CRISP -- Compliant ROS2 Controllers for Learning-Based Manipulation Policies and Teleoperation

Understand

Learning-based controllers, such as diffusion policies and vision-language action models, often generate low-frequency or discontinuous robot state changes.

• Achieving smooth reference tracking requires a low-level controller that converts high-level targets commands into joint torques, enabling compliant behavior during contact interactions.
• We present CRISP, a lightweight C++ implementation of compliant Cartesian and joint-space controllers for the ROS2 control standard, designed for seamless integration with high-level learning-based policies as well as teleoperation.
• The controllers are compatible with any manipulator that exposes a joint-torque interface.