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作 者:杨婉振 蒋林[1,2] 汤勃 万乐 刘艺 Yang Wanzhen;Jiang Lin;Tang Bo;Wan Le;Liu Yi(Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education,Wuhan University of Science and Technology,Wuhan Hubei 430081;Institute of Robotics and Intelligent Systems,Wuhan University of Science and Technology,Wuhan Hubei 430081)
机构地区:[1]武汉科技大学冶金装备及其控制教育部重点实验室,湖北武汉430081 [2]武汉科技大学机器人与智能系统研究院,湖北武汉430081
出 处:《中国仪器仪表》2025年第2期78-83,共6页China Instrumentation
基 金:国家重点研发计划项目(2019YFB1310000);湖北省重点研发计划项目(2020BAB098);国家自然科学基金(51874217)。
摘 要:针对A^(*)算法规划出来的路径贴近障碍物、转折点多、不能保证机器人导航过程中安全性等问题,本文提出了一种基于动态距离场地图的改进A^(*)路径规划算法。首先,对路径规划用的栅格地图进行预处理,利用多层次的地图结构生成代价地图。然后,改进距离场算法,通过倒角距离变换对代价地图进行近似距离计算,生成距离场地图;改进A^(*)算法的评价函数,将距离场地图融入到A^(*)的评价函数中,解决了A^(*)算法规划出来的路径贴近障碍物、转折点多的问题;在计算距离场地图时加入最大距离限制,解决了空旷大环境下规划路径冗余的问题。经过多次试验后,证明该算法规划路径时耗时短、效率高,规划出来的路径更安全、远离障碍物,保证了机器人导航过程中的安全性。To address issues with A^(*)path planning,such as paths that are too close to obstacles,frequent turns,and insufficient safety during robot navigation,an improved A^(*)path planning algorithm based on a dynamic distance field map is proposed.First,a cost map is generated by preprocessing the grid map used for path planning with a multi-level map structure.Then,the distance field algorithm is enhanced using a chamfer distance transform to approximate distance calculations on the cost map,generating a distance field map.The evaluation function of the A^(*)algorithm is improved by integrating the distance field map,effectively addressing the problem of paths being too close to obstacles and having excessive turns.Additionally,a maximum distance limit is introduced when calculating the distance field map,reducing redundant paths in large,open environments.Multiple experiments demonstrate that this algorithm achieves faster and more efficient path planning,producing paths that are safer,maintain greater distance from obstacles,and ensure safety during robot navigation.
关 键 词:距离场 A^(*)最大距离限制 路径规划 代价地图
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