Статті в журналах з теми "Semantic coupling of task and motion planning"
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1
Lagriffoul, Fabien, and Benjamin Andres. "Combining task and motion planning: A culprit detection problem." International Journal of Robotics Research 35, no. 8 (January 21, 2016): 890–927. http://dx.doi.org/10.1177/0278364915619022.
Анотація:
Solving problems combining task and motion planning requires searching across a symbolic search space and a geometric search space. Because of the semantic gap between symbolic and geometric representations, symbolic sequences of actions are not guaranteed to be geometrically feasible. This compels us to search in the combined search space, in which frequent backtracks between symbolic and geometric levels make the search inefficient. We address this problem by guiding symbolic search with rich information extracted from the geometric level through culprit detection mechanisms.
2
Lee, Seokjun, and Incheol Kim. "Constraint Satisfaction for Motion Feasibility Checking." Mathematical Problems in Engineering 2021 (May 27, 2021): 1–16. http://dx.doi.org/10.1155/2021/2334236.
Анотація:
Task and motion planning (TAMP) is a key research field for robotic manipulation tasks. The goal of TAMP is to generate motion-feasible task plan automatically. Existing methods for checking motion feasibility of task plan skeletons have some limitations of semantic-free pose candidate sampling, weak search heuristics, and early value commitment. In order to overcome these limitations, we propose a novel constraint satisfaction framework for checking motion feasibility of task plan skeletons. Our framework provides (1) a semantic pose candidate sampling method, (2) novel variable and constraint ordering heuristics based on intra- and inter-action dependencies in a task plan skeleton, and (3) an efficient search strategy using constraint propagation. Based upon these techniques, our framework can improve the efficiency of motion feasibility checking for TAMP. From experiments using the humanoid robot PR2, we show that the motion feasibility checking in our framework is 1.4x to 6.0x faster than previous ones.
3
Luan, Zhirong, Yujun Lai, Rundong Huang, Shuanghao Bai, Yuedi Zhang, Haoran Zhang, and Qian Wang. "Enhancing Robot Task Planning and Execution through Multi-Layer Large Language Models." Sensors 24, no. 5 (March 6, 2024): 1687. http://dx.doi.org/10.3390/s24051687.
Анотація:
Large language models have found utility in the domain of robot task planning and task decomposition. Nevertheless, the direct application of these models for instructing robots in task execution is not without its challenges. Limitations arise in handling more intricate tasks, encountering difficulties in effective interaction with the environment, and facing constraints in the practical executability of machine control instructions directly generated by such models. In response to these challenges, this research advocates for the implementation of a multi-layer large language model to augment a robot’s proficiency in handling complex tasks. The proposed model facilitates a meticulous layer-by-layer decomposition of tasks through the integration of multiple large language models, with the overarching goal of enhancing the accuracy of task planning. Within the task decomposition process, a visual language model is introduced as a sensor for environment perception. The outcomes of this perception process are subsequently assimilated into the large language model, thereby amalgamating the task objectives with environmental information. This integration, in turn, results in the generation of robot motion planning tailored to the specific characteristics of the current environment. Furthermore, to enhance the executability of task planning outputs from the large language model, a semantic alignment method is introduced. This method aligns task planning descriptions with the functional requirements of robot motion, thereby refining the overall compatibility and coherence of the generated instructions. To validate the efficacy of the proposed approach, an experimental platform is established utilizing an intelligent unmanned vehicle. This platform serves as a means to empirically verify the proficiency of the multi-layer large language model in addressing the intricate challenges associated with both robot task planning and execution.
4
Niu, Guochen, Yunxiao Zhang, and Wenshuai Li. "Path Planning of Continuum Robot Based on Path Fitting." Journal of Control Science and Engineering 2020 (December 22, 2020): 1–11. http://dx.doi.org/10.1155/2020/8826749.
