Application of a modified Genetic Algorithm for enhancing grasp quality on 3D objects

Author

Rakesh, Venkataramani ; Sharma, Utkarsh ; Rao, B.P.C. ; Venugopal, S. ; Asokan, T.

Author_Institution

Robot. & Remote Handling Sect., Indira Gandhi Centre for Atomic Res. (IGCAR), Kalpakkam, India

fYear

2015

fDate

18-20 Feb. 2015

Firstpage

1

Lastpage

5

Abstract

Robots are increasingly being inducted to perform a variety of complex handling operations in various industries. In contrast to use of parallel jaw grippers, automated grasping by robot fingers, offer more challenges in synthesis and task planning. In this paper, a meta-heuristic optimization method based on a modified Genetic Algorithm (GA) has been formulated for automated synthesis of high quality grasps. This unique modified GA scheme is applied on initially feasible grasps. The widely used largest ball criterion is employed to calculate the quality of the resulting grasps. The performance of the method is numerically presented by the use of tessellated 3D objects for the implementation of the algorithm. The optimization for these test cases is conducted for both frictional and non-frictional cases.

Keywords

friction; genetic algorithms; grippers; 3D objects; GA; automated grasping; complex handling operations; frictional cases; grasp quality; high quality grasps; largest ball criterion; metaheuristic optimization method; modified genetic algorithm; nonfrictional cases; parallel jaw grippers; robot fingers; task planning; tessellated 3D objects; Friction; Genetic algorithms; Optimization; Planning; Robots; Thumb; Robot grasping; modified Genetic Algorithm (GA); tessellation;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics, Automation, Control and Embedded Systems (RACE), 2015 International Conference on

Conference_Location

Chennai

Type

conf

DOI

10.1109/RACE.2015.7097278

Filename

7097278