Adaptive Fault Tolerant Execution of Multi-Robot Missions using Behavior Trees

TL;DR

This paper presents a method to extend single robot Behavior Trees to multi-robot systems, enhancing fault tolerance and performance through parallel execution and fault handling, demonstrated with concrete examples and analysis.

Contribution

It introduces a novel extension of Behavior Trees for multi-robot fault-tolerant mission execution, combining fallback strategies with parallel task execution.

Findings

Fault tolerance improves with multi-robot BT extension

Parallel execution enhances mission performance

Minor and major faults impact performance differently

Abstract

Multi-robot teams offer possibilities of improved performance and fault tolerance, compared to single robot solutions. In this paper, we show how to realize those possibilities when starting from a single robot system controlled by a Behavior Tree (BT). By extending the single robot BT to a multi-robot BT, we are able to combine the fault tolerant properties of the BT, in terms of built-in fallbacks, with the fault tolerance inherent in multi-robot approaches, in terms of a faulty robot being replaced by another one. Furthermore, we improve performance by identifying and taking advantage of the opportunities of parallel task execution, that are present in the single robot BT. Analyzing the proposed approach, we present results regarding how mission performance is affected by minor faults (a robot losing one capability) as well as major faults (a robot losing all its capabilities). Finally, a detailed example is provided to illustrate the approach.