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Sampling-based motion planners have experienced much success due to their ability to efficiently and evenly explore the state space.
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M. Zucker, J. Kuffner, and J. A. Bagnell, “Adaptive workspace biasing for sampling-based planners,” in Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on
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J. D. Gammell, S. S. Srinivasa, and T. D. Barfoot, “Informed rrt*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,” in Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on
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T. Kunz, A. Thomaz, and H. Christensen, “Hierarchical rejection sampling for informed kinodynamic planning in high-dimensional spaces,” in Robotics and Automation (ICRA), 2016 IEEE International Conference on
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S. Choudhury, J. D. Gammell, T. D. Barfoot, S. S. Srinivasa, and S. Scherer, “Regionally accelerated batch informed trees (rabit*): A framework to integrate local information into optimal path planning,” in Robotics and Automation (ICRA), 2016 IEEE International Conference on
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2017
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2017
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