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室内环境下改进的混合路径规划算法 被引量:1

Improved Hybrid Path Planning Algorithm in Indoor Environment
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摘要 为了解决室内非结构化复杂环境下的机器人在路径规划时常常出现目标点不可达、规划过程产生折角偏移、规划过程无法及时规避动态障碍物等问题,提出一种改进的混合室内路径规划算法。该算法将改进的全局路径规划与改进的局部路径规划算法相融合。首先,优化传统A-Star算法的启发因子,减少搜索范围和节点,再通过角平分线切点法对传统A-Star算法进行平滑处理。其次,综合路径与环境信息,采用改进的人工势场算法进行局部路径规划,通过修正斥力场参数来解决目标点不可达问题,同时构造了动态的势力场函数,使其具备决解决动态障碍物的能力。最后,对混合算法进行实际环境的路径规划实验,比起传统的混合算法文中提出的混合算法在路径规划长度上减少11.4%,运行时间减少11.1%,少经过34个冗余节点,结果表明该融合算法可以有效解决室内非结构化复杂的路径规划问题。 In the path planning of robots in the indoor unstructured complex environment,problems often arise such as inaccessible target points,deflection in the planning process,and failure to avoid dynamic obstacles in time.To solve these problems,an improved hybrid algorithm for indoor path planning is proposed,which combines the improved global path planning with the improved local path planning algorithm.Firstly,the heurism factor of the traditional A-Star algorithm is optimized,the search range and nodes are reduced,and then the traditional A-Star algorithm is smoothed by the Angle bisector tangent point method.Secondly,with the combination of path and environment information,an improved artificial potential field algorithm is employed for local path planning,and then the repulsive field parameters are modified to solve the problem of unreachable target point.Also,the dynamic force field function is constructed which enables it to resolve dynamic obstacles.Finally,a path planning experiment was conducted on the hybrid algorithm in real environment.Compared with the traditional hybrid algorithm,by the hybrid algorithm proposed in this paper the path planning length is reduced by 10.3%,the running time by 12.5%,and 34 redundant nodes are cut out.The results show that the hybrid algorithm can effectively solve the problems in the indoor unstructured and complex path planning.
作者 徐淑萍 杨定哲 闫索遥 杨帆 XU Shuping;YANG Dingzhe;YAN Suoyao;YANG Fan(School of Computer Science and Engineering,Xi’an Technological University,Xi’an 710021,China)
出处 《西安工业大学学报》 CAS 2024年第2期232-243,共12页 Journal of Xi’an Technological University
基金 陕西省科技厅重点产业链一段项目(2022GY-239)。
关键词 移动机器人 路径规划技术 A-STAR算法 人工势场算法 自主避障 计算机控制 mobile robot path planning technology A Star algorithm artificial potential field algorithm autonomous obstacle avoidance conputer control
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