Анотація:
The Continuum Robot has a multiredundant dof structure, which is extremely advantageous in the unstructured environment, and can complete such tasks as aircraft fuel tank inspection. However, due to its complex kinematics and coupling of joint motion, its motion path planning is also a challenging task. In this paper, a path planning method for Continuum Robot based on an equal curvature model in an aircraft fuel tank environment is proposed. Considering the complexity of calculation and the structural characteristics of Continuum Robot, a feasible obstacle avoidance discrete path is obtained by using the improved RRT algorithm. Then, joint fitting is performed on the existing discrete path according to the kinematic model of Continuum Robot, joint obstacle avoidance was conducted in the process of fitting, and finally, a motion path suitable for the Continuum Robot was selected. A reasonable experiment is designed based on MATLAB, and simulation and analysis results demonstrate excellent performance of this method and feasibility of path planning.
5
Bit-Monnot, Arthur, Rafael Bailon-Ruiz, and Simon Lacroix. "A Local Search Approach to Observation Planning with Multiple UAVs." Proceedings of the International Conference on Automated Planning and Scheduling 28 (June 15, 2018): 437–45. http://dx.doi.org/10.1609/icaps.v28i1.13924.
Анотація:
Observation planning for Unmanned Aerial Vehicles (UAVs) is a challenging task as it requires planning trajectories over a large continuous space and with motion models that can not be directly encoded into current planners. Furthermore, realistic problems often require complex objective functions that complicate problem decomposition. In this paper, we propose a local search approach to plan the trajectories of a fleet of UAVs on an observation mission. The strength of the approach lies in its loose coupling with domain specific requirements such as the UAV model or the objective function that are both used as black boxes. Furthermore, the Variable Neighborhood Search (VNS) procedure considered facilitates the adaptation of the algorithm to specific requirements through the addition of new neighborhoods. We demonstrate the feasibility and convenience of the method on a large joint observation task in which a fleet of fixed-wing UAVs maps wildfires over areas of a hundred square kilometers. The approach allows generating plans over tens of minutes for a handful of UAVs in matter of seconds, even when considering very short primitive maneuvers.
6
Jia, Qingxuan, Bonan Yuan, Gang Chen, and Yingzhuo Fu. "Kinematic and Dynamic Characteristics of the Free-Floating Space Manipulator with Free-Swinging Joint Failure." International Journal of Aerospace Engineering 2019 (September 12, 2019): 1–22. http://dx.doi.org/10.1155/2019/2679152.
Анотація:
For the free-floating space manipulator with free-swinging joint failure, motions among its active joints, passive joints, free-floating base, and end-effector are coupled. It is significant to make clear all motion coupling relationships, which are defined as “kinematic coupling relationships” and “dynamic coupling relationships,” inside the system. With the help of conservation of system momentum, the kinematic model is established, and velocity mapping relation between active joints and passive joints, velocity mapping relation between active joints and base, velocity mapping relation between active joints and end-effector. We establish the dynamic model based on the Lagrange equation, and the system inertia matrix is partitioned according to the distribution of active joints, passive joints, and the base. Then, kinematic and dynamic coupling relationships are explicitly derived, and coupling indexes are defined to depict coupling degree. Motions of a space manipulator with free-swinging joint failure simultaneously satisfy the first-order nonholonomic constraint (kinematic coupling relationships) and the second-order nonholonomic constraint (dynamic coupling relationships), and the manipulator can perform tasks through motion planning and control. Finally, simulation experiments are carried out to verify the existence and correctness of the first-order and second-order nonholonomic constraints and display task execution effects of the space manipulator. This research analyzes the kinematic and dynamic characteristics of the free-floating space manipulator with free-swinging joint failure for the first time. It is the theoretical basis of free-swinging joint failure treatment for a space manipulator.
7
Lewkowicz, Daniel, and Yvonne N. Delevoye-Turrell. "Predictable real-time constraints reveal anticipatory strategies of coupled planning in a sequential pick and place task." Quarterly Journal of Experimental Psychology 73, no. 4 (November 20, 2019): 594–616. http://dx.doi.org/10.1177/1747021819888081.
