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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 inertial measurement units (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 center of mass (CoM) position with the simplest possible model.

The main objective of this paper is to evaluate experimentally the influence of different structural parameters on passive dynamic gaits. For this purpose a passive dynamic walker with knees and arc-shaped feet has been designed and built. Incremental encoders have been added on the hip and knee joints and force sensors have been installed not only in the sole of the feet but also the thighs of the prototype. Furthermore, each leg segment is also equipped with an inertial measurement unit. The acquired information is then used to determine how the changes in the ramp angle affect the step period, the step length and the walking speed. Conclusions could play an important role on the generation of gaits for actuated biped robots.