慣性情報を用いた脚式ロボットの確率的接触状態推定
Probabilistic Contact State Estimation for Legged Robots using Inertial Information
脚先に搭載したIMUの計測値のみから、カーネル密度推定を用いて接地の安定性を確率的に推定する手法を提案し、二足・四足ロボットで検証した。
著者: Michael Maravgakis, Despina-Ekaterini Argiropoulos, Stylianos Piperakis, Panos Trahanias
分類: cs.RO
原文アブストラクト
Legged robot navigation in unstructured and slippery terrains depends heavily on the ability to accurately identify the quality of contact between the robot's feet and the ground. Contact state estimation is regarded as a challenging problem and is typically addressed by exploiting force measurements, joint encoders and/or robot kinematics and dynamics. In contrast to most state of the art approaches, the current work introduces a novel probabilistic method for estimating the contact state based solely on proprioceptive sensing, as it is readily available by Inertial Measurement Units (IMUs) mounted on the robot's end effectors. Capitalizing on the uncertainty of IMU measurements, our method estimates the probability of stable contact. This is accomplished by approximating the multimodal probability density function over a batch of data points for each axis of the IMU with Kernel Density Estimation. The proposed method has been extensively assessed against both real and simulated scenarios on bipedal and quadrupedal robotic platforms such as ATLAS, TALOS and Unitree's GO1.