Анотація:
Planning a sequence of two motor elements is much more than concatenating two independent movements. However, very little is known about the cognitive strategies that are used to perform fluent sequences for intentional object manipulation. In this series of studies, the participants’ task was to reach for and pick to place a wooden cylinder to set it on a place pad of three different diameters, which served to modify terminal accuracy constraints. Participants were required to perform the sequences (1) at their preferred speed or (2) as fast as possible. Action kinematics were recorded with the Qualisys motion-capture system in order to implement a real-time protocol to get participants to engage in a true interactive relation. Results revealed that with low internal constraints (at preferred speed), low coupling between the two elements of the motor sequence was observed, suggesting a step-by-step planning strategy. Under high constraints (at fastest speed), an important terminal accuracy effect back propagated to modify early kinematic parameters of the first element, suggesting strong coupling of the parameters in an encapsulated planning strategy. In Studies 2 and 3, we further manipulated instructions and timing constraints to confirm the importance of time and predictability of external information for coupled planning. These findings overall sustain the hypothesis that coupled planning can take place in a pick and place task when anticipatory strategies are possible. This mode of action planning may be the key reason why motor intention can be read through the observation of micro variations in body kinematics.
8
Wei, Rongke, Haodong Pei, Dongjie Wu, Changwen Zeng, Xin Ai, and Huixian Duan. "A Semantically Aware Multi-View 3D Reconstruction Method for Urban Applications." Applied Sciences 14, no. 5 (March 6, 2024): 2218. http://dx.doi.org/10.3390/app14052218.
Анотація:
The task of 3D reconstruction of urban targets holds pivotal importance for various applications, including autonomous driving, digital twin technology, and urban planning and development. The intricate nature of urban landscapes presents substantial challenges in attaining 3D reconstructions with high precision. In this paper, we propose a semantically aware multi-view 3D reconstruction method for urban applications which incorporates semantic information into the technical 3D reconstruction. Our research primarily focuses on two major components: sparse reconstruction and dense reconstruction. For the sparse reconstruction process, we present a semantic consistency-based error filtering approach for feature matching. To address the challenge of errors introduced by the presence of numerous dynamic objects in an urban scene, which affects the Structure-from-Motion (SfM) process, we propose a computation strategy based on dynamic–static separation to effectively eliminate mismatches. For the dense reconstruction process, we present a semantic-based Semi-Global Matching (sSGM) method. This method leverages semantic consistency to assess depth continuity, thereby enhancing the cost function during depth estimation. The improved sSGM method not only significantly enhances the accuracy of reconstructing the edges of the targets but also yields a dense point cloud containing semantic information. Through validation using architectural datasets, the proposed method was found to increase the reconstruction accuracy by 32.79% compared to the original SGM, and by 63.06% compared to the PatchMatch method. Therefore, the proposed reconstruction method holds significant potential in urban applications.
9
Zhao, Yingshen, Philippe Fillatreau, Linda Elmhadhbi, Mohamed Hedi Karray, and Bernard Archimede. "Semantic coupling of path planning and a primitive action of a task plan for the simulation of manipulation tasks in a virtual 3D environment." Robotics and Computer-Integrated Manufacturing 73 (February 2022): 102255. http://dx.doi.org/10.1016/j.rcim.2021.102255.
10
Caballero, Alvaro, Manuel Bejar, Angel Rodriguez-Castaño, and Anibal Ollero. "Motion planning with dynamics awareness for long reach manipulation in aerial robotic systems with two arms." International Journal of Advanced Robotic Systems 15, no. 3 (May 1, 2018): 172988141877052. http://dx.doi.org/10.1177/1729881418770525.
