Localization and self calibration of a robot for volcano exploration

Daniele Caltabiano; Giovanni Muscato; Francesco Russo

doi:10.1109/robot.2004.1307212

Localization and self calibration of a robot for volcano exploration

Daniele Caltabiano, Giovanni Muscato, Francesco Russo

Università degli Studi di Catania

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper describes an algorithm for the localization and self calibration of a mobile robot. Data from a DGPS and two optical encoders are fused by an Extended Kalman Filter (EKF) in order to calculate the absolute position of the robot and to estimate the values of the parameters used by the odometry (wheels radii and wheelbase). The presented Self Calibrating EKF (EKF_SC) has been tested both on a simulator and on the mobile robot "Robovolc": a six independently actuated wheels robot for volcano exploration. The EKF _SC does not need a separate phase for the parameter identification. Moreover the odometry parameters of the Robovolc robot have been identified both with the UMBmark and with the EKF_SC; some comparative tests show an improvement of the estimated trajectories.

Original language	English
Pages (from-to)	586-591
Number of pages	6
Journal	Proceedings - IEEE International Conference on Robotics and Automation
Volume	2004
Issue number	1
DOIs	https://doi.org/10.1109/robot.2004.1307212
Publication status	Published - 1 Jan 2004
Externally published	Yes
Event	Proceedings- 2004 IEEE International Conference on Robotics and Automation - New Orleans, LA, United States Duration: 26 Apr 2004 → 1 May 2004

Keywords

Calibration
GPS
Localization
Odometry
Sensor fusion

Access to Document

10.1109/robot.2004.1307212

Cite this

@article{dc224c7063d04554acd721088b30f80d,

title = "Localization and self calibration of a robot for volcano exploration",

abstract = "This paper describes an algorithm for the localization and self calibration of a mobile robot. Data from a DGPS and two optical encoders are fused by an Extended Kalman Filter (EKF) in order to calculate the absolute position of the robot and to estimate the values of the parameters used by the odometry (wheels radii and wheelbase). The presented Self Calibrating EKF (EKFSC) has been tested both on a simulator and on the mobile robot {"}Robovolc{"}: a six independently actuated wheels robot for volcano exploration. The EKF SC does not need a separate phase for the parameter identification. Moreover the odometry parameters of the Robovolc robot have been identified both with the UMBmark and with the EKFSC; some comparative tests show an improvement of the estimated trajectories.",

keywords = "Calibration, GPS, Localization, Odometry, Sensor fusion",

author = "Daniele Caltabiano and Giovanni Muscato and Francesco Russo",

year = "2004",

month = jan,

day = "1",

doi = "10.1109/robot.2004.1307212",

language = "English",

volume = "2004",

pages = "586--591",

journal = "Proceedings - IEEE International Conference on Robotics and Automation",

issn = "1050-4729",

number = "1",

note = "Proceedings- 2004 IEEE International Conference on Robotics and Automation ; Conference date: 26-04-2004 Through 01-05-2004",

}

TY - JOUR

T1 - Localization and self calibration of a robot for volcano exploration

AU - Caltabiano, Daniele

AU - Muscato, Giovanni

AU - Russo, Francesco

PY - 2004/1/1

Y1 - 2004/1/1

N2 - This paper describes an algorithm for the localization and self calibration of a mobile robot. Data from a DGPS and two optical encoders are fused by an Extended Kalman Filter (EKF) in order to calculate the absolute position of the robot and to estimate the values of the parameters used by the odometry (wheels radii and wheelbase). The presented Self Calibrating EKF (EKFSC) has been tested both on a simulator and on the mobile robot "Robovolc": a six independently actuated wheels robot for volcano exploration. The EKF SC does not need a separate phase for the parameter identification. Moreover the odometry parameters of the Robovolc robot have been identified both with the UMBmark and with the EKFSC; some comparative tests show an improvement of the estimated trajectories.

AB - This paper describes an algorithm for the localization and self calibration of a mobile robot. Data from a DGPS and two optical encoders are fused by an Extended Kalman Filter (EKF) in order to calculate the absolute position of the robot and to estimate the values of the parameters used by the odometry (wheels radii and wheelbase). The presented Self Calibrating EKF (EKFSC) has been tested both on a simulator and on the mobile robot "Robovolc": a six independently actuated wheels robot for volcano exploration. The EKF SC does not need a separate phase for the parameter identification. Moreover the odometry parameters of the Robovolc robot have been identified both with the UMBmark and with the EKFSC; some comparative tests show an improvement of the estimated trajectories.

KW - Calibration

KW - GPS

KW - Localization

KW - Odometry

KW - Sensor fusion

U2 - 10.1109/robot.2004.1307212

DO - 10.1109/robot.2004.1307212

M3 - Conference article

AN - SCOPUS:3042575346

SN - 1050-4729

VL - 2004

SP - 586

EP - 591

JO - Proceedings - IEEE International Conference on Robotics and Automation

JF - Proceedings - IEEE International Conference on Robotics and Automation

IS - 1

T2 - Proceedings- 2004 IEEE International Conference on Robotics and Automation

Y2 - 26 April 2004 through 1 May 2004

ER -

Localization and self calibration of a robot for volcano exploration

Abstract

Keywords

Access to Document

Fingerprint

Cite this