HIERARCHICAL PROBABILISTIC ESTIMATION OF ROBOT REACHABLE WORKSPACE

Jing Yang, Patrick Dymond, Michael Jenkin

2009

Abstract

Estimating a robot’s reachable workspace is a fundamental problem in robotics. For simple kinematic chains within an empty environment this computation can be relatively straightforward. For mobile kinematic structures and cluttered environments, the problem becomes more challenging. An efficient probabilistic method for workspace estimation is developed by applying a hierarchical strategy and developing extensions to a probabilistic motion planner. Rather than treating each of the degrees of freedom (DOFs) ‘equally’, a hierarchical representation is used to maximize the volume of the robot’s workspace that is identified as reachable for each probe of the environment. Experiments with a simulated mobile manipulator demonstrate that the hierarchical approach is an effective alternative to the use of an estimation process based on the use of a traditional probabilistic planner.

References

  1. Alameldin, T., Badler, N. I., and Sobh, T. (1990). An adaptive and efficient system for computing the 3-d reachable workspace. In IEEE International Conference on Systems Engineering, pages 503-506.
  2. Badescu, M. and Mavroidis, C. (2004). New performance indices and workspace analysis of reconfigurable hyper-redundant robotic arms. The International Journal of Robotics Research, 23:643-659.
  3. Canny, J. F. (1988). The Complexity of Robot Motion Planning. MIT Press, Cambridge, MA.
  4. Horsch, T., Schwarz, F., and Tolle, H. (1994). Motion planning for many degrees of freedom - random reflections at c-space obstacles. In Proceedings of IEEE International Conference on Robotics and Automation (ICRA 7894), pages 3318-3323.
  5. Hsu, M.-S. and Kohli, D. (1987). Boundary surfaces and accessibility regions for regional structures of manipulators. Mechanism and Machine Theory, 22:277-289.
  6. Kavraki, L. E., Svestka, P., Latombe, J.-C., and Overmars, M. (1996). Probabilistic roadmaps for path planning in high dimensional configuration spaces. IEEE Transactions on Robotics and Automation, 12(4):566- 580.
  7. Kumar, A. (1980). Characterization of Manipulator Geometry. PhD thesis, University of Houston.
  8. Latombe, J.-C. (1991). Robot Motion Planning. Cluwer.
  9. Lenarcic, J. and Umek, A. (1994). Simple model of human arm reachable workspace. IEEE Transactions on Systems, Man and Cybernetics, 24(8):1239-1246.
  10. Morecki, A. and Knapczyk, J. (1999). Basics of Robotics: Theory and Components of Manipulators and Robots. SpringerWienNewYork.
  11. Yang, J., Dymond, P., and Jenkin, M. (2008). Accessibility assessment via workspace estimation. International Journal of Smart Home, 3:73-90.
  12. Zacharias, F., Borst, C., and Hirzinger, G. (2007). Capturing robot workspace structure: representing robot capabilities. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3229-3236.
Download


Paper Citation


in Harvard Style

Yang J., Dymond P. and Jenkin M. (2009). HIERARCHICAL PROBABILISTIC ESTIMATION OF ROBOT REACHABLE WORKSPACE . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-674-000-9, pages 60-66. DOI: 10.5220/0002205600600066


in Bibtex Style

@conference{icinco09,
author={Jing Yang and Patrick Dymond and Michael Jenkin},
title={HIERARCHICAL PROBABILISTIC ESTIMATION OF ROBOT REACHABLE WORKSPACE},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2009},
pages={60-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002205600600066},
isbn={978-989-674-000-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - HIERARCHICAL PROBABILISTIC ESTIMATION OF ROBOT REACHABLE WORKSPACE
SN - 978-989-674-000-9
AU - Yang J.
AU - Dymond P.
AU - Jenkin M.
PY - 2009
SP - 60
EP - 66
DO - 10.5220/0002205600600066