Quantification of Joint Redundancy considering Dynamic Feasibility using Deep Reinforcement Learning
Jiazheng Chai,Mitsuhiro Hayashibe,Jiazheng Chai,Mitsuhiro Hayashibe
The robotic joint redundancy for executing a task and the optimal usage of robotic joints given the redundant degrees of freedom are crucial for the performance of a robot. It is therefore of interest to quantify the joint redundancy to better understand the robotic dexterity considering the dynamic feasibility. To this end, model-based approaches have been among the most commonly used methods to ...
