Estimation and Stabilization of Humanoid Flexibility Deformation Using Only Inertial Measurement Units and Contact Information

Most robots are today controlled as being entirely rigid. But often, as for HRP-2 robot, there are flexible parts, intended for example to absorb impacts. The deformation of this flexibility modifies the orientation of the robot and endangers balance. Nevertheless, robots have usually inertial sensors (IMUs) to reconstruct their orientation based on gravity and inertial effects. Moreover, humanoids have usually to ensure a firm contact with the ground, which provides reliable information on surrounding environment. We show in this study how important it is to take into account these information to improve IMU-based position/orientation reconstruction. We use an extended Kalman filter to rebuild the deformation, making the fusion between IMU and contact information, and without making any assumption on the dynamics of the flexibility. We show how, with this simple setting, we are able to compensate for perturbations and to stabilize the end-effector’s position/orientation in the world reference frame. We show also that this estimation is reliable enough to enable a closed-loop stabilization of the flexibility and control of the CoM position with the simplest possible model. balance; compliance; state observation; sensor fusion; inertial measurement unit; force sensors; stabilization