Combining Control Barrier Functions and Behavior Trees for Multi-Agent Underwater Coverage Missions

TL;DR

This paper presents a method combining Control Barrier Functions and Behavior Trees to manage multiple concurrent and sequential objectives in multi-agent underwater coverage missions, ensuring mission success with performance guarantees.

Contribution

It introduces a novel principled approach to integrate CBFs and BTs for complex multi-objective robot missions, demonstrated through simulation.

Findings

Successful simulation of underwater coverage mission

Effective handling of concurrent and sequential objectives

Performance guarantees in mission completion

Abstract

Robot missions typically involve a number of desired objectives, such as avoiding collisions, staying connected to other robots, gathering information using sensors and returning to the charging station before the battery runs out. Some of these objectives need to be taken into account at the same time, such as avoiding collisions and staying connected, while others are focused upon during different parts of the executions, such as returning to the charging station and connectivity maintenance. In this paper, we show how Control Barrier Functions(CBFs) and Behavior Trees(BTs) can be combined in a principled manner to achieve both types of task compositions, with performance guarantees in terms of mission completion. We illustrate our method with a simulated underwater coverage mission.