Robust Relative Hand Placement For Bi-Manual Tasks
Anirban Sinha, Nilanjan Chakraborty

TL;DR
This paper introduces a method to compute robust inverse kinematics solutions for bi-manual robots, ensuring high-probability success in tasks like peg-in-a-hole assembly despite actuation errors.
Contribution
It develops a systematic approach to find joint configurations that keep task errors below a threshold with high probability, improving reliability in bi-manual tasks.
Findings
The method successfully reduces task error variability in simulations.
It enables robots to self-assess task feasibility under actuation uncertainties.
Numerical results demonstrate improved success rates in peg-in-a-hole assembly.
Abstract
In many bi-manual robotic tasks, like peg-in-a-hole assembly, the success of the task execution depends on the error in achieving the desired relative pose between the peg and the hole in a pre-insertion configuration. Random actuation errors in the joint space usually prevent the two arms from reaching their desired task space poses, which in turn results in a random error in relative pose between the two hands. This random error varies from trial to trial, and thus depending on the tolerance between the peg and the hole, the outcome of the assembly task may be random (sometimes the task execution succeeds and sometimes it fails). In general, since the relative pose has degrees-of-freedom, there are infinite numbers of joint space solutions for the two arms that correspond to the same task space relative pose. However, in the presence of actuation errors, the joint space solutions…
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Taxonomy
TopicsRobotic Mechanisms and Dynamics · Robot Manipulation and Learning · Soft Robotics and Applications
