Multi-goal Trajectory Planning with Motion Primitives for Hexapod Walking Robot

Petr Vaněk, Jan Faigl, Diar Masri

2014

Abstract

This paper presents our early results on multi-goal trajectory planning with motion primitives for a hexapod walking robot. We propose to use an on-line unsupervised learning method to simultaneously find a solution of the underlying traveling salesman problem together with particular trajectories between the goals. Using this technique, we avoid pre-computation of all possible trajectories between the goals for a graph based heuristic solvers for the traveling salesman problem. The proposed approach utilizes principles of self-organizing map to steer the randomized sampling of configuration space in promising areas regarding the multi-goal trajectory. The presented results indicate the proposed steering mechanism provides a feasible multi-goal trajectory in a less number of samples than an approach based on a priori known sequence of the goals visits.

References

  1. Applegate, D., Bixby, R., Chvátal, V., and Cook, W. (2003). CONCORDE TSP Solver. [cited 28 Feb 2012].
  2. Applegate, D. L., Bixby, R. E., Chvatal, V., and Cook, W. J. (2007). The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics). Princeton University Press.
  3. Bevly, D., Farritor, S., and Dubowsky, S. (2000). Action module planning and its application to an experimental climbing robot. In ICRA, pages 4009-4014.
  4. Englot, B. and Hover, F. (2011). Multi-goal feasible path planning using ant colony optimization. In ICRA, pages 2255-2260.
  5. Faigl, J., Kulich, M., Vonásek, V., and Pr?euc?il, L. (2011). An Application of Self-Organizing Map in the nonEuclidean Traveling Salesman Problem. Neurocomputing, 74(5):671-679.
  6. Karaman, S. and Frazzoli, E. (2011). Sampling-based algorithms for optimal motion planning. Int. J. Rob. Res., 30(7):846-894.
  7. Lavalle, S. M. and Kuffner, J. J. (2001). Rapidly-Exploring Random Trees: Progress and Prospects. Algorithmic and Computational Robotics: New Directions, pages 293-308.
  8. Pivtoraiko, M. and Kelly, A. (2005). Efficient constrained path planning via search in state lattices. In Proceedings of the 8th International Symposium on Artificial Intelligence, Robotics and Automation in Space.
  9. Reif, J. H. (1979). Complexity of the mover's problem and generalizations. In SFCS 7879: Proceedings of the 20th Annual Symposium on Foundations of Computer Science, pages 421-427. IEEE Computer Society.
  10. Saha, M., Roughgarden, T., Latombe, J.-C., and SánchezAnte, G. (2006). Planning Tours of Robotic Arms among Partitioned Goals. Int. J. Rob. Res., 25(3):207- 223.
  11. Vonásek, V., Saska, M., Kosnar, K., and Preucil, L. (2013). Global motion planning for modular robots with local motion primitives. In ICRA, pages 2465-2470.
  12. Yamakawa, T., Horio, K., and Hoshino, M. (2006). SelfOrganizing Map with Input Data Represented as Graph. In Neural Information Processing, pages 907- 914. Springer Berlin / Heidelberg.
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Paper Citation


in Harvard Style

Vaněk P., Faigl J. and Masri D. (2014). Multi-goal Trajectory Planning with Motion Primitives for Hexapod Walking Robot . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-040-6, pages 599-604. DOI: 10.5220/0005118405990604


in Bibtex Style

@conference{icinco14,
author={Petr Vaněk and Jan Faigl and Diar Masri},
title={Multi-goal Trajectory Planning with Motion Primitives for Hexapod Walking Robot},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2014},
pages={599-604},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005118405990604},
isbn={978-989-758-040-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Multi-goal Trajectory Planning with Motion Primitives for Hexapod Walking Robot
SN - 978-989-758-040-6
AU - Vaněk P.
AU - Faigl J.
AU - Masri D.
PY - 2014
SP - 599
EP - 604
DO - 10.5220/0005118405990604