一种轮式移动机器人实时速度估计方法

环境和机器人自身的不确定性影响轮式移动机器人的轨迹跟踪控制性能,此时仅仅使用里程计往往不能正确表达机器人的状态信息。在无速度传感器的情况下,讨论了使用加速度传感器和位置传感器的输出实时估计轮式移动机器人的速度。首先使用滑模观测器进行里程计信号处理,然后对车体加速度信号进行带通滤波提取车体扰动信息,通过频域融合信号表达轮式移动机器人的速度,并针对正交轮式全方位移动机器人进行了轨迹跟踪控制研究。试验结果表明采用融合数据可以更准确提供机器人的状态信息并得到更好的控制性能。

Uncertainties in environment and robot itself worsen performance of trajectory tracking control of a wheeled mobile robot. States of the robot cannot be correctly estimated by the odometry in this situation. The velocities estimation problem is described for a wheeled mobile robot without velocity sensors. Real-time velocities are estimated using accelerometers and position-measurement sensors. First the odometry signal is processed using sliding mode observer, then bandpass filter is applied to extract disturbances information of the robot body. The fused data in frequency domain is used to represent velocities of the wheeled mobile robot and fed into controller of an omnidirectional mobile robot with orthogonal-wheel assemblies for studying its trajectory tracking control. The experimental results show that more proper data of the robot states are provided and better control performance can be obtained using fused data.