Balancing Priorities in Patrolling with Rabbit Walks

TL;DR

This paper introduces a distributed online algorithm for patrolling environments with prioritized locations, balancing frequent visits to high-priority sites and ensuring coverage of non-priority sites through scalable offline routes called Rabbit Walks.

Contribution

The paper proposes a novel scalable algorithm that generates offline patrol routes with three segments, balancing priorities and non-priorities in patrolling tasks.

Findings

Algorithm ensures balanced visits to priority and non-priority locations.

Performance validated through simulations and experiments.

Scalable implementation based on onboard resources.

Abstract

In an environment with certain locations of higher priority, it is required to patrol these locations as frequently as possible due to their importance. However, the Non-Priority locations are often neglected during the task. It is necessary to balance the patrols on both kinds of sites to avoid breaches in security. We present a distributed online algorithm that assigns the routes to agents that ensures a finite time visit to the Non-Priority locations along with Priority Patrolling. The proposed algorithm generates offline patrol routes (Rabbit Walks) with three segments (Hops) to explore non-priority locations. The generated number of offline walks depends exponentially on a parameter introduced in the proposed algorithm, thereby facilitating the scalable implementation based on the onboard resources available on each patrolling robot. A systematic performance evaluation through simulations and experimental results validates the proportionately balanced visits and suggests the proposed algorithm's versatile applicability in the implementation of deterministic and non-deterministic scenarios.