Evolutionary multi criteria design optimization of robot grippers

Applied Soft Computing Journal

Volumn 9, Issue 1, 2009, Pages 159-172

  Saravanan, R ^a   Ramabalan, S ^b   Ebenezer, N Godwin Raja ^c   Dharmaraja, C ^d  

^a KUMARAGURU COLLEGE OF TECHNOLOGY   (India)

^b J J COLLEGE OF ENGINEERING AND TECHNOLOGY   (India)

^c Einstein College of Engineering   (India)

^d VIT UNIVERSITY   (India)

Author keywords

Evolutionary computing; MODE; MOGA; Multicriterion optimization; NSGA II; Optimal gripper design; Robotics

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; COMPOSITE STRUCTURES; CONSTRAINED OPTIMIZATION; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHMS; GRIPPERS; MACHINE DESIGN; MULTIOBJECTIVE OPTIMIZATION; OPTIMIZATION; PARETO PRINCIPLE; ROBOTICS; ROBOTS;

EVOLUTIONARY COMPUTING; MODE; MOGA; MULTICRITERION OPTIMIZATION; NSGA-II; OPTIMAL GRIPPER DESIGN;

PROBLEM SOLVING;

EID: 53749106275     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2008.04.001     Document Type: Article

References (21)

1. Osswald D., and Wörn H. Mechanical system and control system of a dexterous robot hand. Proceedings of the International Conference on Humanoid Robots. Tokyo (2001)
2. Butterfass J., Grebenstein M., Liu H., and Hirzinger G. DLR-Hand 11: next generation of a dextrous robot hand. Robotics and Automation 1 (2001) 109-114
3. Zhu Y., Gao X., Xie Z., and Liu H. Development of a gripper for Chinese space robot. Proceedings of IEEE International Conference on Mechatronics and Automation (2006) 1465-1470
4. Cesare Stefanini R., Cutkoskq Mark, and Paolo Dario. A high force miniature gripper fabricated via shape deposition manufacturing. Proceedings of the IEEE international Conference on Robotics & Automation. Taipei, Taiwan, September 14-19 (2003)
5. Manley J.D., Smith T.J., Holden J., Edwards R., and Liptrot G. Modular approaches to automation system design using industrial robots. Journal of the Association for Laboratory Automation 13 1 (2008) 13-23
6. Zhong Z.W., and Yeong C.K. Development of a gripper using SMA wire. Sensors and Actuators A: Physical 126 2 (2006) 375-381
7. Zhong Z.W., and Chan S.Y. Investigation of a gripping device actuated by SMA wire. Sensors and Actuators A: Physical 136 1 (2007) 335-340
8. Pham D.T., and Gourashi N.S. Knowledge-based configuration design. Proceedings of IEEE International Conference on Industrial Informatics. August (2003) 248-254
9. Abu Zitar R.A. Optimum gripper using ant colony intelligence. Industrial Robot: An International Journal 32 1 (2005) 17-23
10. Abu Zitar R., and Al-Fahed Nuseirat A.M. An evolutionary based method for solving the nonlinear gripper problem. International Journal of Applied Science and Engineering 2 3 (2004) 211-221
11. Ramesh Kolluru, Valavanis P., Kimon, Smith A., Stanford, and Nikos Tsourveloudis. Design fundamentals of a reconfigurable robotic gripper system. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 30 2 (2000) 181-187
12. Sdahl M., and Kuhlenkoetter B. CAGD-computer aided gripper design for a flexible gripping system. International Journal of Advanced Robotic Systems 2 2 (2005) 135-138
13. Zhang M.T., and Goldberg K. Internet-based CAD tool for design of gripper jaws. ASME Journal of Computing and Information Science in Engineering 4 1 (2004) 43-48
14. Yan G.-Z., Wu T., and Xu K.-J. Estimation of wrist force/torque for robot gripper using neural network. Proceedings of IEEE International Conference on Robotics and Biomimetics (2006) 1450-1453
15. Al-Gallaf E.A. Multi-fingered robot hand optimal task force distribution neural inverse kinematics approach. Robotics and Autonomous Systems 54 (2006) 34-51
16. Andrzej Osyczka, and Stanislaw Krenich. New methods for multicriteria design optimization using evolutionary algorithms. Workshop: Optimal Design Laboratories de Mécanique des Solides Ecole Polytechnique Palaiseau. France, November (2003) 26-28
17. Rajan Filomeno Coelho, Multicriteria optimization with expert rules for mechanical design, Dissertation, Université Libre De Bruxelles Faculté Des Sciences Appliquées, 2004.
18. Goldberg D.E. Genetic Algorithms in Search, Optimization, and Machine Learning (1984), Addison-Wesley, Reading, MA
19. Kalyanmoy Deb, Amrit Pratap, Subrajyoti Moitra, Mechanical Component Design for Multiple Objectives using Elitist Non-Dominated Sorting GA, Kanpur Genetic Algorithms Laboratory (KanGAL), Indian Institute of Technology, Kanpur, India, Technical Report No. 200002.
20. B.V. Babu, B. Anbarasu, Multi-objective differential evolution (MODE): an evolutionary algorithm for multi-objective optimization problems (MOOPs), http://discovery.bitspilani.ac.in/discipline/chemical/BVb/publications/htmlPrice.
21. Tan K.C., Lee T.H., and Khor E.F. Evolutionary algorithms for multi-objective optimization: performance assessments and computations. Artificial Intelligence Review 17 (2002) 253-290