扁平足ヒューマノイドロボットにおける浮動基底推定器の実験的比較
An Experimental Comparison of Floating Base Estimators for Humanoid Robots with Flat Feet
iCubヒューマノイド上で、状態表現や観測・行列リー群誤差・システムダイナミクスの選択が異なる複数の扁平足フィルタをシミュレーションと実機で比較し、フィルタの一貫性と軌道誤差を評価した。
著者: Prashanth Ramadoss, Stefano Dafarra, Silvio Traversaro, Daniele Pucci
分類: cs.RO
原文アブストラクト
Extended Kalman filtering is a common approach to achieve floating base estimation of a humanoid robot. These filters rely on measurements from an Inertial Measurement Unit (IMU) and relative forward kinematics for estimating the base position-and-orientation and its linear velocity along with the augmented states of feet position-and-orientation, thus giving them their name, flat-foot filters. However, the availability of only partial measurements often poses the question of consistency in the filter design. In this paper, we perform an experimental comparison of state-of-the-art flat-foot filters based on the representation choice of state, observation, matrix Lie group error and system dynamics evaluated for filter consistency and trajectory errors. The comparison is performed over simulated and real-world experiments conducted on the iCub humanoid platform.
