摘要
半挂车辆的非稳定运动学特性为其泊车过程中自主运动规划带来严峻挑战。针对半挂车在多障碍物的静态场景中泊车运动规划算法效率低、结果平滑性差等问题,本文提出了序列式运动规划方法(sequential motion planning algorithm,SMPA)。首先,提出了基于二次规划策略和改进双向快速扩展随机树(bidirectional rapidly-exploring random tree algorithm,Bi-RRT)的初始路径生成方法。然后,结合车辆非完整微分约束下的路径节点可行性判别方法研究,提出基于概率的目标偏向采样策略,提高了采样效率。最后,构建了面向车辆系统控制变量连续性的非线性最优化控制模型,解决泊车换向点的对接问题,提高了泊车轨迹平滑性。仿真结果表明,该方法在多障碍物场景中,规划时间相比Hybrid A*和Bi-RRT分别降低了86.71%和21.44%,轨迹质量也更具优越性。
The unstable kinematic characteristics of tractor-semitrailer vehicles bring considerable chal‐lenges for autonomous motion planning in the parking process.In this paper,sequential motion planning algorithm(SMPA)is proposed to address the problems of low efficiency of parking motion planning algorithms and poor smoothness of results for tractor-semitrailer in static scenario with multiple obstacles.Firstly,an initial path genera‐tion method based on the quadratic planning strategy and improved bidirectional rapidly-exploring random tree algo‐rithm(Bi-RRT)is proposed.Then,combined with the study of path node feasibility discrimination method under vehicle non-complete differential constraints,a probability-based target bias sampling strategy is proposed to im‐prove the sampling efficiency.Finally,a nonlinear optimal control model oriented to the continuity of the control variables of the vehicle system is constructed to solve the docking problem of the parking reversal point and improve the parking trajectory smoothness.Simulation results show that this method reduces the planning time by 86.71%and 21.44%compared to Hybrid A*and Bi-RRT,respectively,in multi obstacle scenarios,with more superior tra‐jectory quality.
作者
王元民
王亚飞
秦文刚
陈浩
刘银华
Wang Yuanmin;Wang Yafei;Qin Wengang;Chen Hao;Liu Yinhua(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093;School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240)
出处
《汽车工程》
EI
CSCD
北大核心
2024年第4期691-702,共12页
Automotive Engineering
基金
上海市自然科学基金面上项目(21ZR1444500)
上海市浦江人才计划(22PJD048)资助。
