DocumentCode :
2848847
Title :
Multiple self-organizing maps for control of a redundant manipulator in an environment with obstacles
Author :
Okada, Nobuhiro ; Qiu, Jinjun ; Han, Min ; Uehara, Ryunosuke ; Kondo, Eiji
Author_Institution :
Dept. of Intell. Machinery & Syst., Kyushu Univ., Fukuoka
fYear :
2008
fDate :
23-26 Aug. 2008
Firstpage :
212
Lastpage :
217
Abstract :
This paper proposes multiple self-organizing maps (SOMs) for control of a visuo-motor system that consists of a redundant manipulator and multiple cameras in an unstructured environment. The maps control the manipulator so that it reaches its end-effector to targets given in the camera images. Also the maps make the manipulator take obstacle free poses. Multiple cameras are introduced to avoid occlusions and multiple SOMs are introduced to deal with multiple camera images. Using two or more SOMs may cause inconsistency among them. We, therefore, developed a new learning method of SOMs to keep the consistency. We also developed a simple collision avoidance approach by using the multiple SOMs and a simple path planning technique. Since the collision free pose is accomplished by the multiple SOMs, the path planning system only plans the end-effectorpsilas path. Simulation results will be shown. This paper proposes multiple self-organizing maps (SOMs) for control of a visuo-motor system that consists of a redundant manipulator and multiple cameras in an unstructured environment. The maps control the manipulator so that it reaches its end-effector to targets given in the camera images. Also the maps make the manipulator take obstacle free poses. Multiple cameras are introduced to avoid occlusions and multiple SOMs are introduced to deal with multiple camera images. Using two or more SOMs may cause inconsistency among them. We, therefore, developed a new learning method of SOMs to keep the consistency. We also developed a simple collision avoidance approach by using the multiple SOMs and a simple path planning technique. Since the collision free pose is accomplished by the multiple SOMs, the path planning system only plans the end-effectorpsilas path. Simulation results will be shown.
Keywords :
cameras; collision avoidance; end effectors; redundant manipulators; robot vision; self-organising feature maps; collision avoidance approach; end-effector; learning method; multiple cameras; obstacle free poses; occlusions; path planning technique; redundant manipulator; self-organizing maps; visuo-motor system; Artificial neural networks; Cameras; Intelligent systems; Learning systems; Machine intelligence; Machinery; Manipulators; Path planning; Robot kinematics; Self organizing feature maps;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Science and Engineering, 2008. CASE 2008. IEEE International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
978-1-4244-2022-3
Electronic_ISBN :
978-1-4244-2023-0
Type :
conf
DOI :
10.1109/COASE.2008.4626540
Filename :
4626540
Link To Document :
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