1 research outputs found
Robot self-calibration using multiple kinematic chains -- a simulation study on the iCub humanoid robot
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.Comment: 8 pages; 8 figures; substantially revised version compared to
previous - all data and results are ne