Estimation of Ground Posture Angle for Quadruped Robots Based on IMU

In unstructured environments, perceiving ground posture angles can help quadruped robots make some adjustments to their movement strategy. While using vision and lidar to perceive terrain is prone to be affected by weather, light, surface texture, etc. This paper introduces a proprioception approach based on the Inertial Measurement Unit (IMU) and kinematics to estimate the ground’s pitch and roll angle. Firstly, the posture angle of the robot body can be obtained according to the IMU under a framework of Extended Kalman Filtering (EKF), and the position of each foot end can be obtained based on the kinematics using the joint encoder information. In addition, a weighted Gaussian probability touchdown estimation model is proposed in this paper, which considers the amplitude of knee torque and the height of the foot end in the vertical direction. By selecting the position of the foot end in two stance phases, the spatial geometric parameters of the foothold support plane can be calculated using Moore–Penrose pseudoinverse based on the least squares method. Furthermore, a low pass filter is employed for smoothing the estimated ground posture angle. The experiment based on the Unitree Robotics GO1 quadruped robot shows the accurate estimation of the ground’s pitch and roll angle. Besides, the touchdown detection method has a good effect on estimating the contact state during trotting.