Анотація:
Human activities in maintenance of industrial plants pose elevated risks as well as significant costs due to the required shutdowns of the facility. An aerial robotic system with two arms for long reach manipulation in cluttered environments is presented to alleviate these constraints. The system consists of a multirotor with a long bar extension that incorporates a lightweight dual arm in the tip. This configuration allows aerial manipulation tasks even in hard-to-reach places. The objective of this work is the development of planning strategies to move the aerial robotic system with two arms for long reach manipulation in a safe and efficient way for both navigation and manipulation tasks. The motion planning problem is addressed considering jointly the aerial platform and the dual arm in order to achieve wider operating conditions. Since there exists a strong dynamical coupling between the multirotor and the dual arm, safety in obstacle avoidance will be assured by introducing dynamics awareness in the operation of the planner. On the other hand, the limited maneuverability of the system emphasizes the importance of energy and time efficiency in the generated trajectories. Accordingly, an adapted version of the optimal Rapidly-exploring Random Tree algorithm has been employed to guarantee their optimality. The resulting motion planning strategy has been evaluated through simulation in two realistic industrial scenarios, a riveting application and a chimney repairing task. To this end, the dynamics of the aerial robotic system with two arms for long reach manipulation has been properly modeled, and a distributed control scheme has been derived to complete the test bed. The satisfactory results of the simulations are presented as a first validation of the proposed approach.
11
Tatievskyi, Dmitry. "REALIZATION OF REVERSE MOTION OF THE MODEL OF A SEMITRAILER ROAD TRAIN." EUREKA: Physics and Engineering 3 (May 31, 2018): 59–66. http://dx.doi.org/10.21303/2461-4262.2018.00644.
Анотація:
The complexity of controlling the road train is due to pronounced nonlinearities, as well as the instability of the control object under reverse motion, often leading to a phenomenon known as jackknifing. Because of this, the task of controlling their motion is relevant, both from the theoretical point of view and from the point of view of the practical implementation of software motion with given constraints. The task of controlling the motion of a road train with a semitrailer under the assumption of non-holonomic constraints (the absence of lateral slippage of support wheels) has a great theoretical and applied significance. Research in this field is stimulated by numerous applied problems. For road trains, the location of the towing device behind the rear axle (off-axle hitching model) is quite typical. This model is used in this study. For this model, management and planning methods are proposed, using a diverse mathematical apparatus. Among the most frequently used methods, let’s select the methods of feedback linearization and chain systems, and methods are used, which are exclusively due to the geometric features of the model kinematics formulated in cascade form. Synthesis of control laws can be performed after the linearization of the model by state feedback, using the Lie algebra apparatus, fuzzy logic, using linear-quadratic controllers, nilpotent approximation, and so on. Studies have been carried out on the state of solving the problem associated with the reverse motion of a road train consisting of a hauler and a semitrailer with a coupling sideshift. The synthesized stabilizing control allowed to study the features of such model, determined by its linear dimensions and dynamic parameters. In this study, one of the possibilities of stabilizing the reversal motion of the dynamic model of a two-link road train on a rectilinear and circular track is considered. Synthesis of the stabilizing control is obtained for the case of rectilinear motion, hauler, stable circular stationary regimes are realized. The obtained theoretical relationships that determine the properties of the crew's ability to rotate when moving in reverse, allow the latter to be used when the algorithm is implemented.
12
Travers, Matthew, Julian Whitman, and Howie Choset. "Shape-based coordination in locomotion control." International Journal of Robotics Research 37, no. 10 (March 24, 2018): 1253–68. http://dx.doi.org/10.1177/0278364918761569.
Анотація:
Highly articulated systems are capable of executing a variety of behaviors by coordinating their many internal degrees of freedom to help them move more effectively in complex terrains. However, this inherent variety poses significant challenges that have been the subject of a great deal of previous work: What are the most effective or most efficient methods for achieving the intrinsic coordination necessary to produce desired global objectives? This work takes these questions one step further, asking how different levels of coordination, which we quantify in terms of kinematic coupling, affect articulated locomotion in environments with different degrees of underlying structure. We introduce shape functions as the analytical basis for specifying kinematic coupling relationships that constrain the relative motion among the internal degrees of freedom for a given system during its nominal locomotion. Furthermore, we show how shape functions are used to derive shape-based controllers (SBCs) that manage the compliant interaction between articulated bodies and the environment while explicitly preserving the inter-joint coupling defined by shape functions. Initial experimental evidence provides a comparison of the benefits of different levels of coordination for two separate platforms in environments with different degrees of inherent structure. The experimental results show that decentralized implementations, where there is relatively little inter-joint coupling, perform well across a spectrum of different terrains but that there are potential benefits to higher degrees of coupling in structured terrains. We discuss how this observation has implications related to future planning and control approaches that actively “tune” their underlying structure by dynamically varying the assumed level of coupling as a function of task specification and local environmental conditions.
