DocumentCode :
1558764
Title :
Low-order-complexity vision-based docking
Author :
Minten, Brian W. ; Murphy, Robin R. ; Hyams, Jeff ; Micire, Mark
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Volume :
17
Issue :
6
fYear :
2001
fDate :
12/1/2001 12:00:00 AM
Firstpage :
922
Lastpage :
930
Abstract :
This paper reports on a reactive docking behavior which uses a vision algorithm that grows linearly with the number of image pixels. The docking robot imprints (initializes) on a two-colored docking fiducial upon departing from the dock, then uses region statistics to adapt the color segmentation in changing lighting conditions. The docking behavior was implemented on a marsupial team of robots, where a daughter micro-rover had to reenter the mother robot from an approach zone with a 2 m radius and 140° angular width with a tolerance of ±5 and ±2 cm. Testing during outdoor conditions (noon, dusk) and challenging indoor scenarios (flashing lights) showed that using adaptation and imprinting was more robust than using imprinting atone
Keywords :
artificial intelligence; computational complexity; computer vision; image segmentation; multi-agent systems; artificial intelligence; color segmentation changing lighting conditions; daughter micro-rover; docking robot; image pixels; low-order-complexity vision-based docking; multi agent systems; reactive docking behavior; two-colored docking fiducial; Cognitive robotics; Image segmentation; Intelligent control; Intelligent robots; Pixel; Robot kinematics; Robot vision systems; Robustness; Statistics; Testing;
fLanguage :
English
Journal_Title :
Robotics and Automation, IEEE Transactions on
Publisher :
ieee
ISSN :
1042-296X
Type :
jour
DOI :
10.1109/70.976026
Filename :
976026
Link To Document :
بازگشت