首页|基于改进A*-DWA算法的移动机器人路径规划

基于改进A*-DWA算法的移动机器人路径规划

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为在能量有限或补给不足的情况下,降低移动机器人的能耗,提高在动态环境下给定任务的完成率,提出一种改进A*算法与动态窗口法相融合的路径规划方法.首先,考虑地面坡度、摩擦等因素,构建机器人能耗模型,提出基于能耗成本的路径搜索新准则.其次,针对路径冗余、多转折造成能量损耗的问题,提出基于动态基准转折惩罚、三角剪枝与弦定弧过渡法相结合的路径优化方法,保证全局路径能耗最优.接着,针对动态窗口法狭窄环境下灵活性差的问题,融合改进A*和动态窗口法并提出航向角自调整策略,增强动态避障能力.最后,设计了全局节能路径偏离评价与能耗评价子函数用于局部节能路径的规划.仿真结果表明,所提方法在能耗、平滑性和动态避障等方面有明显的提升,在复杂、狭窄的场景中应用更具优越性.
Mobile robot path planning based on improved A*-DWA algorithm
To reduce the energy consumption of the mobile robot and improve the completion rate of a given task in the dynamic environment under the condition of limited energy or insufficient supply,a path planning method based on the integration of energy-saving A*algorithm and dynamic window approach was proposed.Considering the road slope,friction and other factors,the energy consumption model of the robot was constructed,and a new path search criterion based on energy cost was proposed.Aiming at the problem of energy loss caused by redundant paths and multiple transitions,a path optimization method based on dynamic benchmark transition penalty,triangular pruning and string-definite arc transition method was proposed to ensure the optimal global path energy consumption.To solve the problem of poor flexibility of dynamic window method in narrow environment,the improved A*and dy-namic window method were combined,and the heading angle self-adjustment strategy was proposed to enhance the dynamic obstacle avoidance ability.The global energy saving path deviation evaluation and energy consumption eval-uation sub-functions were designed to plan the local energy saving path.Simulation results showed that the proposed method had significant improvement in energy consumption,smoothness and dynamic obstacle avoidance,and was more advantageous in complex and narrow scenes.

mobile robotpath planningA*algorithmdynamic window approachdynamic obstacle avoidance

刘钰铭、黄海松、范青松、朱云伟、陈星燃、韩正功

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贵州大学现代制造技术教育部重点实验室,贵州 贵阳 550025

重庆机电职业技术大学信息工程学院,重庆 402760

移动机器人 路径规划 A*算法 动态窗口法 动态避障

国家自然科学基金资助项目贵州省高层次创新人才计划资助项目重庆市自然科学基金面上资助项目贵州省科技计划资助项目贵州省科技计划资助项目贵州省科技计划资助项目贵州省科技计划资助项目贵州省科技计划资助项目High Level Innovation Talent Plan of Guizhou Province,ChinaGuizhou Provincial Science and Technology Program,ChinaGuizhou Provincial Science and Technology Program,ChinaGuizhou Provincial Science and Technology Program,ChinaGuizhou Provincial Science and Technology Program,ChinaGuizhou Provincial Science and Technology Program,China

52165063黔科合平台人才-GCC[2022]006-1CSTB2022NSCQ-MSX1600黔科合支撑[2021]一般445172397黔科合支撑[2022]一般 008165QKH pingtai rencai-GCC[2022]006-1QKHS[2021]General 445172397QKHS[2022]General 008165

2024

10.13196/j.cims.2022.0634

计算机集成制造系统
中国兵器工业集团第210研究所

计算机集成制造系统

CSTPCD北大核心
影响因子：1.092
ISSN：1006-5911
年,卷(期)：2024.30(1)
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