13
Zhao, Jianwei, Tao Han, Xiaofei Ma, Wen Ma, Chengxiang Liu, Jinyu Li, and Yushuo Liu. "Research on Kinematics Analysis and Trajectory Planning of Novel EOD Manipulator." Applied Sciences 11, no. 20 (October 11, 2021): 9438. http://dx.doi.org/10.3390/app11209438.
Анотація:
To address the problems of mismatch, poor flexibility and low accuracy of ordinary manipulators in the complex special deflagration work process, this paper proposes a new five-degree-of-freedom (5-DOF) folding deflagration manipulator. Firstly, the overall structure of the explosion-expulsion manipulator is introduced. The redundant degrees of freedom are formed by the parallel joint axes of the shoulder joint, elbow joint and wrist pitching joint, which increase the flexibility of the mechanism. Aiming at a complex system with multiple degrees of freedom and strong coupling of the manipulator, the virtual joint is introduced, the corresponding forward kinematics model is established by D–H method, and the inverse kinematics solution of the manipulator is derived by analytical method. In the MATLAB platform, the workspace of the manipulator is analyzed by Monte Carlo pseudo-random number method. The quintic polynomial interpolation method is used to simulate the deflagration task in joint space. Finally, the actual prototype experiment is carried out using the data obtained by simulation. The trajectory planning using the quintic polynomial interpolation method can ensure the smooth movement of the manipulator and high accuracy of operation. Furthermore, the trajectory is basically consistent with the simulation trajectory, which can realize the work requirements of putting the object into the explosion-proof tank. The new 5-DOF folding deflagration manipulator designed in this paper has stable motion and strong robustness, which can be used for deflagration during the COVID-19 epidemic.
14
Karklinsky, Matan, and Tamar Flash. "Timing of continuous motor imagery: the two-thirds power law originates in trajectory planning." Journal of Neurophysiology 113, no. 7 (April 2015): 2490–99. http://dx.doi.org/10.1152/jn.00421.2014.
Анотація:
The two-thirds power law, v = γκ−1/3, expresses a robust local relationship between the geometrical and temporal aspects of human movement, represented by curvature κ and speed v, with a piecewise constant γ. This law is equivalent to moving at a constant equi-affine speed and thus constitutes an important example of motor invariance. Whether this kinematic regularity reflects central planning or peripheral biomechanical effects has been strongly debated. Motor imagery, i.e., forming mental images of a motor action, allows unique access to the temporal structure of motor planning. Earlier studies have shown that imagined discrete movements obey Fitts's law and their durations are well correlated with those of actual movements. Hence, it is natural to examine whether the temporal properties of continuous imagined movements comply with the two-thirds power law. A novel experimental paradigm for recording sparse imagery data from a continuous cyclic tracing task was developed. Using the likelihood ratio test, we concluded that for most subjects the distributions of the marked positions describing the imagined trajectory were significantly better explained by the two-thirds power law than by a constant Euclidean speed or by two other power law models. With nonlinear regression, the β parameter values in a generalized power law, v = γκ−β, were inferred from the marked position records. This resulted in highly variable yet mostly positive β values. Our results imply that imagined trajectories do follow the two-thirds power law. Our findings therefore support the conclusion that the coupling between velocity and curvature originates in centrally represented motion planning.
15
Velez, J., G. Hemann, A. S. Huang, I. Posner, and N. Roy. "Modelling Observation Correlations for Active Exploration and Robust Object Detection." Journal of Artificial Intelligence Research 44 (July 14, 2012): 423–53. http://dx.doi.org/10.1613/jair.3516.
