| 自适应双向快速密集树避碰运动规划算法 |
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| 引用本文： | 李华忠,但唐仁,唐强平.自适应双向快速密集树避碰运动规划算法[J].深圳信息职业技术学院学报,2014(3):24-30. |
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| 作者姓名： | 李华忠 但唐仁 唐强平 |
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| 作者单位： | 深圳信息职业技术学院软件工程系,广东深圳,518172 |
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| 基金项目： | 广东省自然基金，深圳基础研究基金，广东省高职教育信息技术类课题，院科技创新团队项目，校级科研培育项目 |
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| 摘 要： | 针对采样运动规划算法效率低，尤其在处理高维空间和复杂障碍环境等问题时，严重依赖于所选采样参数和碰撞检测距离等，提出了一种自适应双向快速密集树（ABiRDT）避碰运动规划方法。首先，深入研究了ABiRDT算法的基础理论和实现方法，可适应调整碰撞检测距离参数和随机采样扩展步长；其次，重点研究了本算法所采用的c-空间加权均匀采样、最近邻位形查找和基于混合包围盒的并行离散碰撞检测等关键自适应策略；最后，通过三维可视化计算机仿真验证了本文提出算法的有效性。
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| 关 键 词： | 运动规划 快速密集树 自适应算法 基于采样技术 离散碰撞检测 位形空间 |
Research on adaptive bi-directional rapidly exploring dense tree collision avoidance motion planning algorithm |
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| LI Huazhong,DAN Tangren,TANG QiangPing.Research on adaptive bi-directional rapidly exploring dense tree collision avoidance motion planning algorithm[J].Journal of Shenzhen Institute of Information Technology,2014(3):24-30. |
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| Authors: | LI Huazhong DAN Tangren TANG QiangPing |
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| Institution: | (Department of Software Engineering, Shenzhen Institute of Information Technology, Shenzhen 518172, P.R. China) |
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| Abstract: | Due to algorithm efficiency of sampling-based motion planning is low, especially when dealing with high- dimensional space and complex environmental obstacles, it is heavily dependent on the selected sampling parameters and collision detection distance, adaptive bidirectional balance rapidly exploring dense tree（ABiRDT） motion planning method has been proposed. First, basic theol7 and implementation method of the ABiRDT algorithm have been researched deeply, its including adaptive strategies include how to automatically adjust the collision detection distance parameter, random sampling expansion step; Secondly, key adaptive key adaptive strategies strategy used in the ABiRDT about C-space weighted uniform sampling, nearest neighbor configuration searching and hybrid bounding box based parallel discrete collision detection have been investigated strongly; Finally, effectiveness of the proposed algorithms have been verified by three-dimensional visualization computer simulation. |
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| Keywords: | motion planning rapidly exploring dense tree adaptive algorithm sampling-based techniques discrete collision detection configuration space |
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