State of the art legged robots are either capable of measuring torque at the output of their drive systems, or have transparent drive systems which enable the computation of joint torques from motor currents. In either case, this sensor modality is seldom used in state estimation. In this paper, we propose to use joint torque measurements to estimate the centroidal states of legged robots. To do so, we project the whole-body dynamics of a legged robot into the nullspace of the contact constraints, allowing expression of the dynamics independent of the contact forces. Using the constrained dynamics and the centroidal momentum matrix, we are able to directly relate joint torques and centroidal states dynamics. Using the resulting model as the process model of an Extended Kalman Filter (EKF), we fuse the torque measurement in the centroidal state estimation problem. Through real-world experiments on a quadruped robot with different gaits, we demonstrate that the estimated centroidal states from our torque-based EKF drastically improve the recovery of these quantities compared to direct computation.
翻译:艺术脚形机器人的状态要么能够测量驱动系统输出的电力,要么具有透明的驱动系统,能够从电流中计算联合电压。 在这两种情况下,这种传感器模式都很少用于国家估算。 在本文中,我们提议使用联合火力测量来估计脚形机器人的环形状态。 为了做到这一点,我们将一个脚形机器人的全体动态投射到接触限制的空隙中,允许表达独立于接触力的动态。我们利用受限制的动力和中间体动力矩阵,能够直接将联合火力和中体状态动态联系起来。我们利用由此产生的模型作为扩展的卡尔曼过滤器(EKF)的流程模型,将原子测量结合到环形状态估算问题中。我们通过用不同的毛孔对四重机器人进行真实世界实验,我们证明我们基于圆柱形的电动电动动力估计的机器人状态大大改善了这些数量的回收量,而不是直接计算。