DocumentCode :
3479350
Title :
Research on the omni-directional mobile manipulator motion planning based on improved genetic algorithm
Author :
Jiang, Lin ; Liu, Baiyan ; Zeng, Liangcai ; Chen, Xinyuan ; Zhao, Jie ; Jihong Yan
Author_Institution :
Key Lab. of Metall. Equip. & its control of Minist. of Educ., Wuhan Univ. of Sci. & Technol., Wuhan, China
fYear :
2009
fDate :
5-7 Aug. 2009
Firstpage :
1921
Lastpage :
1926
Abstract :
The corresponding research was carried out aiming at difficult problem about the redundant robot motion planning. The research was on the omni-directional mobile manipulator (ODMM) motion planning based on the scope of species self-adjust genetic algorithm. In this paper, combining the ODMM characteristics the scope of species self-adjust genetic algorithm was studied, and the speed and efficiency of redundant robot motion planning was improved by the improved genetic algorithm. An example was used to prove that the efficiency of improved Genetic Algorithm in ODMM joint angle change optimization was higher than traditional Genetic Algorithm. Finally, the motion planning experiment about the omni-directional mobile platform and manipulator cooperation drawing circle was performed and the experiment proved that the improved genetic algorithm was effective.
Keywords :
genetic algorithms; mobile robots; path planning; redundant manipulators; joint angle change optimization; manipulator cooperation drawing circle; omni-directional mobile manipulator motion planning; redundant robot; species self-adjust genetic algorithm; Genetic algorithms; Manipulators; Mobile robots; Motion control; Motion planning; Optimization methods; Robot kinematics; Robot motion; Tactile sensors; Technology planning; improved genetic algorithm; motion planning; redundant robot;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
Type :
conf
DOI :
10.1109/ICAL.2009.5262620
Filename :
5262620
Link To Document :
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