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

arXiv: https://arxiv.org/abs/2008.09427 · HTML: https://mlsanity.com/paper/2008.09427/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Aug 2020.

## Built on by (most cited first, 3 of 3)

- [Behavior Trees in Robot Control Systems](https://mlsanity.com/paper/2203.13083/) (2022)
- [Online Control Barrier Functions for Decentralized Multi-Agent Navigation](https://mlsanity.com/paper/2303.04313/) (2023)
- [Behavior Tree-Based Task Planning for Multiple Mobile Robots using a Data Distribution Service](https://mlsanity.com/paper/2201.10918/) (2022)

## Abstract (arXiv)

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.