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Mechanism calibration is an important and non-trivial task in robotics.Advances in sensor technology make affordable but increasingly accurate devicessuch as cameras and tactile sensors available, making it possible to performautomated self-contained calibration relying on redundant information in thesesensory streams. In this work, we use a simulated iCub humanoid robot with astereo camera system and end-effector contact emulation to quantitativelycompare the performance of kinematic calibration by employing differentcombinations of intersecting kinematic chains -- either throughself-observation or self-touch. The parameters varied were: (i) type and numberof intersecting kinematic chains used for calibration, (ii) parameters andchains subject to optimization, (iii) amount of initial perturbation ofkinematic parameters, (iv) number of poses/configurations used foroptimization, (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 asobservability; (2) when using multi-chain calibration, fewer poses suffice toget similar performance compared to when for example only observation from asingle camera is used; (3) parameters of all chains (here 86 DH parameters) canbe subject to calibration simultaneously and with 50 (100) poses, end-effectorerror of around 2 (1) mm can be achieved; (4) adding noise to a sensorymodality degrades performance of all calibrations employing the chains relyingon this information.

Robot self-calibration using multiple kinematic chains -- a simulation study on the iCub humanoid robot