{"title":"An improved dynamic window approach algorithm for dynamic obstacle avoidance in mobile robot formation","authors":"Yanjie Cao, Norzalilah Mohamad Nor","doi":"10.1016/j.dajour.2024.100471","DOIUrl":null,"url":null,"abstract":"<div><p>Dynamic Window Approach (DWA) algorithm is a commonly used choice in dynamic obstacle avoidance. However, the traditional DWA algorithm evaluation function is poorly adapted to dynamic obstacle avoidance and has defects in efficiency and safety. In this paper, we consider the speed and heading of the mobile robot formation and the speed and heading of the obstacles and design the speed-varying obstacle avoidance and safety distance evaluation coefficients. The objective is to design an improved DWA algorithm to improve the obstacle avoidance ability of mobile robot formations when encountering dynamic obstacle interference. First, the obstacle environment in which the mobile robot formation is located is analyzed to determine the obstacles that threaten the formation and those that are not. Second, the obstacle velocity space is evaluated and analyzed using the velocity change evaluation coefficient so that the robot formation’s obstacle avoidance behavior after the combination of angular and linear travel velocities has high robustness in the face of dynamic obstacle interference. Finally, the evaluation coefficient of safe obstacle avoidance distance is designed to accurately judge the positional relationship between the robot formation and dynamic obstacles at the moment of obstacle avoidance, which maximizes the safety of the robot formation traveling. The experimental results show that the improved algorithm shortens the obstacle avoidance time by 37.3% and saves 16.8% of the distance traveled than the traditional algorithm. It also achieves good results in terms of robustness and safety.</p></div>","PeriodicalId":100357,"journal":{"name":"Decision Analytics Journal","volume":"11 ","pages":"Article 100471"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772662224000754/pdfft?md5=9771efe177a10c8ebb96d9ed52f7b44b&pid=1-s2.0-S2772662224000754-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Analytics Journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772662224000754","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Dynamic Window Approach (DWA) algorithm is a commonly used choice in dynamic obstacle avoidance. However, the traditional DWA algorithm evaluation function is poorly adapted to dynamic obstacle avoidance and has defects in efficiency and safety. In this paper, we consider the speed and heading of the mobile robot formation and the speed and heading of the obstacles and design the speed-varying obstacle avoidance and safety distance evaluation coefficients. The objective is to design an improved DWA algorithm to improve the obstacle avoidance ability of mobile robot formations when encountering dynamic obstacle interference. First, the obstacle environment in which the mobile robot formation is located is analyzed to determine the obstacles that threaten the formation and those that are not. Second, the obstacle velocity space is evaluated and analyzed using the velocity change evaluation coefficient so that the robot formation’s obstacle avoidance behavior after the combination of angular and linear travel velocities has high robustness in the face of dynamic obstacle interference. Finally, the evaluation coefficient of safe obstacle avoidance distance is designed to accurately judge the positional relationship between the robot formation and dynamic obstacles at the moment of obstacle avoidance, which maximizes the safety of the robot formation traveling. The experimental results show that the improved algorithm shortens the obstacle avoidance time by 37.3% and saves 16.8% of the distance traveled than the traditional algorithm. It also achieves good results in terms of robustness and safety.
动态窗口法(DWA)算法是动态避障的常用选择。然而,传统的 DWA 算法评价函数对动态避障的适应性较差,在效率和安全性方面存在缺陷。本文考虑了移动机器人编队的速度和航向以及障碍物的速度和航向,设计了随速度变化的避障和安全距离评价系数。目的是设计一种改进的 DWA 算法,以提高移动机器人编队在遇到动态障碍物干扰时的避障能力。首先,分析移动机器人编队所处的障碍物环境,确定对编队有威胁和无威胁的障碍物。其次,利用速度变化评价系数对障碍物速度空间进行评价和分析,使机器人编队在面对动态障碍物干扰时,角速度和线速度相结合后的避障行为具有较高的鲁棒性。最后,设计了安全避障距离评价系数,以准确判断避障时刻机器人编队与动态障碍物之间的位置关系,最大限度地提高机器人编队行进的安全性。实验结果表明,改进后的算法比传统算法缩短了 37.3% 的避障时间,节省了 16.8% 的行进距离。在鲁棒性和安全性方面也取得了良好的效果。