Abstract
We present preliminary results of a path planner for two robotic arms sharing the same workspace. Unlike many other approaches, our planner finds collision-free paths using the robot’s cartesian space as a trade-off between completeness and no workspace preprocessing. Given the high dimensionality of the search space, we use a two phase Genetic Algorithm to find a suitable path in workspaces cluttered with obstacles. Because the length of the path is unknown in advance, the planner manipulates a flexible and well crafted representation which allows the path to grow or shrink during the search process. The performance of our planner was tested on several scenarios where the only moving objects were the two robotic arms. The test scenarios force the manipulators to move through narrow spaces for which suitable and safe paths were found by the planner.
This work was supported by the UAEMex under project grant number 2570/2007U.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing, USA (1989)
Mitchel, M.: An Introduction to Genetic Algorithms. MIT Press, Boston (1998)
Latombe, J.C.: Robot Motion Planning. Kluwer Academic Publishers, Norwell (1991)
Hwang, Y.K., Ahuja, N.: Gross motion planning: A survey. ACM Computing Surveys 24(3), 219–291 (1992)
Choset, H., Lynch, K., Hutchinson, S., Kantor, G., Burgard, W., Kavraki, L.E., Thrun, S.: Principles of Robot Motion: Theory, Algorithms and Implementations. MIT Press, Boston (2005)
Canny, J.: The Complexity of Robot Motion Planning. MIT Press, Boston (1988)
Lozano-Perez, T.: Spatial planning: A configuration space approach. IEEE Transactions on Computers 32(2), 108–120 (1983)
Mazer, E., Ahuactzin, J.M., Bessiere, P.: The ariadne’s clew algorithm. Journal of Artificial Intelligence Research 9, 295–316 (1998)
Smierzchalski, R., Michalewicz, Z.: Path planning in dynamic environments. In: Innovations in Robot Mobility and Control. Studies in Computational Intelligence, vol. 8, pp. 135–153. Springer, Heidelberg (2005)
Ridao, M.A., Riquelme, J., Camacho, E.F., Toro, M.: Automatic generation of collision-free programs for multiple manipulators using evolutive algorithms. In: IEEE-IMACS 3rd World Multi-Conference on Circuits, Systems, Communications and Computers (CSCC 1999), Athenas. Computational Intelligence and Applications, pp. 239–244. World Scientific and Engineering Society Press, Singapore (1999)
Nearchou, A.C., Aspragathos, N.A.: A genetic path planning algorithm for redundant articulated robots. Robotica 15(2), 213–224 (1997)
Erderman, M., Lozano-Perez, T.: On multiple moving objects. In: Proceedings of the IEEE Conference On Robotics and Automation, San Francisco, California, USA, pp. 1419–1424 (1986)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Venegas, H.A.M., Marcial-Romero, J.R. (2009). An Evolutionary Path Planner for Multiple Robot Arms. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-01129-0_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01128-3
Online ISBN: 978-3-642-01129-0
eBook Packages: Computer ScienceComputer Science (R0)