基于膜计算的煤矿井下机器人路径规划算法

黄友锐; 李静; 韩涛; 徐善永

doi:10.13272/j.issn.1671-251x.17847

基于膜计算的煤矿井下机器人路径规划算法

doi: 10.13272/j.issn.1671-251x.17847

安徽理工大学电气与信息工程学院, 安徽淮南 232001

基金项目:

国家自然科学基金资助项目（61772033）。

详细信息

作者简介:
黄友锐(1971-),男,安徽长丰人,教授,博士,主要研究方向为智能优化算法等,E-mail:hyr628@163.com。

中图分类号: TD774
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- 文章访问数: 111
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- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2021-09-08
- 修回日期: 2021-11-05
- 刊出日期: 2021-11-20

Research on path planning algorithm of robot in coal mine based on membrane computing

School of Electrical and Information Engineering, Anhui University of Science and Technology, Huainan 232001, China

摘要

摘要: 现有煤矿井下机器人路径规划算法采用固定步长和串行方式生成路径，存在成功率低、实时性差、效率低下等问题。将膜计算(MC)与Informed RRT^*算法相结合，提出了一种煤矿井下机器人路径规划算法，即MC-IRRT^*算法。该算法分为快速连通和路径寻优2个阶段。在快速连通阶段，构建多步长细胞型膜结构，根据空间区域的大小来调整步长：在可行空间较大的区域采用大步长搜索，加快搜索速度；在狭小的空间使用小步长搜索，使搜索空间更加精细，提高狭小空间路径搜索成功率。在路径寻优阶段，构建多采样点细胞型膜结构，通过多个基本膜并行计算，同时在多个椭圆区域内并行搜索最短可行路径，以节省时间，提高路径优化效率。简单场景实验结果表明，与Informed RRT^*算法相比，MC-IRRT^*算法在快速连通阶段和路径寻优阶段的搜索效率分别提高了76%，40%。复杂场景实验结果表明：RRT^*算法和Informed RRT^*算法路径规划失败，PQ-RRT^*算法和MC-IRRT^*算法均能成功寻得可行路径；与PQ-RRT^*算法相比，MC-IRRT^*算法的速率提高了12.79%，规划的路径长度缩短了8.18%；MC-IRRT^*算法不仅可以迅速通过较窄可行区域，而且在路径转折处可以选择使用较小步长，使路径更加平滑。
- 煤矿机器人 /
- 路径规划 /
- 膜计算 /
- Informed RRT^*算法 /
- MC-IRRT^*算法 /
- 多步长搜索 /
- 并行搜索
Abstract: The existing path planning algorithm of robot in coal mine uses fixed step size and serial mode to generate path, which has problems such as low success rate, poor real-time performance and low efficiency.Combining membrane computing(MC)with Informed RRT^* algorithm, this study proposes a path planning algorithm of robot in coal mine, namely MC-IRRT^* algorithm.The algorithm is divided into two stages, namely fast connectivity and path optimization.In the fast connectivity stage, the multi-step cellular membrane structure is constructed, and the step size is adjusted according to the size of the space area.The large step search is used in the area with larger feasible space to accelerate the search speed.The small step search is used in the narrow space to make the search space more refined and improve the success rate of the narrow space path search.In the path optimization stage, a multi-sampling cellular membrane structure is constructed, and multiple basic membranes are calculated in parallel, and the shortest feasible path is searched in parallel in multiple elliptical areas at the same time to save time and improve the efficiency of path optimization.The simple scene experimental results show that compared with Informed RRT^* algorithm, the search efficiency of MC-IRRT^* algorithm in the fast connectivity stage and the path optimization phase is increased by 76% and 40% respectively.The complex scene experimental results show that the path planning of RRT^* algorithm and Informed RRT^* algorithm fails, and both PQ-RRT^* algorithm and MC-IRRT^* algorithm can find feasible paths successfully.Compared with PQ-RRT^* algorithm, the rate of MC-IRRT^* algorithm is increased by 12.79%, and the planned path length is shortened by 8.18%.The MC-IRRT^* algorithm can not only pass through narrow feasible areas quickly, but also can choose to use smaller step at the turning point of the path so as to make the path smoother.
- coal mine robot /
- path planning /
- membrane computing /
- Informed RRT^* algorithm /
- MC-IRRT^* algorithm /
- multi-step search /
- parallel search

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参考文献(17)

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