RLBotics: Reinforcement Learning Skills

WARNING

RLBotics is not yet released.

This module is under active development and will be available in a future Telekinesis SDK release.

INFO

RLBotics is a module in the Telekinesis SDK for reinforcement learning (RL) skills in robotics.

It provides tools to train RL policies, simulate them, and deploy them sim-to-sim or sim-to-real, so you can run learned behaviors in simulation or on real hardware with a single pipeline.

When to Use RLBotics?

Use RLBotics for robotics applications that require learned control and behaviors, such as:

• Training RL policies for locomotion, manipulation, or control in simulation
• Simulating and validating policies before deployment
• Deploying policies sim-to-sim (e.g., from one simulator to another) or sim-to-real (from simulation to real robots)
• Integrating learned control into Physical AI pipelines alongside perception and planning

What Does RLBotics Provide?

RLBotics includes a collection of modular skills for:

• Training RL policies in simulation with support for common algorithms and backends
• Running and debugging policies in simulation (stress-testing, tuning, validation)
• Sim-to-sim deployment: running the same policy across different simulators
• Sim-to-real deployment: transferring policies from simulation to real robots with a unified interface