Route Design in Sheepdog System--Traveling Salesman Problem Formulation and Evolutionary Computation Solution--

TL;DR

This paper introduces a novel guidance algorithm for sheepdog systems that formulates the route planning as a Traveling Salesman Problem and applies evolutionary computation, effectively reducing guidance failure and distance.

Contribution

It presents a new route design approach for sheepdog guidance using TSP and evolutionary algorithms, addressing guidance distance and failure rate issues.

Findings

Reduces guidance failure rate

Lowers guidance distance

Effective in numerical simulations

Abstract

In this study, we consider the guidance control problem of the sheepdog system, which involves the guidance of the flock using the characteristics of the sheepdog and sheep. Sheepdog systems require a strategy to guide sheep agents to a target value using a small number of sheepdog agents, and various methods have been proposed. Previous studies have proposed a guidance control law to guide a herd of sheep reliably, but the movement distance of a sheepdog required for guidance has not been considered. Therefore, in this study, we propose a novel guidance algorithm in which a supposedly efficient route for guiding a flock of sheep is designed via Traveling Salesman Problem and evolutionary computation. Numerical simulations were performed to confirm whether sheep flocks could be guided and controlled using the obtained guidance routes. We specifically revealed that the proposed method reduces both the guidance failure rate and the guidance distance.