移动机器人局部路径规划的改进DWA算法

IF 1.9 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL
Xin Lai, Dan Wu, Di Wu, Jia He Li, Hang Yu
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引用次数: 9

摘要

为了解决移动机器人动态窗口算法(DWA)稳定性差、能耗高的问题,本文提出了一种新的增强动态窗口算法。该算法以距离函数作为目标导向系数的权重,提出了一种新的评价函数来优化方位角。发现角速度剧烈变化引起的移动机器人抖动在机器人靠近目标点时减小。仿真结果表明,该算法有效地优化了移动机器人在运行过程中的稳定性,具有较低的角速度色散和较少的能量消耗,但运行时间略高于DWA。提出并验证了一种新的增强动态窗口算法。实验结果表明,所提出的算法可以降低机器人的能耗,提高机器人的工作效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced DWA algorithm for local path planning of mobile robot
Purpose The purpose of this study is to solve the problems of poor stability and high energy consumption of the dynamic window algorithm (DWA) for the mobile robots, a novel enhanced dynamic window algorithm is proposed in this paper. Design/methodology/approach The novel algorithm takes the distance function as the weight of the target-oriented coefficient, and a new evaluation function is presented to optimize the azimuth angle. Findings The jitter of the mobile robot caused by the drastic change of angular velocity is reduced when the robot is closer to the target point. The simulation results show that the proposed algorithm effectively optimizes the stability of the mobile robot during operation with lower angular velocity dispersion and less energy consumption, but with a slightly higher running time than DWA. Originality/value A novel enhanced dynamic window algorithm is proposed and verified. According to the experimental result, the proposed algorithm can reduce the energy consumption of the robot and improves the efficiency of the robot.
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来源期刊
CiteScore
4.50
自引率
16.70%
发文量
86
审稿时长
5.7 months
期刊介绍: Industrial Robot publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of robotic technology, and reflecting the most interesting and strategically important research and development activities from around the world. The journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations. Industrial Robot''s coverage includes, but is not restricted to: Automatic assembly Flexible manufacturing Programming optimisation Simulation and offline programming Service robots Autonomous robots Swarm intelligence Humanoid robots Prosthetics and exoskeletons Machine intelligence Military robots Underwater and aerial robots Cooperative robots Flexible grippers and tactile sensing Robot vision Teleoperation Mobile robots Search and rescue robots Robot welding Collision avoidance Robotic machining Surgical robots Call for Papers 2020 AI for Autonomous Unmanned Systems Agricultural Robot Brain-Computer Interfaces for Human-Robot Interaction Cooperative Robots Robots for Environmental Monitoring Rehabilitation Robots Wearable Robotics/Exoskeletons.
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