Custom Environments and Algorithms
Custom Environments and Algorithms
rlbotics is not tied to a simulator or to PPO - implement the VecEnv interface and the runner trains against it, or pass your own algorithm class to the runner.
TIP
Install with pip install telekinesis-rlbotics — see Install Support for Reinforcement Learning for the simulator backends.
Your Own Environment
VecEnv is three methods and a handful of attributes. The three built-in adapters for Gymnasium, mjlab and Isaac Lab are each about 200 lines and are the reference implementations.
Your Own Algorithm
The runner owns the loop and calls into the algorithm through a fixed set of methods, so anything implementing them can take PPO's place.
Where to Go Next?
You have reached the end of the tutorial series. Revisit any section from the overview.
Tutorials Overview
Browse every tutorial category - computer vision, robotics, hardware interfaces, camera calibration, infrastructure, and reinforcement learning.
Back to overview →