Collaborative Safety-Critical Formation Control with Obstacle Avoidance

TL;DR

This paper develops a collaborative safety framework using control barrier functions for multi-agent formation control with obstacle avoidance, ensuring safety and convergence in complex environments.

Contribution

It introduces a novel safety filter control law for distributed formation control that handles multiple static and dynamic obstacles with proven convergence properties.

Findings

Proposed a control barrier function-based safety filter for multi-agent systems.

Proved linear-time convergence to safe actions in tree-structured networks with one obstacle.

Demonstrated finite-time convergence in simulations with multiple static and dynamic obstacles.

Abstract

This work explores a collaborative method for ensuring safety in multi-agent formation control problems. We formulate a control barrier function (CBF) based safety filter control law for a generic distributed formation controller and extend our previously developed collaborative safety framework to an obstacle avoidance problem for agents with acceleration control inputs. We then incorporate multi-obstacle collision avoidance into the collaborative safety framework. This framework includes a method for computing the maximum capability of agents to satisfy their individual safety requirements. We analyze the convergence rate of our collaborative safety algorithm, and prove the linear-time convergence of cooperating agents to a jointly feasible safe action for all agents under the special case of a tree-structured communication network with a single obstacle for each agent. We illustrate the analytical results via simulation on a mass-spring kinematics-based formation controller and demonstrate the finite-time convergence of the collaborative safety algorithm in the simple proven case, the more general case of a fully-connected system with multiple static obstacles, and with dynamic obstacles.