areas. For IED inspection the spotlight mode is preferred, constantly pointing the antennas towards the target to obtain maximum azimuth resolution. UWB sensors typically use a wide spectrum shared by other RF communication systems. This may become a limiting factor on system sensitivity and severely degrade the image quality. Cognitive radars can adapt dynamically their bandwidth, frequency and other transmit parameters to the radio frequency environment to avoid interference with primary users.
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Cheng, Teddy M., and Andrey V. Savkin. "Self-deployment of mobile robotic sensor networks for multilevel barrier coverage." Robotica 30, no. 4 (2011): 661–69. http://dx.doi.org/10.1017/s0263574711000877.
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SUMMARYWe study a problem of K-barrier coverage by employing a network of self-deployed, autonomous mobile robotic sensors. A decentralized coordination algorithm is proposed for the robotic sensors to address the coverage problem. The algorithm is developed based on some simple rules that only rely on local information. By applying the algorithm to the robotic sensors, K layers of sensor barriers are formed to cover the region between two given points. To illustrate the proposed algorithm, numerical simulations are carried out for a number of scenarios.
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Setiawan, Joga Dharma, Mochammad Ariyanto, M. Munadi, Muhammad Mutoha, Adam Glowacz, and Wahyu Caesarendra. "Grasp Posture Control of Wearable Extra Robotic Fingers with Flex Sensors Based on Neural Network." Electronics 9, no. 6 (2020): 905. http://dx.doi.org/10.3390/electronics9060905.
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This study proposes a data-driven control method of extra robotic fingers to assist a user in bimanual object manipulation that requires two hands. The robotic system comprises two main parts, i.e., robotic thumb (RT) and robotic fingers (RF). The RT is attached next to the user’s thumb, while the RF is located next to the user’s little finger. The grasp postures of the RT and RF are driven by bending angle inputs of flex sensors, attached to the thumb and other fingers of the user. A modified glove sensor is developed by attaching three flex sensors to the thumb, index, and middle fingers of a wearer. Various hand gestures are then mapped using a neural network. The input data of the robotic system are the bending angles of thumb and index, read by flex sensors, and the outputs are commanded servo angles for the RF and RT. The third flex sensor is attached to the middle finger to hold the extra robotic finger’s posture. Two force-sensitive resistors (FSRs) are attached to the RF and RT for the haptic feedback when the robot is worn to take and grasp a fragile object, such as an egg. The trained neural network is embedded into the wearable extra robotic fingers to control the robotic motion and assist the human fingers in bimanual object manipulation tasks. The developed extra fingers are tested for their capacity to assist the human fingers and perform 10 different bimanual tasks, such as holding a large object, lifting and operate an eight-inch tablet, and lifting a bottle, and opening a bottle cap at the same time.
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Noritsugu, Toshiro. "Special Issue on Robotics for Innovative Industry and Society." International Journal of Automation Technology 8, no. 2 (2014): 139. http://dx.doi.org/10.20965/ijat.2014.p0139.
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Robotics has become one of the most important automation technologies for industry and society. Robot components such as actuators and sensors, together with mechanisms and control systems, are being more and more combined with intelligent sensors in innovative industry design and fabrication. Robot technology is being applied in such fields as welfare, education, agriculture, and energy. Robot technology for welfare and nursing is being promoted by the government to increase lifestyle creativity as society ages. This special issue focuses on robotics in fields from manufacturing industries to societal needs. Papers ranging from robotics theory to robot application have been invited. Among the topics covered are robot mechanisms, robot components, actuators, sensors, and controllers, robot control theory, robotic systems, energy saving, industrial applications, automation, vehicles, entertainment, medicine, welfare and nursing applications, and robotics education. The 15 papers presented in this issue include actuators such as rubber artificial muscles or phase-change actuators, pneumatics, power assist devices such as assist glove and upper-limb assist devices, robotic suits, sensor fusion, omnidirectional locomotion, underwater robots, force display apparatuses, meal assistant robots, manufacturing applications of parallel-link mechanisms, surface polishing, and agricultural applications. These papers bring readers the latest state-of-the-art robot technologies useful in everything from analysis and design to control and applications in innovative industries. We thank the authors for their invaluable contributions and the reviewers for their advice – all of which have made this special issue both informative and entertaining.
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Khort, Dmitriy, Alexey Kutyrev, Rostislav Filippov, and Stepan Semichev. "Development control system robotic platform for horticulture." E3S Web of Conferences 262 (2021): 01024. http://dx.doi.org/10.1051/e3sconf/202126201024.
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The article presents a control system for a robotic platform for horticulture. The electronic control system consists of a running engine control unit, a stepper motor steering unit, an electronic differential control unit, a power plant automatic on / off control unit, and battery charging balancing. The developed control system of the robotic vehicle contains a central computer that collects information from sensors and sensors, processes it and transmits control signals to the drives of the machine movement. The movement of the robotic platform is carried out both by a radio signal with a remote control, and in offline mode on a pre-set map of the area according to data from the GLONASS/GPS differential receiver of the satellite navigation system. It is also possible to independently control the movement of a robotic platform using a vision system. The autonomy of the robotic platform provides 10 hours of continuous operation in low-light conditions in various weather conditions.
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B Lima, Glaydson Luiz, Osamu Saotome, and Ijar M. Da Fonseca. "Inspection and control system for experiments in space robotics." South Florida Journal of Development 2, no. 3 (2021): 4094–104. http://dx.doi.org/10.46932/sfjdv2n3-023.
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The communication subsystem is one among the various subsystems of a telerobotic space system. It is responsible for coordinating the commands received from the teleoperator control subsystem to the robotic arm, for reading signals from the sensors, and for stating the communication of the telerobot with the ground station. The telerobotic experiment under development by the ITA space robotics research group was developed with the purpose of investigating a robotic space system dynamics and control, including the study of the working and integration of all subsystems involved in the teleoperation control. The lab experiment consists of two identical units of robot manipulators, each of them mounted on its own floating air-supported platform. The objective is to simulate computationally the operations of rendezvous and capture in the microgravity' orbital environment, emulated by the floating manipulators' dynamics. The closed circuit for this system involves the in time position detection, transmission and data processing by using a position-tracking (X, Y, and Z) computer system combined with a Kinect sensor (RGB-D). The computer system comprises two computers capable of processing the positional images with greater accuracy. One of them receive and send the sensor data to a second computer which performs the data processing by proper algorithms in Matlab® and Simulink and sends commands to the robotic arm via WIFI (UDP protocol) network. The robot receives and executes the control signals moving the robotic arms whose position is again detected by the kinect sensor and informed back to the computer system, closing the control mesh and allowing the safe capture of the target. This work deals with the communication subsystem of the space robot experiment and its ability to set an integrated and efficient communication satisfying the telerobot control requirements