Use of relaxation methods in sampling-based algorithms for optimal motion planning

@article{Arslan2013UseOR,
  title={Use of relaxation methods in sampling-based algorithms for optimal motion planning},
  author={Oktay Arslan and Panagiotis Tsiotras},
  journal={2013 IEEE International Conference on Robotics and Automation},
  year={2013},
  pages={2421-2428}
}
Several variants of incremental sampling-based algorithms have been recently proposed in order to optimally solve motion planning problems. Popular examples include the RRT* and the PRM* algorithms. These algorithms are asymptotically optimal and thus provide high quality solutions. However, the convergence rate to the optimal solution may still be slow. Borrowing from ideas used in the well-known LPA* algorithm, in this paper we present a new incremental sampling-based motion planning… CONTINUE READING
Highly Cited
This paper has 82 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 56 extracted citations

83 Citations

010203020142015201620172018
Citations per Year
Semantic Scholar estimates that this publication has 83 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 14 references

An efficient sampling-based algorithm for motion planning with optimality guarantees

  • O. Arslan, P. Tsiotras
  • Technical Report DCSL- 12-09-010, Georgia…
  • 2012
1 Excerpt

D∗ lite

  • S. Koenig, M. Likhachev
  • Eighteenth National Conference on Artificial…
  • 2002
1 Excerpt

Rapidly-exploring random trees: Progress and prospects

  • S. M. LaValle, J. J. Kuffner, Jr.
  • New Directions in Algorithmic and Computational…
  • 2001
1 Excerpt

Similar Papers

Loading similar papers…