Safe Legged Locomotion using Collision Cone Control Barrier Functions (C3BFs)

TL;DR

This paper presents a novel collision avoidance method for legged robots using Collision Cone Control Barrier Functions (C3BFs), formulated as a Quadratic Program (C3BF-QP), validated through simulations in PyBullet.

Contribution

The paper introduces C3BF-QP, a new safety filter for legged robots that enhances collision avoidance in complex environments, combining control barrier functions with quadratic programming.

Findings

C3BF-QP effectively prevents collisions in simulated environments.

The approach integrates seamlessly with existing controllers.

Simulations demonstrate improved safety in dynamic obstacle scenarios.

Abstract

Legged robots exhibit significant potential across diverse applications, including but not limited to hazardous environment search and rescue missions and the exploration of unexplored regions both on Earth and in outer space. However, the successful navigation of these robots in dynamic environments heavily hinges on the implementation of efficient collision avoidance techniques. In this research paper, we employ Collision Cone Control Barrier Functions (C3BF) to ensure the secure movement of legged robots within environments featuring a wide array of static and dynamic obstacles. We introduce the Quadratic Program (QP) formulation of C3BF, referred to as C3BF-QP, which serves as a protective filter layer atop a reference controller to ensure the robots' safety during operation. The effectiveness of this approach is illustrated through simulations conducted on PyBullet.