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作 者:坚葆林 张博文 李许军 JIAN Baolin;ZHANG Bowen;LI Xujun(School of Electronic Information,Gansu Industry Polytechnic College,Tianshui 741025;School of Information Engineering,Gansu Institute of Mechanical&Electrical Engineering,Tianshui 741001)
机构地区:[1]甘肃工业职业技术学院电子信息学院,天水741025 [2]甘肃机电职业技术学院信息工程学院,天水741001
出 处:《电气工程学报》2025年第1期88-98,共11页Journal of Electrical Engineering
摘 要:针对传统时间弹性带(Time elastic band,TEB)算法在稠密障碍物环境中存在的全局路径偏离、路径不平滑及机器人运动不连续问题,提出一种结合电机控制优化的改进TEB平滑路径规划算法。该算法首先对机器人静态位姿进行动态自适应采样,确保机器人在高密度障碍物区域中紧密跟随全局路径。在此基础上,通过对TEB优化目标函数的扩展,利用五次多项式插值法引入轨迹连续性代价约束,减少电机的频繁加减速行为,实现机器人的路径平滑与运动连续。通过仿真对比试验,验证了所提改进TEB算法相较于现有基准算法,在保持电机稳定运行的前提下,能够规划出更贴近全局路径的平滑轨迹,使机器人高效穿越稠密障碍物区域。本研究为提升机器人在复杂环境中的路径规划能力与电机控制性能提供了有效方法。To address the issues of global path deviation,path discontinuity,and robot motion discontinuity in dense obstacle environments inherent in the traditional time elastic band(TEB)algorithm,an improved TEB smooth path planning algorithm combined with motor control optimization is proposed.The algorithm initially employs dynamic adaptive sampling of the robot’s static pose,ensuring close adherence to the global path in high-density obstacle regions.Based on this,the TEB optimization objective function is extended by incorporating a trajectory continuity cost constraint through quantic polynomial interpolation.This incorporation reduces the motor’s frequent acceleration and deceleration,thereby facilitating smoother path planning and more continuous robot motion.Simulation comparison experiments are conducted,the results show that,compared with existing benchmark algorithms,the proposed algorithm plans trajectories that are closer to the global path and smoother,while maintaining stable motor operation.This enables efficient navigation of the robot through dense obstacle areas.The research presented offers an effective method for enhancing robots’path planning capabilities and motor control performance in complex environments.
关 键 词:时间弹性带 电机控制 动态自适应 五次多项式插值 轨迹连续性约束
分 类 号:TM306[电气工程—电机] TP242[自动化与计算机技术—检测技术与自动化装置]
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