针对复杂U型障碍物环境中跳点搜索算法(jump point search,JPS)路径长、拐点多和人工势场法(artificial potential field,APF)陷入U型陷阱引起的路径曲折、寻路效率低等问题,提出融合改进JPS算法和APF算法(JPS^(*)-APF)的移动机器人路...针对复杂U型障碍物环境中跳点搜索算法(jump point search,JPS)路径长、拐点多和人工势场法(artificial potential field,APF)陷入U型陷阱引起的路径曲折、寻路效率低等问题,提出融合改进JPS算法和APF算法(JPS^(*)-APF)的移动机器人路径规划算法。首先,在传统JPS算法中增加角度偏差函数并删除冗余节点,减小搜索距离和转折次数;其次,改进JPS算法的拐点作为子目标点,分段引导APF算法逃出U型陷阱,自适应生成拐角障碍物斥力或动态子目标点提高路径平滑度;然后,在目标点区域添加对称虚拟障碍物解决目标不可达、融合外部斥力和重规划策略逃出局部最优,提高寻路效率;最后,适时加入相对速度斥力保证动态避障的安全性。针对不同U/L型障碍物环境进行数值仿真,结果表明,JPS^(*)-APF算法较IA^(*)-APF算法平均减少了51.5%的寻路时间和7.3%的路径长度,而且JPS^(*)-APF算法路径更平滑,能有效逃出U型陷阱并提升移动机器人的工作效率;同时通过真实环境实验测试验证了JPS^(*)-APF算法规划的可行性。展开更多
Sparse arrays of telescopes have a limited (u, v)-plane coverage. In this paper, an optimization method for designing planar arrays of an aperture synthesis telescope is proposed that is based on distributed genetic a...Sparse arrays of telescopes have a limited (u, v)-plane coverage. In this paper, an optimization method for designing planar arrays of an aperture synthesis telescope is proposed that is based on distributed genetic algorithm. This distributed genetic algorithm is implemented on a network of workstations using community communication model. Such an aperture synthesis system performs with imperfection of (u, v) components caused by deviations and(or) some missing baselines. With the maximum (u, v)-plane coverage of this rotation-optimized array, the image of the source reconstructed by inverse Fourier transform is satisfactory.展开更多
文摘针对复杂U型障碍物环境中跳点搜索算法(jump point search,JPS)路径长、拐点多和人工势场法(artificial potential field,APF)陷入U型陷阱引起的路径曲折、寻路效率低等问题,提出融合改进JPS算法和APF算法(JPS^(*)-APF)的移动机器人路径规划算法。首先,在传统JPS算法中增加角度偏差函数并删除冗余节点,减小搜索距离和转折次数;其次,改进JPS算法的拐点作为子目标点,分段引导APF算法逃出U型陷阱,自适应生成拐角障碍物斥力或动态子目标点提高路径平滑度;然后,在目标点区域添加对称虚拟障碍物解决目标不可达、融合外部斥力和重规划策略逃出局部最优,提高寻路效率;最后,适时加入相对速度斥力保证动态避障的安全性。针对不同U/L型障碍物环境进行数值仿真,结果表明,JPS^(*)-APF算法较IA^(*)-APF算法平均减少了51.5%的寻路时间和7.3%的路径长度,而且JPS^(*)-APF算法路径更平滑,能有效逃出U型陷阱并提升移动机器人的工作效率;同时通过真实环境实验测试验证了JPS^(*)-APF算法规划的可行性。
基金This project was supported by the High Technology Research and Development Programme of China (2002AA111040).
文摘Sparse arrays of telescopes have a limited (u, v)-plane coverage. In this paper, an optimization method for designing planar arrays of an aperture synthesis telescope is proposed that is based on distributed genetic algorithm. This distributed genetic algorithm is implemented on a network of workstations using community communication model. Such an aperture synthesis system performs with imperfection of (u, v) components caused by deviations and(or) some missing baselines. With the maximum (u, v)-plane coverage of this rotation-optimized array, the image of the source reconstructed by inverse Fourier transform is satisfactory.
