Priority Patrolling Algorithm for Multi-Robot Systems

Overview

The Priority Patrolling Algorithm (PPA) addresses the challenge of efficient area coverage by multiple robots with heterogeneous priorities. The system dynamically allocates robots to patrol zones based on changing priority levels, ensuring critical areas receive more frequent visits while maintaining overall coverage guarantees.

Key Features

• Adaptive patrolling strategies based on dynamic priority maps
• Theoretical guarantees on worst-case idleness times
• Decentralized decision-making for scalable deployment
• Handles robot failures and dynamic priority changes
• Energy-aware path planning for extended operation

Technical Approach

PPA uses a graph-based representation of the environment where nodes represent patrol points and edges represent traversable paths. The algorithm maintains a priority queue of patrol points based on their importance and time since last visit. Robots use a distributed auction-based mechanism to claim patrol targets, with bids computed based on travel distance and expected idleness reduction. The approach provides theoretical bounds on the maximum time any high-priority location remains unvisited.

Applications

This work enables efficient multi-robot patrolling in various scenarios:

• Security surveillance with threat-level-based priorities
• Environmental monitoring with adaptive sampling rates
• Infrastructure inspection prioritizing critical components
• Agricultural monitoring focusing on high-value crops

Results

Experimental validation demonstrates significant improvements over baseline approaches:

• 50% reduction in maximum idleness for high-priority locations
• 30% improvement in overall coverage efficiency
• Scales effectively to teams of 20+ robots
• Robust to individual robot failures without global replanning