Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
Zur Ablage hinzufügen
  Lokale TagsFreigabegeschichteDetailsÜbersicht

Freigegeben
Zeitschriftenartikel

Simultaneous Calibration of Odometry and Sensor Parameters for Mobile Robots

MPG-Autoren
/persons/resource/persons83915

Franchi,  A
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

Externe Ressourcen

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6482657
(Verlagsversion)

Volltexte (beschränkter Zugriff)
Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in PuRe verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Censi, A., Franchi, A., Marchionni, L., & Oriolo, G. (2013). Simultaneous Calibration of Odometry and Sensor Parameters for Mobile Robots. IEEE Transaction on Robotics, 29(2), 475-492. doi:10.1109/TRO.2012.2226380.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-B52C-F
Zusammenfassung
Consider a differential-drive mobile robot equipped with an on-board exteroceptive sensor that can estimate its own motion, e.g., a range-finder. Calibration of this robot involves estimating six parameters: three for the odometry (radii and distance between the wheels), and three for the pose of the sensor with respect to the robot. After analyzing the observability of this problem, this paper describes a method for calibrating all parameters at the same time, without the need for external sensors or devices, using only the measurement of the wheels velocities and the data from the exteroceptive sensor. The method does not require the robot to move along particular trajectories. Simultaneous calibration is formulated as a maximum-likelihood problem and the solution is found in a closed form. Experimental results show that the accuracy of the proposed calibration method is very close to the attainable limit given by the Cramér–Rao bound.