Robot Self-Calibration Using Multiple Kinematic Chains-A Simulation Study on the iCub Humanoid Robot

Mechanism calibration is an important and nontrivial 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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE robotics and automation letters Ročník 4; číslo 2; s. 1900 - 1907
Hlavní autoři: Stepanova, Karla, Pajdla, Tomas, Hoffmann, Matej
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.04.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Calibration
calibration and identification
Cameras
Chains
End effectors
force and tactile sensing
Humanoid
Humanoid robots
Kinematics
Noise measurement
Optimization
optimization and optimal control
Parameters
Performance degradation
Perturbation
Robot vision systems
Robotics
Robots
Self calibration
Tactile sensors (robotics)
Touch
ISSN:2377-3766, 2377-3766
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Mechanism calibration is an important and nontrivial 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 letter, 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 as follows: first, type and number of intersecting kinematic chains used for calibration, second, parameters and chains subject to optimization, third, amount of initial perturbation of kinematic parameters, fourth, number of poses/configurations used for optimization, and fifth, amount of measurement noise in end-effector positions/cameras. The main findings are as follows: 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 multichain 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; and 4) adding noise to a sensory modality degrades performance of all calibrations employing the chains relying on this information.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2019.2898320