ORCHID: Optimisation of Robotic Control and Hardware In Design using Reinforcement Learning
Lucy Jackson,Celyn Walters,Steve Eckersley,Pete Senior,Simon Hadfield,Lucy Jackson,Celyn Walters,Steve Eckersley,Pete Senior,Simon Hadfield
The successful performance of any system is dependant on the hardware of the agent, which is typically immutable during RL training. In this work, we present ORCHID (Optimisation of Robotic Control and Hardware In Design) which allows for truly simultaneous optimisation of hardware and control parameters in an RL pipeline. We show that by forming a complex differential path through a trajectory ro...
