Achieving Safe Control Online through Integration of Harmonic Control Lyapunov-Barrier Functions with Unsafe Object-Centric Action Policies

TL;DR

This paper introduces a method to ensure robot safety by integrating Harmonic Control Lyapunov-Barrier Functions with existing policies, providing formal safety guarantees while maintaining task performance.

Contribution

It presents a novel approach to combine HCLBFs derived from STL specifications with robot policies, enabling safe control with formal guarantees.

Findings

Successfully avoided collisions in a reinforcement learning-based robot arm task.

Demonstrated the method's potential for generalization to complex specifications.

Provided a proof-of-concept implementation with safety guarantees.

Abstract

We propose a method for combining Harmonic Control Lyapunov-Barrier Functions (HCLBFs) derived from Signal Temporal Logic (STL) specifications with any given robot policy to turn an unsafe policy into a safe one with formal guarantees. The two components are combined via HCLBF-derived safety certificates, thus producing commands that preserve both safety and task-driven behavior. We demonstrate with a simple proof-of-concept implementation for an object-centric force-based policy trained through reinforcement learning for a movement task of a stationary robot arm that is able to avoid colliding with obstacles on a table top after combining the policy with the safety constraints. The proposed method can be generalized to more complex specifications and dynamic task settings.