PyRep: Bringing V-REP to Deep Robot Learning
This toolkit addresses the need for efficient simulation in robot learning research, though it is incremental as it builds upon existing V-REP software.
The researchers tackled the challenge of slow and inflexible robot learning simulation by developing PyRep, a toolkit built on V-REP that offers a flexible API, new rendering engine, and speed boosts up to 10,000x, enabling rapid prototyping in areas like reinforcement learning and computer vision.
PyRep is a toolkit for robot learning research, built on top of the virtual robotics experimentation platform (V-REP). Through a series of modifications and additions, we have created a tailored version of V-REP built with robot learning in mind. The new PyRep toolkit offers three improvements: (1) a simple and flexible API for robot control and scene manipulation, (2) a new rendering engine, and (3) speed boosts upwards of 10,000x in comparison to the previous Python Remote API. With these improvements, we believe PyRep is the ideal toolkit to facilitate rapid prototyping of learning algorithms in the areas of reinforcement learning, imitation learning, state estimation, mapping, and computer vision.