Skip to main content

Evolutionary design of modular robotic arms

  • O. Chocron (a1)

This paper proposes a method for task based design of modular serial robotic arms using evolutionary algorithms (EA). We introduce a 3D kinematics and a global optimization for both topology and configuration from task specifications. The search features revolute as well as prismatic joints and any number of DOF to build up a solution without using any design knowledge. A study of the evolution dynamics gives some keys to set evolution parameters that enable artificial evolution. An adapted algorithm dealing with the topology/configuration search tradeoff is proposed, descibed, and discussed. Illustrations of the algorithms results are given and conclusions are drawn from their analysis. Perspectives of this work are given, extending its reach to control and complex system design.

Corresponding author
*Corresponding author. E-mail:
Hide All
1.Fukuda, T. and Nakagawa, S., “Dynamically reconfigurable robotic system,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Philadelphia, PA, USA (1988) pp. 1581–1586.
2.Paredis, C. and Khosla, P., “A rapidly deployable manipulator system,” IEEE International Conference on Robotics and Automation (ICRA), Minneapolis, MN, USA (1996) pp. 1434–1439.
3.Yim, M., “A reconfigurable modular robot with many modes of locomotion,” Proceedings of International Conference on Advanced Mechatronics, Tokyo, Japan (1993) pp. 283–288.
4.Rus, D. and Chirikjian, G. S., “Self-reconfigurable robots,” Auton Rob 10 (1), 55 (2001).
5.Ambrose, R. O., Design, construction and demonstration of modular, reconfigurable robots Ph.D. Thesis (Austin, USA, University of Texas, 1991).
6.Chen, I. M. and Burdick, J., “Determining task optimal modular robot assembly configurations,” IEEE International Conference on Robotics and Automation (ICRA), Nagoya, Japan (May 1995) pp. 132–137.
7.Hornby, S., Lipson, H. and Pollack, J. B., “Generative representations for the automated design of modular physical robots,” IEEE Trans. Robot. Automat., 19 (4), 703719 (2003).
8.Papadimitriou, C. H. and Steiglitz, K., Combinatorial Optimization- Algorithms and Complexity (Prentice-Hall, Englewoods Cliffs, NJ, USA, 1982).
9.Arora, J. S., Elwakeil, O. A. and Chahande, A. I., “Global optimization methods for engineering applications: a review.” J. Str. Opt. 9 (3-4), 137159 (1995).
10.Shen, S. N., Chew, M. and Issa, G. F., “Kinematic structural synthesis of mechanisms using knowledge-based systems,” J. Mech. Des. 117, 96–10 (1995)].
11.Kim, J. O. and Khosla, P., “A multi-population genetic algorithm and its application to design of manipulators,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Raleigh, NC, USA (1992) pp. 279–286.
12.Paredis, C. and Khosla, P., Kinematic design of serial link manipulator from task specification. International Journal of Robotics Research, 12 (3), 274287, (1993).
13.Khwaja, A. A., Rahman, M. O. and Wagner, M. G., “Inverse kinematics of arbitrary robotic manipulators using genetic algorithms,” In: Advances in Robot Kinematics: Analysis and Control. (Lenarcic, J. and Husty, M. L., eds., (Kluwer Academic Publishers, 1998).
14.Yang, G. and Chen, I.-M.. Task-Based Optimization of Modular Robot Configurations—MDOF Approach. Mechanism and Machine Theory, 35 (4), 517540 (2000).
15.Chedmail, P. and Ramstein, E., “Robot mechanism synthesis and genetic algorithms,” IEEE International Conference on Robotics and Automation (ICRA), Minneapolis, MN, USA (April, 1996) pp. 3466–3471.
16.Pollack, J., Lipson, H., Ficici, S., Funes, P., Hornby, G. and Watson, R.. “Evolutionary techniques in physical robotics,” Proceedings of the Third International Conference on Evolvable Systems, Edinburgh, UK (April, 2000) pp. 175–186.
17.Chocron, O. and Bidaud, Ph., “Genetic design of 3d modular manipulators,” IEEE International Conference on Robotics and Automation (ICRA), Albuquerque, NM, USA (April 1997) pp. 223–228.
18.Chocron, O. and Bidaud, Ph., “Evolutionnary algorithms in kinematic design of robotic systems,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Grenoble, France (September 1997) pp. 1111–1117.
19.Chapelle, F., Chocron, O. and Bidaud, Ph., “Genetic programming for inverse kinematics problem approximation,” International Symposium on Robotics (ISR), Montreal, Canada (May 2000) pp. 5–11.
20.Sakka, S. and Chocron, O., “Optimal design, configurations and positions for a mobile manipulation task using genetic algorithms,” TENTH IEEE International Conference on Robot and Human Communication (ROMAN), Paris-Bordeaux, France (September 2001) pp. 268–273.
21.Yoshikawa, T.. Foundations of robotics: analysis and control (MIT Press Cambridge, MA, USA, 1990).
22.Goldberg, D. E., Genetic Algorithms in Search, Optimization and Machine Learning (Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, 1989).
23.Bäck, T., Evolutionary Algorithms in Theory and Practise (Oxford University Press, New York, NY, USA 1996).
24.Thornton, A. C., “Genetic algorithms versus simulated annealing: satisfaction of large sets of algebraic mechanical design constraints,” Proceedings of Artificial Intelligence in Design, Lausanne, Switzerland (August 1994) pp. 381–400.
25.Yoshida, E., Murata, S., Tomita, K., Kurokawa, H. and Kokaji, S.. Distributed formation control for a modular mechanical system. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Grenoble, France (1997) pp. 1090–1097.
26.Yim, M., Shen, W.-M., Salemi, B., Rus, D., Moll, M., Lipson, H., Klavins, E., and Chirikjian, G. S., “Modular self-reconfigurable robot systems—challenges and opportunities for the fiture,” IEEE Robot. Automat. Mag. 14 (1), 4352 (2007).
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

  • ISSN: 0263-5747
  • EISSN: 1469-8668
  • URL: /core/journals/robotica
Please enter your name
Please enter a valid email address
Who would you like to send this to? *