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Vision-based Online Learning Kinematic Control for Soft Robots using Local Gaussian Process Regression
2019
IEEE Robotics and Automation Letters
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Index Terms-Eye-in-hand visual-servo, Learning-based control, Local Gaussian process regression, Soft robot control. ...
Local Gaussian process regression (GPR) is used to initialize and refine the inverse mappings online, without prior knowledge of robot and camera parameters. ...
Vision-based Online Learning Kinematic Control for Soft Robots using Local Gaussian Process Regression In this paper, we propose an adaptive eye-in-hand visual servo control framework based on local online ...
doi:10.1109/lra.2019.2893691
fatcat:cifzcd3xwbc77drnd3viekjmai
A Survey for Machine Learning-Based Control of Continuum Robots
2021
Frontiers in Robotics and AI
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In this article, we attempt to overview the current state of kinematic/dynamic model-free control schemes for continuum manipulators, particularly by learning-based means, and discuss their similarities ...
To this end, data-driven modeling strategies making use of machine learning algorithms would be an encouraging way out for the control of soft continuum robots. ...
Figure 3 describes the pipeline of reinforcement learning algorithms in soft manipulator control. ...
doi:10.3389/frobt.2021.730330
pmid:34692777
pmcid:PMC8527450
fatcat:p4yeo5jqajfhphzsdbiu746swa
2020 Index IEEE Robotics and Automation Letters Vol. 5
2020
IEEE Robotics and Automation Letters
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., +, LRA Oct. 2020 6772-6779
Full-Pose Manipulation Control of a Cable-Suspended Load With Multiple
UAVs Under Uncertainties. ...
Sasaki, H., +, LRA July 2020 4533-4540
Full-Pose Manipulation Control of a Cable-Suspended Load With Multiple
UAVs Under Uncertainties. ...
doi:10.1109/lra.2020.3032821
fatcat:qrnouccm7jb47ipq6w3erf3cja
Table of Contents
2021
IEEE Robotics and Automation Letters
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Nejat 1793 Lightweight 3-D Localization and Mapping for Solid-State LiDAR .
2745 Self-Supervised Learning of Domain-Invariant Local Features for Robust Visual Localization Under Challenging Conditions ...
Tadokoro 3073 FEM-Based Gain-Scheduling Control of a Soft Trunk Robot .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Wu and G. ...
doi:10.1109/lra.2021.3072707
fatcat:qyphyzqxfrgg7dxdol4qamrdqu
Table of Contents
2022
IEEE transactions on industrial electronics (1982. Print)
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Merzouki A Simultaneous Learning and Control Scheme for Redundant Manipulators With Physical Constraints on Decision Variable and Its Derivative . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Yan Parametric PH Curves Model Based Kinematic Control of the Shape of Mobile Soft Manipulators in Unstructured Environment . . . . . . . . . . . . . . . . . . . . . . . . . S. Mbakop, G. Tagne, S. ...
doi:10.1109/tie.2022.3171155
fatcat:frmcc3zr2bggxpp43mzvmofupy
Table of Contents
2021
IEEE Robotics and Automation Letters
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Pacchierotti 4859 An Overall Configuration Planning Method of Continuum Hyper-Redundant Manipulators Based on Improved ArtificialPotential Field Method .. . . . . . . . . . . . . . . . . . . . . . . ...
Righetti 4766 Tracking Control of a Miniature 2-DOF Manipulator With Hydrogel Actuators .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/lra.2021.3095987
fatcat:uyk6vlvv45hifbzj4ruzdi6w54
Table of Contents
2020
IEEE Robotics and Automation Letters
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Asada 2177 Full-Pose Manipulation Control of a Cable-Suspended Load With Multiple UAVs Under Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Barfoot 1429 A Probabilistic Model-Based Online Learning Optimal Control Algorithm for Soft Pneumatic Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/lra.2020.2987582
fatcat:3qafzip5xrg5jliyngq4xxvjha
Model-Based FDI Schemes For Robot Manipulators Using Soft Computing Techniques
[chapter]
2010
Fault Detection
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FDI Schemes For Robot Manipulators Using Soft Computing Techniques 143 Computed Torque control is a special application of feedback linearization of nonlinear systems to robotics. ...
Robot manipulator used in the simulations is a two-link planar manipulator under gravity and masses of the links are defined at the end of the links (Lewis et al., 1993) . ...
