Article ID Journal Published Year Pages File Type
8953581 Neurocomputing 2018 18 Pages PDF
Abstract
Path planning is a significant issue for the safe flight of unmanned aerial vehicles (UAVs). In the situation of multiple UAVs, the problem is even more challenging due to the tough manipulation of coordination and constrains. In this paper, a novel multi-UAV path planning model is developed which is based on the time stamp segmentation (TSS) technique. Other than the traditional methods, the TSS model utilizes the common time bases to simplify the handling of multi-UAV coordination cost. Then, a novel social-class pigeon-inspired optimization (SCPIO) algorithm is proposed as the solver of optimal search on the TSS model. The social-class strategy is utilized to enhance the convergence capabilities of the standard PIO. The efficiency of the proposed method is verified through the comparative experiments and the performance profiles (PP). Integrated experiment in a 3D environment demonstrates the reliability of the proposed system.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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