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Provably safe navigation for mobile robots with limited field-of-views in dynamic environments

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Abstract

This paper addresses the problem of navigating in a provably safe manner a mobile robot with a limited field-of-view placed in a unknown dynamic environment. In such a situation, absolute motion safety (in the sense that no collision will ever take place whatever happens in the environment) is impossible to guarantee in general. It is therefore settled for a weaker level of motion safety dubbed passive motion safety: it guarantees that, if a collision takes place, the robot will be at rest.

The primary contribution of this paper is the concept of Braking Inevitable Collision States (ICS), i.e. a version of the ICS corresponding to passive motion safety. Braking ICS are defined as states such that, whatever the future braking trajectory followed by the robot, a collision occurs before it is at rest. Passive motion safety is obtained by avoiding Braking ICS at all times.

It is shown that Braking ICS verify properties that allow the design of an efficient Braking ICS-Checking algorithm, i.e. an algorithm that determines whether a given state is a Braking ICS or not.

To validate the Braking ICS concept and demonstrate its usefulness, the Braking ICS-Checking algorithm is integrated in a reactive navigation scheme called PassAvoid. It is formally established that PassAvoid is provably passively safe in the sense that it is guaranteed that the robot will always stay away from Braking ICS no matter what happens in the environment.

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References

  1. Althoff, D., Althoff, M., Wollherr, D., & Buss, M. (2010). Probabilistic collision state checker for crowded environments. In IEEE int. conf. on robotics and automation, Anchorage, USA. doi:10.1109/ROBOT.2010.5509369.

  2. Bautin, A., Martinez-Gomez, L., & Fraichard, T. (2010). Inevitable collision states, a probabilistic perspective. In IEEE int. conf. robotics and automation, Anchorage, USA. doi:10.1109/ROBOT.2010.5509233.

  3. Bekris, K., & Kavraki, L. (2010). Greedy but safe replanning under kinodynamic constraints. In IEEE int. conf. robotics and automation, Rome, Italy. doi:10.1109/ROBOT.2007.363069.

  4. Bekris, K., Tsianos, K., & Kavraki, L. (2009). Safe and distributed kinodynamic replanning for vehicular networks. Mobile Networks and Applications, 14(3). doi:10.1007/s11036-009-0152-y.

  5. Chan, N., Zucker, M., & Kuffner, J. (2007). Towards safe motion planning for dynamic systems using regions of inevitable collision. In Collision-free motion planning for dynamic systems workshop, Rome, Italy.

  6. Chung, W., Kim, S., Choi, M., Choi, J., Kim, H., Moon, C., & Song, J. (2009). Safe navigation of a mobile robot considering visibility of environment. IEEE Transactions of Industrial Electronics, 56(10). doi:10.1109/TIE.2009.2025293.

  7. Ferguson, D., Howard, T., & Likhachev, M. (2008). Motion planning in urban environments. Journal of Field Robotics, 25(11–12). doi:10.1002/rob.20265.

  8. Fiorini, P., & Shiller, Z. (1998). Motion planning in dynamic environments using velocity obstacles. International Journal of Robotics Research, 17(7). doi:10.1177/027836499801700706.

  9. Fletcher, L., Teller, S., Olson, E., Moore, D., Kuwata, Y., How, J., Leonard, J., Miller, I., Campbell, M., Huttenlocher, D., Nathan, A., & Kline, F. R. (2008). The MIT—Cornell collision and why it happened. International Journal of Field Robotics, 25(10).

  10. Fox, D., Burgard, W., & Thrun, S. (1997). The dynamic window approach to collision avoidance. IEEE Robotics and Automation Magazine 4(1).

  11. Fraichard, T. (2007). A short paper about motion safety. In IEEE Int. conf. robotics and automation, Roma, Italy.

  12. Fraichard, T., & Asama, H. (2004). Inevitable collision states: a step towards safer robots? Advanced Robotics, 18(10).

  13. Frazzoli, E., Feron, E., & Dahleh, M. (2002). Real-time motion planning for agile autonomous vehicle. Journal of Guidance, Control, and Dynamics, 25(1).

  14. Hsu, D., Kindel, R., Latombe, J. C., & Rock, S. (2002). Randomized kinodynamic motion planning with moving obstacles. International Journal of Robotics Research, 21(3).

