基于优化快速搜索随机树算法的全局路径规划The Global Path Planning Algorithm Based on Optimization RRT Algorithm
杨炜,谭亮,孙雪,杜亚峰,周晓冰
摘要(Abstract)：
为了改善传统快速搜索随机树（RRT）算法在全局路径规划中存在的平滑度差、具有潜在碰撞性等问题，提出了一种双重优化的RRT算法。在传统RRT算法基础上，引入自适应目标偏向策略以缩短采样时间，引入角度约束采样策略以适应车辆极限转角。得到初始路径后，建立二项优化函数（即降低路径曲率和远离障碍物），并将其作为基点进行梯度下降二次优化，生成可供车辆行驶、平滑性良好且碰撞概率低的路径，并进行仿真验证。结果表明：优化RRT算法相比于传统RRT算法、RRT-Connect算法和RRT*算法，平均曲率分别降低了38.1%、36.4%和24.7%，曲率均方差分别降低了38.4%、38.4%和27.2%。
关键词(KeyWords)：
基金项目(Foundation): 国家重点研发计划项目（2021YFE0203600）;; 陕西省自然科学基金青年项目（2017JQ6045）
作者(Author): 杨炜,谭亮,孙雪,杜亚峰,周晓冰
DOI: 10.19620/j.cnki.1000-3703.20230346
参考文献(References)：
- [1]朱冰,韩嘉懿,赵健,等.基于安全场改进RRT~*算法的智能汽车路径规划方法[J].汽车工程, 2020, 42(9):1145-1150+1182.ZHU B, HAN J Y, ZHAO J, et al. Intelligent Vehicle Path Planning Method Based on Improved RRT~*Algorithm Based on Safety Field[J]. Automotive Engineering, 2020, 42(9):1145-1150+1182.
- [2]叶颖诗,魏福义,蔡贤资.基于并行计算的快速Dijkstra算法研究[J].计算机工程与应用, 2020, 56(6):58-65.YE Y S, WEI F Y, CAI X Z. Research on Fast Dijkstra’s Algorithm Based on Parallel Computing[J]. Computer Engineering and Applications, 2020, 56(6):58-65.
- [3] HONG Z H, SUN P F, TONG X H, et al. Improved A-Star Algorithm for Long-Distance Off-Road Path Planning Using Terrain Data Map[J]. ISPRS International Journal of Geo-Information, 2021, 10(11).
- [4] SANGEETHA V, RAVICHANDRAN K S, SHEKHAR S, et al. An Intelligent Gain-Based Ant Colony Optimisation Method for Path Planning of Unmanned Ground Vehicles[J].Defence Science Journal, 2019, 69(2):167-172.
- [5]李根,李航,张帅阳,等.基于蚁群算法的最优路径规划及参数研究[J].中国科技论文, 2018, 13(16):1909-1914.LI G, LI H, ZHANG S Y, et al. Research on Optimal Path Planning and Parameters Based on ant Colony Algorithm[J].China Science and Technology Papers, 2018, 13(16):1909-1914.
- [6] LAVALLE S M. Rapidly-Exploring Random Trees:A New Tool for Path Planning[J]. Algorithmic and Computational Robotics New Directions, 1998:293-308.
- [7] TAHERI E, FERDOWSI M H, DANESH M. Fuzzy Greedy RRT Path Planning Algorithm in a Complex Configuration Space[J]. International Journal of Control Automation and Systems, 2018, 16(6):3026-3035.
- [8]张卫波,肖继亮.改进RRT算法在复杂环境下智能车路径规划中的应用[J].中国公路学报, 2021, 34(3):225-234.ZHANG W B, XIAO J L. Application of Improved RRT Algorithm in Intelligent Vehicle Path Planning Complex Environment[J]. Chinese Journal of Highways, 2021, 34(3):225-234.
- [9] ZAID T, QURESHI A H, YASAR A, et al. Potentially Guided Bidirectionalized RRT*for Fast Optimal Path Planning in Cluttered Environments[J]. Robotics and Autonomous Systems, 2018, 108:13-27.
- [10] SKA?KAUSKAS P, SOKOLOVSKIJ E. Analysis of the Hybrid Global Path Planning Algorithm for Different Environments[J]. Transport and Telecommunication, 2019,20(1):1-11.
- [11]臧强,张国林,靳雨桐,等.一种基于动态步长的AAPFRRT*移动机器人路径规划新算法[J].中国科技论文,2021, 16(11):1227-1233+1270.ZANG Q, ZHANG G L, JIN Y T, et, al. A New AAPFRRT*Mobile Robot Path Planning Algorithm Based on Dynamic Step Size[J]. China Science and Technology Paper, 2021, 16(11):1227-1233+1270.
- [12]胡小平,曹敬.一种多机器人的改进势场路径规划算法[J].机械科学与技术, 2018, 37(8):1207-1216.HU X P, CAO J. An Improved Potential Field Path Planning Algorithm for Multiple Robots[J]. Mechanical Science and Technology, 2018, 37(8):1207-1216.
- [13] MOHAMMED H, JARADAT M A, ROMDHANE L B.RRT*N:An Improved Rapidly-Exploring Random Tree Approach for Reduced Processing Times[C]//2018 11th International Symposium on Mechatronics and Its Applications(ISMA). Sharjah, United Arab Emirates:IEEE, 2018.
- [14]陈特,陈龙,徐兴,等.基于Hamilton理论的无人车路径跟踪控制[J].北京理工大学学报, 2019, 39(7):676-682.CHEN T, CHEN L, XU X, et al. Unmanned Vehicle Path Tracking Control Based on Hamilton Theory[J].Transactions of Beijing Institute of Technology, 2019, 39(7):676-682.