Анотація:
Today, mobile robots are expected to carry out increasingly complex tasks in multifarious, real-world environments. Often, the tasks require a certain semantic understanding of the workspace. Consider, for example, spoken instructions from a human collaborator referring to objects of interest; the robot must be able to accurately detect these objects to correctly understand the instructions. However, existing object detection, while competent, is not perfect. In particular, the performance of detection algorithms is commonly sensitive to the position of the sensor relative to the objects in the scene. This paper presents an online planning algorithm which learns an explicit model of the spatial dependence of object detection and generates plans which maximize the expected performance of the detection, and by extension the overall plan performance. Crucially, the learned sensor model incorporates spatial correlations between measurements, capturing the fact that successive measurements taken at the same or nearby locations are not independent. We show how this sensor model can be incorporated into an efficient forward search algorithm in the information space of detected objects, allowing the robot to generate motion plans efficiently. We investigate the performance of our approach by addressing the tasks of door and text detection in indoor environments and demonstrate significant improvement in detection performance during task execution over alternative methods in simulated and real robot experiments.
16
Li, Jiyong, Hai Huang, Lei Wan, Zexing Zhou, and Yang Xu. "Hybrid Strategy-based Coordinate Controller for an Underwater Vehicle Manipulator System Using Nonlinear Disturbance Observer." Robotica 37, no. 10 (March 12, 2019): 1710–31. http://dx.doi.org/10.1017/s0263574719000213.
Анотація:
SummaryThis paper presents a hybrid strategy-based coordinate controller with a novel nonlinear disturbance observer for autonomous underwater vehicle manipulator systems (UVMSs). This method can reduce the influence from external unknown disturbances, inner coupling effects and model uncertainties by using a modified disturbance observer. Considering the natural redundancy property of the UVMS, the redundancy resolution algorithm is often utilized to give desired trajectories in the vehicle–joint space. However, because of the calibration errors, assembling errors and numerical errors, these desired trajectories may not lead the end-effector to the goal point accurately. To realize accurate motion control even when small errors exist in the planning phase, a hybrid strategy is introduced to transform the controller in the joint–vehicle space to the controller in the task space. Numerical simulations based on a UVMS have been carried out to testify the effectiveness of the proposed coordinate controller and the hybrid strategy. During the simulations, unknown disturbances are exerted upon the system. The trajectory tracking and error fixing performances are discussed in comparative analyses. The controller also maintains robust characteristics in comparison with the passivity-based controller and the proposed controller but without the disturbance observer. Experiments are also carried out to test its performance.
17
Miao, Runqing, Qingxuan Jia, and Fuchun Sun. "Long-term robot manipulation task planning with scene graph and semantic knowledge." Robotic Intelligence and Automation, January 25, 2023. http://dx.doi.org/10.1108/ria-09-2022-0226.
Анотація:
Purpose Autonomous robots must be able to understand long-term manipulation tasks described by humans and perform task analysis and planning based on the current environment in a variety of scenes, such as daily manipulation and industrial assembly. However, both classical task and motion planning algorithms and single data-driven learning planning methods have limitations in practicability, generalization and interpretability. The purpose of this work is to overcome the limitations of the above methods and achieve generalized and explicable long-term robot manipulation task planning. Design/methodology/approach The authors propose a planning method for long-term manipulation tasks that combines the advantages of existing methods and the prior cognition brought by the knowledge graph. This method integrates visual semantic understanding based on scene graph generation, regression planning based on deep learning and multi-level representation and updating based on a knowledge base. Findings The authors evaluated the capability of this method in a kitchen cooking task and tabletop arrangement task in simulation and real-world environments. Experimental results show that the proposed method has a significantly improved success rate compared with the baselines and has excellent generalization performance for new tasks. Originality/value The authors demonstrate that their method is scalable to long-term manipulation tasks with varying complexity and visibility. This advantage allows their method to perform better in new manipulation tasks. The planning method proposed in this work is meaningful for the present robot manipulation task and can be intuitive for similar high-level robot planning.
18
Zhao, Haoming, and Xinling Zhang. "Design of nonlinear control system for motion trajectory of industrial handling robot." Advanced Control for Applications, September 20, 2023. http://dx.doi.org/10.1002/adc2.165.
