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!