Implicit Kinematic Policies: Unifying Joint and Cartesian Action Spaces in End-to-End Robot Learning
Aditya Ganapathi,Pete Florence,Jake Varley,Kaylee Burns,Ken Goldberg,Andy Zeng,Aditya Ganapathi,Pete Florence,Jake Varley,Kaylee Burns,Ken Goldberg,Andy Zeng
Action representation is an important yet often overlooked aspect in end-to-end robot learning with deep networks. Choosing one action space over another (e.g. target joint positions, or Cartesian end-effector poses) can result in surprisingly stark performance differences between various downstream tasks - and as a result, considerable research has been devoted to finding the right action space f...
