UAV Path Planning in Search Operations
Farzad Kamrani, Rassul Ayani · InTech eBooks · 2009
In this chapter, we investigated the problem of autonomous UAV path planning in search or surveillance mission, when some a priori information about the target and the environment is available. A search operation that utilizes the available uncertain information about the initial location of the target, terrain data, and reasonable assumptions about the target movement can in average perform better than a uniform search that does not incorporate this information. We introduced a simulation-based framework for utilizing uncertain information in path planning. Search operations are generally dynamic and should be modified during the mission due to sensor observations, changes in the environment, and reports from other sources, hence an on-line simulation method was suggested. This method fuses continuously all available information using Sequential Monte Carlo methods to yield an updated picture of the probability density of the target's location. This estimation is used periodically to run a set of what-if simulations to determine which UAV path is most promising. From a set of different UAV paths the one that decreases the uncertainty about the location of the target is preferable. Hence, the expectation of information entropy is used as a measure for comparing different courses of action of the UAV. The suggested framework was applied to a test case scenario involving a single UAV searching for a single target moving on a known road network. The performance of the method was tested by simulation, which indicated that the on-line path planning has generally a high performance. The result obtained by the on-line simulation method was compared with an exhaustive search, where the UAV searched the entire road network indiscriminately. The on-line simulation method showed significantly higher performance and detected the target in a considerably shorter time. Furthermore, the performance of the method was compared with the detection time when the UAV had the exact information about the initial location of the target, its velocity, and its path (minimum detection time). Comparison with this value indicated that the on-line simulation method in many cases achieved a "near" optimal performance in the studied scenario.