Model-Based FDI Schemes For Robot Manipulators Using Soft Computing Techniques, Fault Detection, Wei Zhang (Ed.), ISBN: 978-953-307-037-7, InTech, Available from: http://www.intechopen.com/books/fault-detection ...
doi:10.5772/9071
fatcat:ndl7j6hn2feufggyhchmelenim
2021 Index IEEE Transactions on Robotics Vol. 37
2021
IEEE Transactions on robotics
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
Note that the item title is found only under the primary entry in the Author Index. ...
Predictive End-Effector Control of Manipulators on Moving Platforms Under Disturbance. Woolfrey, J., +, TRO Dec. 2021 2210-2217 Toward Orientation Learning and Adaptation in Cartesian Space. ...
doi:10.1109/tro.2022.3141270
fatcat:wbcpmrap6ndprec2gtu7m2yhmy
Design, Control, and Applications of a Soft Robotic Arm
[article]
2020
arXiv
pre-print
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In order to design a soft arm with large load capacity, several design principles are proposed by analyzing two kinds of buckling issues, under which we present a novel structure named Honeycomb Pneumatic ...
This paper presents the design, control, and applications of a multi-segment soft robotic arm. ...
Funding This research is supported by the National Natural Science Foundation of China under grant 61573333. ...
arXiv:2007.04047v1
fatcat:nzefed5r6fcgnnywb6rhqx2wa4
2019 Index IEEE Robotics and Automation Letters Vol. 4
2019
IEEE Robotics and Automation Letters
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., +, Based Active Safe Control of a Variable Stiffness Soft Actuator. ...
., +, LRA July 2019 2691-2698 Vision-Based Online Learning Kinematic Control for Soft Robots Using Local Gaussian Process Regression. ...
Permanent magnets Adaptive Dynamic Control for Magnetically Actuated Medical Robots. ...
doi:10.1109/lra.2019.2955867
fatcat:ckastwefh5chhamsravandtnx4
Table of contents
2006
Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.
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On Redundant Flagged Manipulators . ...
Murray Adaptive Observer for the Calibration of the Force-Moment Sensor of a Space Robot . . 1667
Kourosh Parsa, Farhad Aghili Optical Torque Sensors for Implementation of Local Impedance Control ...
A New Motion Control Hardware Architecture with FPGA-Based IC Design for Robotic Manipulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/robot.2006.1641151
fatcat:f5zhr6x7trhazlcmsvfdhkpqm4
Soft Robotics as an Enabling Technology for Agroforestry Practice and Research
2019
Sustainability
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However, current soft robotic arms are difficult to design and control, slow to actuate, and have limited payloads. ...
The shortage of qualified human labor is a key challenge facing farmers, limiting profit margins and preventing the adoption of sustainable and diversified agroecosystems, such as agroforestry. ...
Closed loop control, coupled with online policy adaptation based on the feedback, could significantly improve the tracking performance. ...
doi:10.3390/su11236751
fatcat:awwqdn2iargxxcwyixb6rgd6hi
2018 Index IEEE/ASME Transactions on Mechatronics Vol. 23
2018
IEEE/ASME transactions on mechatronics
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., +, TMECH April 2018 690-701
Manipulators
A DMPs-Based Framework for Robot Learning and Generalization of Hu-
manlike Variable Impedance Skills. ...
., +, TMECH Dec. 2018 2587-2598 Online Reconfiguration of a Variable-Stiffness Actuator. ...
1981 -1992 Improved NO and NO2 Concentration Estimation for a Diesel-Engine-Aftertreatment System. Zhang, H., +, TMECH Feb. 2018 190-199 ...
doi:10.1109/tmech.2019.2893551
fatcat:ds4rb6mpw5bnbbbrdn25n3oh6m
Review on generic methods for mechanical modeling, simulation and control of soft robots
2022
PLoS ONE
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In this review paper, we are interested in the models and algorithms that allow generic simulation and control of a soft robot. ...
Moreover, we refer to dynamic control algorithms based on mechanical models, allowing for robust control of the positioning of the robot. ...
Indeed it is the authors' belief that those methods allow to bridge the gap between rigid and soft robots, thus allowing to use common robotic tools, such as inverse models, kinematic and dynamic control ...
doi:10.1371/journal.pone.0251059
pmid:35030170
pmcid:PMC8759680
fatcat:igsjjyai2befdne4jgiuxfqlzy
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