Effective Mobile Target Searching Using Robots

Abstract

With robotics technologies advancing rapidly, there are many new robotics applications such as surveillance, mining tasks, search and rescue, and autonomous armies. In this work, we focus on the use of robots for target searching. For example, a collection of Unmanned Aerial Vehicle (UAV) could be sent to search for survivor targets in disaster rescue missions, with no prior knowledge of locations and movement behaviors of the survivor targets. Our objective is to compute a search plan that maximizes the probability of finding the targets and minimizes the searching latency. These are critical in search and rescue applications. Our idea is to partition the search area into grid cells and apply the divide-and-conquer approach. We propose two searching strategies, namely, the circuit strategy and the rebound strategy. The robots search the cells in a Hamiltonian circuit in the circuit strategy while they backtrack in the rebound strategy. We prove that the expected searching latency of the circuit strategy for a moving target is upper bounded by $\frac {3n^{2}-4n+3}{2n}$ where n is the number of grid cells of the search region. To handle robot failure, each robot regularly communicates with neighboring robots and takes over the task of a failed neighbor robot. Simulations are conducted and the results show that the circuit strategy with our failure handling mechanism achieves the best search effectiveness.