摘要
针对野外移动机器人的滑动效益建模和补偿控制问题进行了研究.以履带式移动机器人为研究对象,将履带和地面之间的滑动效应建模为时变的滑动参数,由此建立起带滑动参数的机器人运动学和动力学模型,并采用基于方根无色卡尔曼滤波(SR-UKF)的在线非线性估计方法对机器人的位姿和滑动参数进行联合估计.在此基础上,提出了一种基于动态反馈线性化的全局指数收敛控制律以解决机器人的轨迹跟踪控制问题.仿真实验表明了该方法的有效性和鲁棒性.
The problems of slippage modeling and compensating control for mobile robots in outdoor environments are studied.Focusing on a tracked mobile robot,the slippage efficiency between tracks of a tracked mobile robot and ground is analyzed and modeled as time-varying parameters,meanwhile the corresponding kinematic and dynamic models of the robot are created with slipping parameters.Then the online nonlinear estimators such as the square-rooted unscented Kalman filter （UKF）can be used to estimate the pose and slipping parameters jointly.Furthermore the dynamic feedback linearization integrated with a globally exponentially convergent control law is applied to the tracking control.Simulation results demonstrate the effectiveness and robustness of the proposed method.
出处
《机器人》
EI
CSCD
北大核心
2011年第3期265-272,共8页
Robot
基金
国家863计划资助项目(2006AA040202)
国家自然科学基金资助项目(61005092)
关键词
移动机器人
滑动建模
SR-UKF
跟踪控制
mobile robot
slippage modeling
square-rooted unscented Kalman filter（SR-UKF）
tracking control
