In this paper, we propose the "Kinetics Observer", a novel estimator addressing the challenge of state estimation for legged robots using proprioceptive sensors (encoders, IMU and force/torque sensors). Based on a Multiplicative Extended Kalman Filter, the Kinetics Observer allows the real-time simultaneous estimation of contact and perturbation forces, and of the robot's kinematics, which are accurate enough to perform proprioceptive odometry. Thanks to a visco-elastic model of the contacts linking their kinematics to the ones of the centroid of the robot, the Kinetics Observer ensures a tight coupling between the whole-body kinematics and dynamics of the robot. This coupling entails a redundancy of the measurements that enhances the robustness and the accuracy of the estimation. This estimator was tested on two humanoid robots performing long distance walking on even terrain and non-coplanar multi-contact locomotion.

翻译：本文提出了一种名为“动力学观测器”的新型估计器，旨在解决利用本体感知传感器（编码器、惯性测量单元及力/力矩传感器）进行腿式机器人状态估计的难题。该观测器基于乘法扩展卡尔曼滤波器，能够实时同步估计接触力与扰动外力，以及机器人的运动学状态，其精度足以实现基于本体感知的里程计功能。通过采用一种将接触运动学与机器人质心运动学相关联的粘弹性接触模型，动力学观测器确保了机器人全身运动学与动力学之间的紧耦合关系。这种耦合形成了测量冗余，从而提升了估计的鲁棒性与准确性。本估计器已在两台人形机器人上进行了测试，实验场景包括平坦地面的长距离行走以及非共面多接触步态运动。