複数の運動連鎖を用いたロボットの自己キャリブレーション：iCubヒューマノイドロボットのシミュレーション研究
Robot self-calibration using multiple kinematic chains -- a simulation study on the iCub humanoid robot
シミュレーション上のiCubヒューマノイドで、自己観察と自己接触による複数の運動連鎖を組み合わせた運動学キャリブレーションの性能を定量的に比較し、単一連鎖のパラメータを複数連鎖で校正する優位性や少ない姿勢での高精度化を示した。
著者: Karla Stepanova, Tomas Pajdla, Matej Hoffmann
分類: cs.RO
原文アブストラクト
Mechanism calibration is an important and non-trivial task in robotics. Advances in sensor technology make affordable but increasingly accurate devices such as cameras and tactile sensors available, making it possible to perform automated self-contained calibration relying on redundant information in these sensory streams. In this work, we use a simulated iCub humanoid robot with a stereo camera system and end-effector contact emulation to quantitatively compare the performance of kinematic calibration by employing different combinations of intersecting kinematic chains -- either through self-observation or self-touch. The parameters varied were: (i) type and number of intersecting kinematic chains used for calibration, (ii) parameters and chains subject to optimization, (iii) amount of initial perturbation of kinematic parameters, (iv) number of poses/configurations used for optimization, (v) amount of measurement noise in end-effector positions / cameras. The main findings are: (1) calibrating parameters of a single chain (e.g. one arm) by employing multiple kinematic chains ("self-observation" and "self-touch") is superior in terms of optimization results as well as observability; (2) when using multi-chain calibration, fewer poses suffice to get similar performance compared to when for example only observation from a single camera is used; (3) parameters of all chains (here 86 DH parameters) can be subject to calibration simultaneously and with 50 (100) poses, end-effector error of around 2 (1) mm can be achieved; (4) adding noise to a sensory modality degrades performance of all calibrations employing the chains relying on this information.
