Limiting Kinetic Energy through Control Barrier Functions: Analysis and Experimental Validation
Federico Califano, Daniël Dylan Logmans, Wesley Roozing
AI summary
Problem
Collaborative robots require reliable safety guarantees to prevent human injury during physical contact, yet existing energy-limiting methods often depend on complex passivity frameworks or auxiliary energy tanks that complicate real-time implementation.
Approach
The authors implement a Control Barrier Function as a safety filter that directly bounds kinetic energy by minimally modifying the nominal control input through targeted damping injection.
Key results
- Analytical proof that the safety filter only injects non-positive power (damping)
- Derivation of steady-state kinetic energy error bounds under unmodelled external forces
- Experimental validation on a 7-DoF Franka Panda robot across multiple collision scenarios
- Demonstration of a minimally invasive, passivity-preserving safety layer without auxiliary energy tanks
Why it matters
Offers a theoretically rigorous and experimentally validated safety layer for collaborative robots that directly mitigates human injury risk while remaining simple to implement alongside existing controllers.
Abstract
In the context of safety-critical control, we propose and analyse the use of Control Barrier Functions (CBFs) to limit the kinetic energy of torque-controlled robots. The proposed scheme is able to modify a nominal control action in a minimally invasive manner to achieve the desired kinetic energy limit. We show how this safety condition is achieved by appropriately injecting damping in the underlying robot dynamics independently of the nominal controller structure. We present an extensive experimental validation of the approach on a 7-Degree of Freedom (DoF) Franka Emika Panda robot. The results demonstrate that this approach provides an effective, minimally invasive safety layer that is straightforward to implement and is robust in real experiments.