Optimal Path Planning in Complex Cost Spaces With Sampling-Based Algorithms

@article{Devaurs2016OptimalPP,
  title={Optimal Path Planning in Complex Cost Spaces With Sampling-Based Algorithms},
  author={Didier Devaurs and Thierry Sim{\'e}on and Juan Cort{\'e}s},
  journal={IEEE Transactions on Automation Science and Engineering},
  year={2016},
  volume={13},
  pages={415-424}
}
Sampling-based algorithms for path planning, such as the Rapidly-exploring Random Tree (RRT), have achieved great success, thanks to their ability to efficiently solve complex high-dimensional problems. However, standard versions of these algorithms cannot guarantee optimality or even high-quality for the produced paths. In recent years, variants of these methods, such as T-RRT, have been proposed to deal with cost spaces: by taking configuration-cost functions into account during the… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 24 references

Enhancing the transition-based RRT to deal with complex cost spaces

2013 IEEE International Conference on Robotics and Automation • 2013

Addressing cost-space chasms in manipulation planning

2011 IEEE International Conference on Robotics and Automation • 2011

Anytime Motion Planning using the RRT*

2011 IEEE International Conference on Robotics and Automation • 2011

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