Path planning of UAV in dynamic environment
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摘要: 为了解决动态环境中的路径规划问题,提出了一种引入时间轴的方法.在构型空间的基础上引入时间轴,将构型空间扩展为构型-时间空间,在构型-时间空间中可以表示动态障碍物所有时刻的位置.在路径生成阶段,提出了一种改进的蚁群算法,将方向信息作为启发信息引入蚁群算法中,使蚂蚁在初始搜索路径时更有针对性.仿真结果表明:构型-时间空间可以解决动态环境的表示问题,改进蚁群算法可以更快地收敛到全局最优解.Abstract: In order to solve the problem of path planning in dynamic environment, a new method which introduced the time axis was given. Based on the configuration space (C space), the time axis was introduced to expand the C space to the configuration-time space (CT space), and the position of moving obstacles at all times could be expressed in the CT space. In the path generation stage, an improved ant colony algorithm was proposed. The heading information was introduced as heuristic information to the ant colony algorithm, and at the beginning of the algorithm ants could be guided to search the road map more efficiently. The simulation results show that the moving obstacles can be expressed well in the CT space. The improved ant colony algorithm is more efficient and it can converge to the best solution more quickly.
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Key words:
- path planning /
- unmanned aerial vehicle /
- dynamic environment /
- ant colony algorithm
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