DocumentCode :
716907
Title :
Omnidirectional-vision-based estimation for containment detection of a robotic mower
Author :
Junho Yang ; Soon-Jo Chung ; Hutchinson, Seth ; Johnson, David ; Kise, Michio
Author_Institution :
Dept. of Mech. Sci. & Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fYear :
2015
fDate :
26-30 May 2015
Firstpage :
6344
Lastpage :
6351
Abstract :
In this paper, we present an omnidirectional-vision-based localization and mapping system which can detect whether a robotic mower is contained in a permitted area. We exploit a robot-centric mapping framework that exploits a differential equation of motion of the landmarks, which are referenced with respect to the robot body frame. The estimator in our system generates a 3D point-based map with landmarks. Concurrently, the estimator defines a boundary of the mowing area with the estimated trajectory of the mower. The estimated boundary and the landmark map are provided for the estimation of the mowing location and for the containment detection. We validate the effectiveness of our system through numerical simulations and present the results of the outdoor experiment that we conducted with our robotic mower.
Keywords :
SLAM (robots); differential equations; mobile robots; robot vision; 3D point-based map; containment detection; landmark motion differential equation; omnidirectional-vision-based estimation; omnidirectional-vision-based localization-and-mapping system; outdoor experiment; permitted area; robot body frame; robot-centric mapping framework; robotic mower; Cameras; Estimation; Robot kinematics; Robot vision systems; Simultaneous localization and mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2015 IEEE International Conference on
Conference_Location :
Seattle, WA
Type :
conf
DOI :
10.1109/ICRA.2015.7140090
Filename :
7140090
Link To Document :
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