Multi-UAV Distributed Collaborative Coverage for Target Search Using Heuristic Strategy

Abstract

Collaborative coverage for target search using a group of unmanned aerial vehicles (UAVs) has received increasing attention in recent years. However, the design of distributed control strategy and coordination mechanisms remains a challenge. This paper presents a distributed and online heuristic strategy to solve the problem of multi-UAV collaborative coverage. As a basis, each UAV maintains a probability grid map in the form of a locally stored matrix, without shared memory. Then we design two evaluation functions and related technical strategies to enable UAVs to make state transfer or area transfer decisions in an online self-organizing way. The simulation results show that the algorithm integrates geometric features such as parallel search and internal spiral search, and is not interfered by factors such as sudden failure of UAVs, changes in detection range, and target movement. Compared with other commonly used methods for target search, our strategy has high search efficiency, good robustness, and fault tolerance.