This paper investigates data-oriented inverse kinematics models in a soft robot prototype using fiducial markers to get shape information.
The results demonstrate the potential of visual feedback combined with machine learning to assist the manipulator estimate control actions to reach a ...
This paper investigates data-oriented inverse kinematics models in a soft robot prototype using fiducial markers to get shape information. A missing values ...
A position control algorithm, which controls finger angular trajectories (angular position and velocity), was developed based on motion sensor feedback. The ...
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Data-oriented Inverse Kinematics Applied to Soft Robots With Fiducial Markers for Shape Feedback. LARS/SBR/WRE 2023: 182-187. [c2]. view. electronic edition ...
... Data driven for soft robots modeling often learn and generates a robot's inverse kinematics [109, 110] . Several approaches have consequently emerged using ...
Missing: Fiducial | Show results with:Fiducial
This paper investigates data-oriented inverse kinematics models in a soft robot prototype using fiducial markers to get shape information. ...
Data-oriented Inverse Kinematics Applied to Soft Robots With Fiducial Markers for Shape Feedback. LARS/SBR/WRE 2023: 182-187; 2021. [j4]. view. electronic ...
Editorial: Machine Learning Techniques for Soft Robots | Semantic ...
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Data-oriented Inverse Kinematics Applied to Soft Robots With Fiducial Markers for Shape Feedback · Engineering, Computer Science. Latin American Robotics ...
This work takes a direct data-driven approach to learn the kinematics of the three-dimensional shape of a soft robot, by using visual markers. No prior ...
Missing: Fiducial | Show results with:Fiducial