RCS (Robotic Control Stack)#
RCS is a modular toolset designed to streamline the process of setting up and running robotics experiments and simulations. Rather than being a rigid framework, RCS acts as a minimalist, scalable architecture that brings together existing tools into an integrated system with simple, unified interfaces.
Key Characteristics#
Unified Simulation and Hardware Interface
Seamless transitions between simulation and physical robot execution, reducing potential obstacles in development and testing cycles.Minimal Dependencies
Lightweight and easy to set up, ensuring high portability across environments.Robot-Agnostic Design
Initially developed for the Franka Research 3 robot, but equipped with abstraction layers to easily support other robot types.Gymnasium-Style API
Offers a familiar and standardized interface for reinforcement learning, promoting ease of integration.
Use Cases of RCS#
Teleoperation for Data Collection
RCS supports teleoperation to manually control robots and collect expert task demonstrations, which are essential for training robotics foundation models (RFMs).Policy-Based Control with RFMs
RCS allows robots to be controlled using trained AI policies, including those from RFMs, by providing a modular interface for easy policy switching and remote inference execution.Modular Inverse Kinematics
The RCS architecture enables users to configure and swap inverse kinematics (IK) algorithms without modifying code, demonstrating the system’s modularity and flexibility.