Distributed and Cooperative Exploration for Multiple Targets Using Probabilistic Roadmaps

In this study, we propose a distributed search method for multiple targets in In this study, we propose a distributed search method for multiple targets in a two-dimensional space using HEDAC(Heat Equation Driven Area Coverage). HEDAC has been recently used to control multi-agent systems. In contrast to the conventional centralized HEDAC, this paper proposes a decentralized algorithm that uses probability maps to make it more practical. Specifically, each search agent shares the probability of target detection by its own search as a probability map with other agents, and is controlled along the gradient of the potential field created based on this map, enabling it to conduct its search activities in a distributed and efficient way. The contribution of this paper is to improve the flexibility of conventional search methods by decentralizing them. Finally, we confirm the effectiveness of the proposed method through simulation validation.