ON EDGE-LAZY RRT COLLISION CHECKING IN SAMPLING-BASED MOTION PLANNING

Lorenzo Ricciardi Celsi and Michela Ricciardi Celsi

References

  1. [1] L. Kavraki and S. LaValle, Motion planning, in B. Sicilianoand O. Khatib (eds.), Springer Handbook of Robotics (Berlin,Heidelberg: Springer, 2008).
  2. [2] L. Wang and C. Luo, A hybrid genetic tabu search algorithmfor mobile robot to solve AS/RS path planning, InternationalJournal of Robotics and Automation, 206, 2018.
  3. [3] B. Hao and Z. Yan, Recovery path planning for an agriculturalmobile robot by Dubins-RRT algorithm, International Journalof Robotics and Automation, 206, 2018.
  4. [4] Y. Liu, M. Cong, H. Dong, and D. Liu, Reinforcement learningand ega-based trajectory planning for dual robots, Interna-tional Journal of Robotics and Automation, 206, 2018.
  5. [5] S. Karaman and E. Frazzoli, Sampling-based algorithms foroptimal motion planning, International Journal of RoboticsResearch, 30(7), 2011, 846–894.
  6. [6] S. LaValle and J. Kuffner, Rapidly-exploring random trees:Progress and prospects, in B. Donald, K. Lynch, and D.Rus (eds.), Algorithmic and Computational Robotics: NewDirections (New York: CRC Press, 2000), 293–308.
  7. [7] R. Seif and M. Oskoei, Motion robot path planning by RRTin dynamic environments, International Journal of IntelligentSystems and Applications, 7(5), 2015, 24–30.
  8. [8] K. Hauser, Lazy collision checking in asymptotically-optimalmotion planning, Proc. of IEEE Int. Conf. on Robotics andAutomation, Seattle, Washington, 2015, 2951–2957.
  9. [9] S. Sharma, G. Kraetzschmar, C. Scheurer, and R. Bischoff,Unified closed form inverse kinematics for the kuka youbot,ROBOTIK, Munich, Germany, 2012.
  10. [10] C. Schindelhauer, Minimal energy path planning for wirelessrobots, Mobile Networks and Applications, 14, 2009, 309–321.

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