摘要
为了实时获取农用履带机器人运行过程中履带与地面之间的滑动信息,改善机器人控制精度,在对履带机器人运动学原理进行分析的基础上,推导了机器人运动学方程和非线性测量方程,设计了基于无迹卡尔曼滤波的滑动参数估计系统,实时估计出机器人精确姿态,并根据机器人的运动特性重建不可测的滑动量。实验结果表明:滑动参数估计系统可以提供准确和高更新率的滑动量,为农用履带机器人的精确控制提供依据。
In order to real-time achieve accurate sliding parameters between tracks of a agricultural tracked robot and ground and improve control accuracy,a dynamics equation and nonlinear measurement equation of agricultural tracked robot were deduced by analyzing working principle of an agricultural tracked robot and using dynamics principle.Then an estimation system based on the unscented Kalman filter（UKF） was designed to estimate the precision pose parameters of agricultural tracked robot.Through this estimation the system sliding parameters might be reconstructed relying on kinematics analysis,which couldn＇t be directly measured before.The simulation and experimental results suggested that with careful modeling of agricultural tracked robot,the estimation system was able to provide reliable and high update rate sliding parameters,which were taken as the basis for accurate control.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2014年第4期55-60,共6页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金资助项目(51205101)
安徽省教育厅自然科学基金资助项目(KJ2014A074)
安徽农业大学博士启动基金资助项目
关键词
农用履带机器人
无迹卡尔曼滤波
滑动参数
Agricultural tracked robot
Unscented Kalma n filter
Sliding parameters