  15. Kalisiak, M., & van de Panne, M. (2007). Faster motion planning using learned local viability models. In IEEE int. conf. robotics and automation, Roma, Italy.

  16. Kant, K., & Zucker, S. (1986) Toward efficient trajectory planning: the path-velocity decomposition. International Journal of Robotics Research, 5(3).

  17. Kohout, R., Hendler, J., & Musliner, D. (1996). Guaranteeing safety in spatially situated agents. In AAAI nat. conf. artificial intelligence, Portland.

  18. Kuwata, Y., Karaman, S., Teo, J., Frazzoli, E., How, J., & Fiore, G. (2009). Real-time motion planning with applications to autonomous urban driving. IEEE Transations on Control Systems Technology, 17(5). doi:10.1109/TCST.2008.2012116.

  19. Lalish, E., & Morgansen, K. (2008). Decentralized reactive collision avoidance for multivehicle systems. In IEEE conf. decision and control, Cancun.

  20. LaValle, S. (2006). Planning algorithms. Cambridge: Cambridge University Press.

  21. LaValle, S., & Kuffner, J. (1999). Randomized kinodynamic planning. In IEEE int. conf. robotics and automation, Detroit, MI, USA.

  22. Lumelsky, V., & Tiwari, S. (1994). Velocity bounds for motion planning in the presence of moving planar obstacles. In IEEE-RSJ int. conf. intelligent robots and systems, München, Germany.

  23. Macek, K., Vasquez-Govea, D., Fraichard, T., & Siegwart, R. (2009). Towards safe vehicle navigation in dynamic urban scenarios. Automatika, 50(3–4).

  24. Madhava Krishna, K., Alami, R., & Simeon, T. (2006). Safe proactive plans and their execution. Robotics and Autonomous Systems, 54(3).

  25. Martinez-Gomez, L., & Fraichard, T. (2008). An efficient and generic 2D inevitable collision state-checker. In IEEE-RSJ int. conf. intelligent robots and systems, Nice, France.

  26. Pallottino, L., Scordio, V., Bicchi, A., & Frazzoli, E. (2007) Decentralized cooperative policy for conflict resolution in multivehicle systems. IEEE Transations on Robotics, 23(6). doi:10.1109/TRO.2007.909810.

  27. Petti, S., & Fraichard, T. (2005). Safe motion planning in dynamic environments. In Proc. of the IEEE-RSJ int. conf. on intelligent robots and systems, Edmonton, Canada. doi:10.1109/IROS.2005.1545549.

  28. Reif, J., & Sharir, M. (1985). Motion planning in the presence of moving obstacles. In IEEE int. symp. foundations of computer science, Portland, USA.

  29. Sadou, M., Polotski, V., & Cohen, P. (2004). Occlusion in obstacle detection for safe navigation. In IEEE intelligent vehicles symp., Parma, Italy. doi:10.1109/IVS.2004.1336472.

  30. Seder, M., & Petrovic, I. (2007). Dynamic window based approach to mobile robot motion control in the presence of moving obstacles. In IEEE int. conf. robotics and automation, Roma, Italy.

  31. Van den Berg, J., & Overmars, M. (2008). Planning time-minimal safe paths amidst unpredictably moving obstacles. International Journal of Robotics Research, 27(11–12). doi:10.1177/0278364908097581.

  32. Van den Berg, J., Lin, M., & Manocha, D. (2008). Reciprocal velocity obstacles for real-time multi-agent navigation. In IEEE int. conf. robotics and automation, Pasadena, US. doi:10.1109/ROBOT.2008.4543489.

  33. Vatcha, R., & Xiao, L. (2008). Perceived CT-space for motion planning in unknown and unpredictable environments. In Workshop on algorithmic foundations of robotics, Guanajuato, Mexico.

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Author information

Correspondence to Thierry Fraichard.

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Bouraine, S., Fraichard, T. & Salhi, H. Provably safe navigation for mobile robots with limited field-of-views in dynamic environments. Auton Robot 32, 267–283 (2012). https://doi.org/10.1007/s10514-011-9258-8

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Keywords

  • Mobile robots
  • Dynamic environments
  • Autonomous navigation
  • Motion safety
  • Collision avoidance
  • Inevitable collision states