Solving Dexterous Manipulation Tasks with Trajectory Optimisation and Reinforcement Learning
Henry Charlesworth and Giovanni Montana
WMG, University of Warwick, UK
- 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
By Henry Charlesworth