A Comprehensive Review of Shepherding as a Bio-inspired Swarm-Robotics Guidance Approach

TL;DR

This paper reviews bio-inspired swarm shepherding techniques, highlighting their potential for controlling multiple robotic agents through simple interactions inspired by nature, especially sheep herding behaviors.

Contribution

It provides a comprehensive survey of existing research on swarm shepherding, emphasizing its advantages and future applications in robotics.

Findings

Swarm shepherding effectively guides multiple agents using simple rules.

Bio-inspired techniques show promise for complex robotic control tasks.

The review identifies key challenges and future directions in the field.

Abstract

The simultaneous control of multiple coordinated robotic agents represents an elaborate problem. If solved, however, the interaction between the agents can lead to solutions to sophisticated problems. The concept of swarming, inspired by nature, can be described as the emergence of complex system-level behaviors from the interactions of relatively elementary agents. Due to the effectiveness of solutions found in nature, bio-inspired swarming-based control techniques are receiving a lot of attention in robotics. One method, known as swarm shepherding, is founded on the sheep herding behavior exhibited by sheepdogs, where a swarm of relatively simple agents are governed by a shepherd (or shepherds) which is responsible for high-level guidance and planning. Many studies have been conducted on shepherding as a control technique, ranging from the replication of sheep herding via simulation, to the control of uninhabited vehicles and robots for a variety of applications. We present a comprehensive review of the literature on swarm shepherding to reveal the advantages and potential of the approach to be applied to a plethora of robotic systems in the future.