2014Unpublished venueRequires access

Improved PRM method of low altitude penetration trajectory planning for UAVs

Qianru Li, Wei Chen, Jiang Wu, Xiaofang Zhu

Open publisher page 10 citations

Abstract

In this paper, an improved probabilistic roadmap (PRM) method of low altitude penetration trajectory planning for UAVs is proposed. This approach generates a reference trajectory by constructing a roadmap firstly and searching it secondly before the take-off of UAV. During the roadmap construction process, the traditional randomized sampling method is improved by new kinds of sampling methods, in which information of terrain and threats is fully used so that the roadmap can avoid terrain and threats as well as follow the terrain automatically. During the search process, A* algorithm is used to search for a trajectory and UAVs dynamic constraints are considered in the search process to guarantee that the trajectory is feasible. The simulation results demonstrated that the improved method can achieve a desirable trajectory in the low altitude penetration tasks.

About this research paper

What this paper is about

In this paper, an improved probabilistic roadmap (PRM) method of low altitude penetration trajectory planning for UAVs is proposed. This approach generates a reference trajectory by constructing a roadmap firstly and searching it secondly before the take-off of UAV. During the roadmap construction process, the traditional randomized sampling method is improved by new kinds of sampling methods, in which information of terrain and threats is fully used so that the roadmap can avoid terrain and threats as well as follow the terrain automatically. During the search process, A* algorithm is used to search for a trajectory and UAVs dynamic constraints are considered in the search process to guarantee that the trajectory is feasible. The simulation results demonstrated that the improved method can achieve a desirable trajectory in the low altitude penetration tasks.

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Available abstract

In this paper, an improved probabilistic roadmap (PRM) method of low altitude penetration trajectory planning for UAVs is proposed. This approach generates a reference trajectory by constructing a roadmap firstly and searching it secondly before the take-off of UAV. During the roadmap construction process, the traditional randomized sampling method is improved by new kinds of sampling methods, in which information of terrain and threats is fully used so that the roadmap can avoid terrain and threats as well as follow the terrain automatically. During the search process, A* algorithm is used to search for a trajectory and UAVs dynamic constraints are considered in the search process to guarantee that the trajectory is feasible. The simulation results demonstrated that the improved method can achieve a desirable trajectory in the low altitude penetration tasks.

Key concepts: Trajectory, Terrain, Computer science, Probabilistic logic, Process (computing), Low altitude, Probabilistic roadmap, Sampling (signal processing)

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