Abstract

This paper proposes a fast cooperative path planning algorithm for multiple UAVs that satisfies the time–space cooperative constraints, namely, the RRT* algorithm based on heuristic decentralized prioritized planning (HDP-TSRRT*), which takes into account the simultaneous arrival time variables of each UAV as well as the avoidance of conflicts and threats. HDP-TSRRT* is a hierarchical decoupling algorithm. First, all UAV pre-paths are planned simultaneously at the synchronous decentralized planning level. Second, at the coordination path level, the heuristic decentralized prioritized planning algorithm (HDP) is proposed to quickly complete the coordination process of the path planning sequence. This strategy assigns reasonable and robust priority to all UAVs based on the performance evaluation function composed of the number of potential collisions and the violation of collaboration time of the pre-planned path. Third, the time–space cooperative constraints-based RRT* algorithm (TSRRT*) is proposed at the single-machine cooperative path planning level. Based on this, the algorithm uses multiple sampling and cost evaluation strategies to guide the expansion of new nodes, and then optimizes neighborhood nodes based on the time coordination cost function so as to improve the efficiency of coordination path planning. Simulation and comparison show that HDP-TSRRT* has certain advantages in algorithm performance.

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