摘要
提出了一种基于误差矫正的轨迹纠偏算法,通过误差控制机器人快速矫正姿态。算法通过自适应蒙特卡罗定位(Adaptive Deterministic Monte Carlo Localization,AMCL)算法实时获取机器人位置和姿态,根据当前位姿与超前点求取偏差量,使用距离PID、角度PID将偏差量解算为机器人运动控制指令。最后,定位算法获取修正后的位姿,重新计算误差和控制量,形成闭环控制。实验结果表明,基于该控制系统的地坪磨抛机器人能够应对较大的轨迹偏离情况,在处理[0,15]度范围内的角度偏差和[0,22]厘米范围内的横向偏离的情况下,能够快速修正偏移量,保证导航精度。经过矫正,最后轨迹偏差在0.03 m范围内。与现有方法相比,提出的轨迹纠偏方法能够应对较大程度的偏移量,有效解决了地坪磨抛机器人的轨迹偏离问题。
In the process of autonomous navigation,the non-linear lateral jump and angle deviation are caused by the different ground planeness,which will cause great disturbance to the robot movement and lead to unpredictable trajectory deviation of the robot,which has always been a challenge for the precision of the engineering robot.In this paper,a trajectory correction algorithm based on error correction is proposed,which can quickly correct the robot S position and posture through error control.The algorithm obtains the position and posture of the robot in real time through the Adaptive Monte Carlo Localization,calculates the deviation between the current position and the leading point,and uses the distance PID and angle PID to calculate the robot motion control command.Finally,the position algorithm obtains the corrected position and posture,recalculate the error and control amount,and form the closed-loop control.The experimental results show that the floor grinding robot based on the control algorithm can deal with the large trajectory deviation,and can quickly correct the offset and ensure the navigation accuracy when dealing with the angle deviation within the range of[0,15]degrees or the lateral deviation within the range of[0,22]cm.After correction,the final trajectory deviation is within 0.03 m.Compared with existing methods,the proposed trajectory correction method can deal with the large offset,and effectively solve the trajectory deviation of the floor grinding robot.
作者
陈鸿宇
彭彦卿
戴厚德
林名强
CHEN Hongyu;PENG Yanqing;DAI Houde;LIN Mingqiang(School of Electrical Engineering and Automation,Xiamen University of Technology,Xiamen Fujian 361024,China;Quanzhou Institute of Equipment Manufacturing,Haixi Research Institute,Chinese Academy of Sciences,Jinjiang Fujian 362216,China)
出处
《机械设计与研究》
CSCD
北大核心
2022年第1期67-71,77,共6页
Machine Design And Research
基金
福建省自然科学基金(2019J01867)
泉州市科技计划(2020C010R)资助项目。
