Autonomously Traversing Obstacles - Metrics for Path Planning of Reconfigurable Robots on Rough Terrain

Michael Brunner, Bernd Brüeggemann, Dirk Schulz

2012

Abstract

The fixed chassis design of commonly employed mobile robots restricts their application to fairly flat environments, as the wheel diameters or the track heights impose hard limits on their mobility. Unstructured outdoor and urban environments alike comprehend many different invincible obstacles for most of those systems, like stairs, boulders or rubble. However, there are mobile robots with reconfigurable chassis providing a higher degree of mobility and enabling them to overcome such obstacles. Yet, current planning algorithms rarely exploit those enhanced capabilities, limiting these systems to the same environments as the fixed chassis robots. This paper focuses on the metrics used by our motion planner. The employment of a two-stage planning approach allows us to use different cost functions for the initial path search and the detailed motion planning step. The purpose of the initial search is to quickly find a fast environment-driven path to the goal. Hence, it uses fast computable heuristics to assess the drivability, i.e. a risk quantification and the utmost operation limits of the robot model. The detailed planning step determines the desired robot configurations. For this purpose, we consider the actuator controls, the system’s stability, an estimate of the traction, and the driving speed in addition to the quantities used in the first stage. We present experiments to illustrate the influence of the safety weights and real world experiments which prove the validity and feasibility of the metrics used by our motion planning algorithm.

References

  1. Dornhege, C. and Kleiner, A. (2007). Behavior maps for online planning of obstacle negotiation and climbing on rough terrain. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  2. Garcia, E., Estremera, J., and de Santos, P. G. (2002). A Comparative Study of Stability Margins for Walking Machines. Robotica, 20:595-606.
  3. Hirose, S., Tsukagoshi, H., and Yoneda, K. (2001). Normalized Energy Stability Margin and its Contour of Walking Vehicles on Rough Terrain. In IEEE International Conference on Robotics & Automation (ICRA).
  4. Howard, A., Seraji, H., and Tunstel, E. (2001). A rulebased fuzzy traversability index for mobile robot navigation. In IEEE International Conference on Robotics and Automation (ICRA).
  5. Howard, T. M. and Kelly, A. (2007). Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots. International Journal of Robotics Research, 26(2):141-166.
  6. Iagnemma, K. and Dubowsky, S. (2004). Mobile Robots in Rough Terrain - Estimation, Motion Planning, and Control with Application to Planetary Rovers, chapter Rough Terrain Motion Planning, pages 51-79. Springer Tracts in Advanced Robotics.
  7. Iagnemma, K., Kang, S., Shibly, H., and Dubowsky, S. (2004). Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers. IEEE Transactions on Robotics, 20:921 - 927.
  8. Jacoff, A. S., Downs, A. J., Virts, A. M., and Messina, E. R. (2008). Stepfield Pallets: Repeatable Terrain for Evaluating Robot Mobility. In Performance Metrics for Intelligent Systems (PerMIS) Workshop.
  9. Magid, E., Ozawa, K., Tsubouchi, T., Koyanagi, E., and Yoshida, T. (2008). Rescue Robot Navigation: Static Stability Estimation in Random Step Environment. In Carpin, S., Noda, I., Pagello, E., Reggiani, M., and von Stryk, O., editors, Simulation, Modeling, and Programming for Autonomous Robots, volume 5325 of Lecture Notes in Computer Science, pages 305-316. Springer Berlin / Heidelberg.
  10. Messuri, D. A. (1985). Optimization of the locomotion of a legged vehicle with respect to maneuverability. PhD thesis, Ohio State University.
  11. Miro, J., Dumonteil, G., Beck, C., and Dissanayake, G. (2010). A kyno-dynamic metric to plan stable paths over uneven terrain. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  12. Molino, V., Madhavan, R., Messina, E., Downs, A., Balakirsky, S., and Jacoff, A. (2007). Traversability metrics for rough terrain applied to repeatable test methods. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  13. Rusu, R. B., Sundaresan, A., Morisset, B., Hauser, K., Agrawal, M., Latombe, J.-C., and Beetz, M. (2009). Leaving Flatland: Efficient Real-Time ThreeDimensional Perception and Motion Planning. Journal of Field Robotics, 26:841-862.
  14. Seraji, H. (1999). Traversability index: a new concept for planetary rovers. In IEEE International Conference on Robotics and Automation (ICRA).
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Paper Citation


in Harvard Style

Brunner M., Brüeggemann B. and Schulz D. (2012). Autonomously Traversing Obstacles - Metrics for Path Planning of Reconfigurable Robots on Rough Terrain . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8565-22-8, pages 58-69. DOI: 10.5220/0004033400580069


in Bibtex Style

@conference{icinco12,
author={Michael Brunner and Bernd Brüeggemann and Dirk Schulz},
title={Autonomously Traversing Obstacles - Metrics for Path Planning of Reconfigurable Robots on Rough Terrain},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2012},
pages={58-69},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004033400580069},
isbn={978-989-8565-22-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Autonomously Traversing Obstacles - Metrics for Path Planning of Reconfigurable Robots on Rough Terrain
SN - 978-989-8565-22-8
AU - Brunner M.
AU - Brüeggemann B.
AU - Schulz D.
PY - 2012
SP - 58
EP - 69
DO - 10.5220/0004033400580069