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A Motion Planner for Car-Like Robots Based on Rapidly-Exploring Random Trees

  • Rômulo Ramos Radaelli
  • Claudine Badue
  • Michael André Gonçalves
  • Thiago Oliveira-Santos
  • Alberto F. De Souza
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8864)

Abstract

We propose a motion planner for car-like robots based on the rapidly-exploring random tree (RRT) method. Our motion planner was designed especially for cars driving on roads. So, its goal is to build trajectories from the car’s initial state to the goal state in real time, which stay within the desired lane bounds and keep a safe distance from obstacles. For that, our motion planner combines several variants of the standard RRT algorithm. We evaluated the performance of our motion planner using an experimental robotic platform based on a Ford Escape Hybrid. Our experimental results showed that our motion planner is capable of planning trajectories in real time, which follow the lane and avoid collision with obstacles.

Keywords

Motion planning Car-like robots Rapidly-exploring random trees 

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References

  1. 1.
    Dolgov, D., Thrun, S., Montemerlo, M., Diebel, J.: Path Planning for Autonomous Driving in Unknown Environments. In: Khatib, O., Kumar, V., Pappas, G.J. (eds.) Experimental Robotics. STAR, vol. 54, pp. 55–64. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  2. 2.
    Urmson, C., Anhalt, J., Bagnel, D., Baker, C., Bittner, R., Clark, M., Dolan, J., Duggins, D., Gittleman, M., Harbaugh, S., Wolkowicki, Z., Ziglar, J., Bae, H., Brown, T., Demitrish, D., Sadekar, V., Zhang, W., Struble, J., Taylor, M., Darms, M., Ferguson, D.: Autonomous driving in urban environments: Boss and the urban challenge. Journal of Field Robotics: Special Issues on the 2007 DARPA Urban Challenge 25(8), 425–466 (2008)Google Scholar
  3. 3.
    LaValle, S.: Rapidly-exploring random trees: a new tool for path planning. Technical Report, Iowa State University (1998)Google Scholar
  4. 4.
    Kuwata, Y., Fiore, G., Teo, J., Frazzoli, E., How, J.: Motion planning for urban driving using RRT. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.1681–1686 (2008)Google Scholar
  5. 5.
    Cheng, P., LaValle, S.: Resolution complete rapidly-exploring. In: IEEE International Conference on Robotics and Automation, pp. 267–272 (2002)Google Scholar
  6. 6.
    Kuffner, J., LaValle, S.: RRT-connect: an efficient approach to single-query path planning. In: IEEE International Conference on Robotics and Automation, pp. 995–1001 (2000)Google Scholar
  7. 7.
    Powers, M., Wooden, D., Egerstedt, M., Christensen, H., Balch, T.: The sting racing team’s entry to the urban challenge. In: Rouff, C., Hinchey, M. (eds.) Experience from the DARPA Urban Challenge, pp. 43–66. Springer, London (2012)CrossRefGoogle Scholar
  8. 8.
    Frazzoli, E., Dahleh, M., Feron, E.: Real-time motion planning for agile autonomous vehicles. In: American Control Conference, pp. 43–49 (2001)Google Scholar
  9. 9.
    Bekris, K., Kavraki, L.: Greedy but safe replanning under kinodynamic constraints. In: IEEE International Conference on Robotics and Automation, pp. 704–710 (2007)Google Scholar
  10. 10.
    LaValle, S., Kuffner, J.: Rapidly-exploring random trees: progress and prospects. In: Donald, B., Lynch, K., Rus, D. (eds.) Algorithmic and Computational Robotics: New Directions, pp. 293–308. A. K. Peters, Welessley (2001)Google Scholar
  11. 11.
    Macek, K., Becked, M., Siegwart, R.: Motion planning for car-like vehicles in dynamic urban scenarios. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4375–4380 (2006)Google Scholar
  12. 12.
    Franchi, A., Freda, L., Oriolo, G., Vendittelli, M.: A Randomized Strategy for Cooperative Robot Exploration. In: International Conference on Robotics and Automation, pp. 768–774 (2007)Google Scholar
  13. 13.
    Chang-an, L., Jin-gang, C., Guo-dong, L., Chun-Yang, L.: Mobile robot path planning based on an improved rapidly-exploring random tree in unknown environment. In: International Conference on Automation and Logistics, pp. 2375–2379 (2008)Google Scholar
  14. 14.
    LaValle, S.M., Kuffner, J.J..: Randomized kinodynamic planning. In: IEEE International Conference on Robotics and Automation, pp. 473–479 (1999)Google Scholar
  15. 15.
    Ju, T., Liu, S., Yang, J., Sun, D.: Rapidly exploring random tree algorithm-based path planning for robot-aided optical manipulation of biological cells. Transactions on Automation Science and Engineering 11(3), 649–657 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Rômulo Ramos Radaelli
    • 1
  • Claudine Badue
    • 1
  • Michael André Gonçalves
    • 1
  • Thiago Oliveira-Santos
    • 1
  • Alberto F. De Souza
    • 1
  1. 1.Departamento de InformáticaUniversidade Federal do Espírito SantoVitóriaBrazil

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