DocumentCode :
2050073
Title :
Neural network-based recognition of navigation environment for intelligent shipyard welding robots
Author :
Kim, Min Young ; Cho, Hyung Suck ; Kim, Jae-hoon
Author_Institution :
Dept. of Mech. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
446
Abstract :
A robotic welding system for closed block assembly in shipyard needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In the paper, the developed 3D sensor system is briefly introduced, and a strategy of environmental recognition for welding mobile robot navigation is developed in order to recognize work environments efficiently. The task space formed between two lengths within closed blocks is classified into far field. middle field, and near field, according to the robot-to-welding environment distance. The recognition strategy and tactics for sensing the work environment and detecting the obstacles are described and discussed in derail. Finally, a neural network structure for obstacle classification is proposed and tested in a real work environment
Keywords :
CAD; assembling; image sensors; mobile robots; neural nets; path planning; position control; welding; 3D sensor system; closed block assembly; environmental recognition; intelligent shipyard welding robots; navigation environment; neural network-based recognition; obstacle classification; obstacles detection; weld seam tracking; Assembly systems; Mobile robots; Navigation; Neural networks; Orbital robotics; Robot sensing systems; Robotic assembly; Sensor systems; Testing; Welding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on
Conference_Location :
Maui, HI
Print_ISBN :
0-7803-6612-3
Type :
conf
DOI :
10.1109/IROS.2001.973397
Filename :
973397
Link To Document :
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