Learning Reachable Manifold and Inverse Mapping for a Redundant Robot manipulator
Seungsu Kim Julien Perez Seungsu Kim Julien Perez
Validating the kinematic feasibility of a planned robot motion and finding corresponding inverse solutions are time-consuming processes, especially for long-horizon manipulation tasks. Most existing approaches are based on solving iterative gradient-based optimization, so the processes are time-consuming and have a high risk of falling in local minima. In this work, we propose a unified framework ...