Research on Foot Slippage Estimation of Mammal Type Legged Robot.

The accurate of the velocity and posture data of legged robot such as hexapod and quadruped robots can not be obtained by body sensors only due to the influence of the sensor error itself and the installation error, as well as the foot slippage or mechanical error during the foot-terrain interaction. In this paper, the data fusion method based on Extended Kalman Filter (EKF) is adopted, and the data of accurate velocity and posture of trunk body are from the kinematics and IMU information. The single leg foot-terrain slippage model for mammal type legged robot based on leg dynamics model is proposed. The single leg foot-terrain slippage estimation method is presented. The method can detect the slippage rate of the single leg and the state of the slippage can be determined. The estimated value is compared with data obtained by the motion capture system (Mocap system), and the experimental results have demonstrated the effectiveness of the proposed method and realize the single leg slippage estimation of mammal type hexapod and quadruped robots.