Title :
Grasp planning of 3D objects using genetic algorithm
Author :
Zhang, Zichen ; Gu, Jason
Author_Institution :
Dept. of Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada
Abstract :
In this paper, we apply genetic algorithm (GA) to the optimization problem in grasp planning. This method can be used to find “pregrasps” for 3D objects in arbitrary shape and different dexterous hands, which serve as the first step of a complete grasping action. Each component of the GA planner is discussed in detail. The proposed algorithm is implemented in GraspIt! simulator [1]. It is tested on different hand-object combinations and the result shows that genetic algorithm is effective in finding high-quality pregrasps.
Keywords :
dexterous manipulators; genetic algorithms; object detection; robot vision; 3D objects; GA; arbitrary shape; dexterous hands; genetic algorithm; grasp planning; Biological cells; Genetic algorithms; Grasping; Optimization; Planning; Sociology; Statistics; Genetic Algorithm; Multifingered Hands; Robot Grasping;
Conference_Titel :
Automation and Logistics (ICAL), 2012 IEEE International Conference on
Conference_Location :
Zhengzhou
Print_ISBN :
978-1-4673-0362-0
Electronic_ISBN :
2161-8151
DOI :
10.1109/ICAL.2012.6308157
