Inertia Estimation of Quadruped Robot under Load and Its Walking Control Strategy in Urban Complex Terrain

Abstract

When the quadruped robot is engaged in logistics transportation tasks, it encounters a challenge where the distribution of the center of mass (CoM) of the loaded items is not only random but also subject to time variations. Consequently, the robot becomes susceptible to non-zero resultant torques, which inevitably impact its body posture during the walking process. This paper proposes a method to estimate the CoM inertia using four one-dimensional force sensors and a walking control strategy for complex urban terrain. The inertia tensor and CoM of the load are first estimated, then the robot’s dynamics are compensated, and foothold adjustments are made for underactuated orientations to compensate for the extra moment generated by the CoM offset. For uneven terrain, the terrain estimator and event-based gait are used to adjust the robot’s gait to reduce the impact of terrain changes on the robot. The effectiveness of the proposed method and the feasibility of load walking in urban terrain are verified through comparative experiments, complex terrain load walking experiments in Webots, and real prototype experiments.