无人配送机器人的鲁棒避障路径规划

IF 0.4 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS
Mushu Wang, Xingxue Dong, Weigang Pan, Song Gao, Shuxin Wang
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引用次数: 0

摘要

针对公园半结构化道路复杂路况和路径规划困难的问题,提出了一种基于序列二次规划(SQP)算法优化的鲁棒路径规划方法。首先采用改进的矢量场直方图(VFH)算法确定最优可通过区域,然后根据最优可通过区域给出目标状态的确定方法;其次,根据起始点和目标状态,给出了一种基于分段二次Bezier曲线的避障路径描述方法;然后,基于车辆运行曲率约束和目标点方向变化裕度约束,建立曲线参数优化问题,采用SQP算法对曲线参数进行优化;最后,通过仿真实验和实车实验验证了所提方法的有效性和实用性。与其他方法相比,该方法路径最短,鲁棒性更好。DOI: 10.61416 / ceai.v25i2.8595
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Path Planning Of Obstacle Avoidance For Unmanned delivery robot
Aiming at complex road conditions and difficult path planning of semi-structured roads in a park, a robust path planning method based on sequential quadratic programming (SQP) algorithm optimization is proposed. Firstly, an improved vector field histogram (VFH) algorithm is used to determine the optimal passable area, and then the determination method of the target state is given based on the optimal passable area; Secondly, according to a starting point and the target state, a description method of obstacle avoidance path is given based on a piecewise quadratic Bezier curve. Then, the problem of curve parameter optimization is established based on the vehicle running curvature constraint and the direction change margin constraint of the target point, and the SQP algorithm is used to optimize the curve parameters; Finally, the effectiveness and practicability of the proposed method are verified by simulation experiments and real vehicle experiments. Compared with other methods, this method has the shortest path and better robustness. DOI: 10.61416/ceai.v25i2.8595
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来源期刊
CiteScore
1.50
自引率
22.20%
发文量
0
审稿时长
6 months
期刊介绍: The Journal is promoting theoretical and practical results in a large research field of Control Engineering and Technical Informatics. It has been published since 1999 under the Romanian Society of Control Engineering and Technical Informatics coordination, in its quality of IFAC Romanian National Member Organization and it appears quarterly. Each issue has up to 12 papers from various areas such as control theory, computer engineering, and applied informatics. Basic topics included in our Journal since 1999 have been time-invariant control systems, including robustness, stability, time delay aspects; advanced control strategies, including adaptive, predictive, nonlinear, intelligent, multi-model techniques; intelligent control techniques such as fuzzy, neural, genetic algorithms, and expert systems; and discrete event and hybrid systems, networks and embedded systems. Application areas covered have been environmental engineering, power systems, biomedical engineering, industrial and mobile robotics, and manufacturing.
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