Flexibility-Aware Robotic Manipulation: Deformation Estimation, Kinematics, and Control via Distributed Inertial Measurement
Flexibility-Aware Robotic Manipulation: Deformation Estimation, Kinematics, and Control via Distributed Inertial Measurement
This research introduces a flexibility-aware manipulation framework that addresses the limitations of rigid-body assumptions in flexible robot links. By identifying dominant vibration modes using response-convergence and excitation-bandwidth criteria, the method determines the minimum observable IMU configuration required for accurate deformation reconstruction. The reconstructed continuous link deformation is integrated into forward kinematics and a PDE-based controller. Experiments on hydraulic single- and double-link manipulators demonstrate that this approach achieves end-effector root mean square errors of 0.0107 m, 0.0194 m, and 0.0102 rad while utilizing fewer sensors than piecewise-rigid methods, enabling real-time flexibility-aware manipulation.
The paper proposes a framework for flexible robot manipulation that identifies dominant vibration modes to minimize IMU requirements, achieving specific end-effector error metrics on hydraulic manipulators.
Source: arXiv Robotics — research abstracts · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
end-effector root mean square error (m)
0.0107
View original evidence
ility-aware forward kinematics and a deformation-informed partial differential equation-based controller. Experiments on hydraulic single- and double-link manipulators evaluate the framework. On the long-reach double-link platform, the proposed kinematics achieves end-effector root mean square errors of $0.0107$~m, $0.0194$~m, and $0.0102$~rad while using fewer sensors than the piecewise-rigid method. Closed-loop rea
Open source S4end-effector root mean square error (m)
0.0194
View original evidence
ility-aware forward kinematics and a deformation-informed partial differential equation-based controller. Experiments on hydraulic single- and double-link manipulators evaluate the framework. On the long-reach double-link platform, the proposed kinematics achieves end-effector root mean square errors of $0.0107$~m, $0.0194$~m, and $0.0102$~rad while using fewer sensors than the piecewise-rigid method. Closed-loop rea
Open source S4end-effector root mean square error (rad)
0.0102
View original evidence
ility-aware forward kinematics and a deformation-informed partial differential equation-based controller. Experiments on hydraulic single- and double-link manipulators evaluate the framework. On the long-reach double-link platform, the proposed kinematics achieves end-effector root mean square errors of $0.0107$~m, $0.0194$~m, and $0.0102$~rad while using fewer sensors than the piecewise-rigid method. Closed-loop rea
Open source S4
- paper: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
ility-aware forward kinematics and a deformation-informed partial differential equation-based controller. Experiments on hydraulic single- and double-link manipulators evaluate the framework. On the long-reach double-link platform, the proposed kinematics achieves end-effector root mean square errors of $0.0107$~m, $0.0194$~m, and $0.0102$~rad while using fewer sensors than the piecewise-rigid method. Closed-loop rea
Open source S4
ching experiments further demonstrate real-time integration of IMU-estimated joint states and reconstructed deformation into the proposed controller. The results show that dominant modal information can determine sensing requirements and enable real-time flexibility-aware robotic manipulation.
Open source S5
Source：arXiv Robotics — research abstracts · arxiv.org