External Force Estimation of Legged Robots via a Factor Graph Framework with a Disturbance Observer

Abstract

Recently, legged robots have been used for various purposes, such as exploring unknown terrain or interacting with the world. For control and planning legged systems during interactive operations, it is essential to estimate and respond to external forces. However, in legged system, it becomes difficult to estimate forces due to highly dynamic situations. There are several studies that use a force sensor on the foot and end effector, but these approaches have disadvantages in terms of cost and sustainability. Therefore, in this paper, we propose an improved method for estimating external forces without a force sensor. First, each leg force was obtained using the system dynamics of the robot with a disturbance observer. Then, by preintegration, it was tightly coupled with other sensors to estimate the pose and external force simultaneously. Despite the impact and slip, we estimate external forces accurately in standing and walking motions. Moreover, we compared pose estimation performance with VINS-Mono [1], and there is no significant accuracy degradation in spite of highly dynamic force residual.