Solving Dexterous Manipulation Tasks with Trajectory Optimisation and Reinforcement Learning
Henry Charlesworth and Giovanni Montana
WMG, University of Warwick, UK
ICML 2021
Motivation
Most robots in industry use parallel jaw grippers to manipulate objects.
Developing autonomous robots that can perform a wider variety of tasks in unstructured/uncertain environments will require more sophisticated manipulators.
The human hand is probably the most versatile and sophisticated manipulator we know of.
Natural to try and create robotic hands based on a human hand - and to try and train those robotic hands to perform complex manipulation tasks!
Solving Dexterous Manipulation Tasks with RL and TrajOpt - ICML
