Abstract
Evolutionary Robotics (ER) makes use of evolutionary algorithms to evolve controllers and morphologies of robots. Despite successful demonstrations in laboratory experiments, ER has not been widely adopted by industry as means of robot design. A possible reason for this is that current ER approaches ignore issues that are important when designing robots for practical use. For example, the availability and cost of components used for robot construction should be considered. A robot designed by the ER process may require specialised custom components to be built to support the physical functioning of the design, if the components selected by an ER process are not widely available. Alternatively, the ER designed robot may be too expensive to be constructed. This paper demonstrates that standard off-the-shelf components can be used by the ER process to design a robot. A robot arm is used as a sample problem, which is successfully optimised to use components from a fixed list while minimising cost.
The financial assistance of the National Research Foundation (NRF) towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the authors and are not necessarily to be attributed to the NRF.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Christensen, D.J., Schultz, U.P., Stoy, K.: A distributed and morphology-independent strategy for adaptive locomotion in self-reconfigurable modular robots. Robot. Auton. Syst. 61(9), 1021–1035 (2013). Sept
Faiña, A., Bellas, F., Orjales, F., Souto, D., Duro, R.: An evolution friendly modular architecture to produce feasible robots. Robot. Auton. Syst. 63, 195–205 (2015). Jan
Funes, P., Pollack, J.: Computer evolution of buildable objects for evolutionary design by computer, pp. 1–20 (1999)
Harvey, I., Husbands, P., Cliff, D., Thompson, A., Jakobi, N.: Evolutionary robotics: the Sussex approach 20, 205–224 (1997)
HobbyKing. Servos and Parts: http://www.hobbyking.com/hobbyking/store/ __189__189__ Servos_Parts.html?idCategory=189&pc= (2015)
Hornby, G., Lipson, H., Pollack, J.: Generative representations for the automated design of modular physical robots. IEEE Trans. Robot. Autom. 19(4), 703–719 (2003). Aug
Lipson, H.: Evolutionary robotics and open-ended design automation. Biomimetics 17(9), 129–155 (2005)
Lipson, H., Pollack, J.B.: Automatic design and manufacture of robotic lifeforms. Nature 406(6799), 974–978 (2000)
Panda, S., Mishra, D., Biswal, B.: Revolute manipulator workspace optimization: a comparative study. Appl. Soft Comput. 13(2), 899–910 (2013). Feb
Patel, S., Sobh, T.: Task based synthesis of serial manipulators. J. Adv. Res. (2015)
Rout, B., Mittal, R.: Optimal manipulator parameter tolerance selection using evolutionary optimization technique. Eng. Appl. Artif. Intell. 21(4), 509–524 (2008). June
Stan, S., Balan, R., Maties, V.: Multi-objective design optimization of mini parallel robots using genetic algorithms. Ind. Electron. 2007 ISIE (1995), 2173–2178 (2007)
Toz, M., Kucuk, S.: Dexterous workspace optimization of an asymmetric six-degree of freedom Stewart Gough platform type manipulator. Robot. Auton. Syst. 61(12), 1516–1528 (2013). Dec
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Louwrens, M.W., du Plessis, M.C., Greyling, J.H. (2016). Using Standard Components in Evolutionary Robotics to Produce an Inexpensive Robot Arm. In: Pillay, N., Engelbrecht, A., Abraham, A., du Plessis, M., Snášel, V., Muda, A. (eds) Advances in Nature and Biologically Inspired Computing. Advances in Intelligent Systems and Computing, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-319-27400-3_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-27400-3_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27399-0
Online ISBN: 978-3-319-27400-3
eBook Packages: Computer ScienceComputer Science (R0)