DocumentCode :
2851737
Title :
Study of the operator model for robotic excavation
Author :
Gang, Guo ; Bo, Li ; Xuehui, Wang ; Da, Yu ; Haibo, Qiang
Author_Institution :
Eng. Inst. of Corps of Eng., PLA Univ. of Sci. & Technol., Nanjing, China
fYear :
2012
fDate :
24-27 June 2012
Firstpage :
425
Lastpage :
429
Abstract :
Improving the intelligent ability of a robotic excavator is useful in practice, and this is a challengeable work due to the complex working environment of robotic excavation. In order to increase the performance of automatic control, operator model of robotic excavation derive from excavator driver is established to overcome the complex nonlinearities of the control system. The model is accordant with the operation properties of the excavator that it improves the autonomous ability of the robotic excavator. The operator model of robotic excavation based on neural network theory is developed in this paper. The experiment results demonstrate that this operator model is effective and feasible.
Keywords :
control nonlinearities; excavators; intelligent control; intelligent robots; neurocontrollers; nonlinear control systems; automatic control performance; autonomous ability improvement; control system nonlinearities; excavator driver; intelligent robotic excavator; neural network theory; operator model; robotic excavation; Joints; Robot kinematics; Stereo image processing; intelligent control; neural network; operator model; robotic excavation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2363-5
Type :
conf
DOI :
10.1109/EEESym.2012.6258683
Filename :
6258683
Link To Document :
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