Relative Contact Velocity-Controlled Hand-Object Mechanism for Dexterous Tool Manipulation
Overview
This work proposes a unified hand-object mechanism (HOM) framework to enable general multi-finger robotic hands to perform complete tool manipulation, including picking up tools, loading them into suitable poses, and wielding them. By modeling the hand and tool as sub-assemblies with relative contact velocity and force constraints, the authors developed a lightweight motion planning and contact estimation framework using least squares and a complementary filter. Evaluated in simulation via teleoperation of five different robotic hands, the framework successfully enabled all hands to execute the complete tool manipulation process from simple reference trajectories, demonstrating adaptability across different hands, tools, and tasks.
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Environment: simulation
“ons, we developed a lightweight and physically interpretable motion planning and contact estimation framework using least squares and a complementary filter. We evaluated our framework in simulation by teleoperating five different robotic hands. The results show that our framework enabled all five hands to execute the complete tool manipulation process, achieving dexterous behaviors even from identical, simple refere”
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Control: teleoperated
“ons, we developed a lightweight and physically interpretable motion planning and contact estimation framework using least squares and a complementary filter. We evaluated our framework in simulation by teleoperating five different robotic hands. The results show that our framework enabled all five hands to execute the complete tool manipulation process, achieving dexterous behaviors even from identical, simple refere”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalRelative Contact Velocity-Controlled Hand-Object Mechanism for Dexterous Tool Manipulation
This work proposes a unified hand-object mechanism (HOM) framework to enable general multi-finger robotic hands to perform complete tool manipulation, including picking up tools, loading them into suitable poses, and wielding them. By modeling the hand and tool as sub-assemblies with relative contact velocity and force constraints, the authors developed a lightweight motion planning and contact estimation framework using least squares and a complementary filter. Evaluated in simulation via teleoperation of five different robotic hands, the framework successfully enabled all hands to execute the complete tool manipulation process from simple reference trajectories, demonstrating adaptability across different hands, tools, and tasks.
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