Анотація:
AbstractIndustrial robot is a and multi‐output complex system with strong coupling and high nonlinearity. The motion control accuracy of the system is affected by many factors. To solve the difficulty in establishing the input and output characteristics of robot dynamics modeling, the robot motion model is established through the Lagrangian energy function. At the same time, the nonlinear relationship between angular velocity, angular acceleration, and robot torque is accurately expressed through improved cascaded neural network. In addition, the optimal time planning of the robot's trajectory in joint space is studied using multinomial interpolation method and the particle swarm optimization (PSO). In the simulation experiment, the effect of the proposed dynamic model fitting was outstanding. Under the mixed multinomial difference calculation planning, the angular position trajectories of the three joints changed very smoothly. In the data set application test, the average error of the PSO algorithm was 0.4061 mm and the average task time was 9.101 s, which were lower than other planning algorithms. Experiments showed that the Lagrangian dynamic model analysis based on genetic algorithm cascaded neural network and PSO trajectory scheduling method under mixed multinomial difference had better trajectory planning performance in handling tasks.
19
Yang, Jing, Lingyan Jin, Zejie Han, Deming Zhao, and Ming Hu. "Sensitivity analysis of factors affecting motion reliability of manipulator and fault diagnosis based on kernel principal component analysis." Robotica, December 10, 2021, 1–20. http://dx.doi.org/10.1017/s0263574721001788.
Анотація:
Abstract As an important index to quantitatively measure the motion performance of a manipulator, motion reliability is affected by many factors, such as joint clearance. The present research utilized a UR10 manipulator as the research object. A factor mapping model for influencing the motion reliability was established. The link flexibility factor, joint flexibility factor, joint clearance factor, and Denavit–Hartenberg (DH) parameters were comprehensively considered in this model. The coupling relationship among the various factors was concisely expressed. Subsequently, the nonlinear response surface method was used to calculate the reliability and sensitivity of the manipulator, which provided an applicable reference for its trajectory planning and motion control. In addition, a data-driven fault diagnosis method based on the kernel principal component analysis (KPCA) was used to verify the motion accuracy and sensitivity of the manipulator, and joint rotation failure was considered as an example to verify the accuracy of the KPCA method. This study on the motion reliability of the manipulator is of great significance for the current motion performance, adjusting the control strategy and optimizing the completion effect of the motion task of a manipulator.
20
Stebani, Jannik, Martin Blaimer, Simon Zabler, Tilmann Neun, Daniël M. Pelt, and Kristen Rak. "Towards fully automated inner ear analysis with deep-learning-based joint segmentation and landmark detection framework." Scientific Reports 13, no. 1 (November 4, 2023). http://dx.doi.org/10.1038/s41598-023-45466-9.
Анотація:
AbstractAutomated analysis of the inner ear anatomy in radiological data instead of time-consuming manual assessment is a worthwhile goal that could facilitate preoperative planning and clinical research. We propose a framework encompassing joint semantic segmentation of the inner ear and anatomical landmark detection of helicotrema, oval and round window. A fully automated pipeline with a single, dual-headed volumetric 3D U-Net was implemented, trained and evaluated using manually labeled in-house datasets from cadaveric specimen ($$N=43$$ N = 43 ) and clinical practice ($$N=9$$ N = 9 ). The model robustness was further evaluated on three independent open-source datasets ($$N = 23{} + 7{} + 17$$ N = 23 + 7 + 17 scans) consisting of cadaveric specimen scans. For the in-house datasets, Dice scores of $$\text{0.97 and 0.94}$$ 0.97 and 0.94 , intersection-over-union scores of $$\text{0.94 and 0.89}$$ 0.94 and 0.89 and average Hausdorff distances of $$0.065{}$$ 0.065 and $$0.14{}$$ 0.14 voxel units were achieved. The landmark localization task was performed automatically with an average localization error of $$\text{3.3 and 5.2}$$ 3.3 and 5.2 voxel units. A robust, albeit reduced performance could be attained for the catalogue of three open-source datasets. Results of the ablation studies with 43 mono-parametric variations of the basal architecture and training protocol provided task-optimal parameters for both categories. Ablation studies against single-task variants of the basal architecture showed a clear performance benefit of coupling landmark localization with segmentation and a dataset-dependent performance impact on segmentation ability.