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New perspective on sampling-based motion planning via random geometric graphs.

, , and . Int. J. Robotics Res., (2018)

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Efficient high-quality motion planning by fast all-pairs r-nearest-neighbors., , and . CoRR, (2014)An Efficient Algorithm for Computing High-Quality Paths amid Polygonal Obstacles., , and . ACM Trans. Algorithms, 14 (4): 46:1-46:21 (2018)Lazy Receding Horizon A* for Efficient Path Planning in Graphs with Expensive-to-Evaluate Edges., , and . ICAPS, page 476-484. AAAI Press, (2018)Minimizing Task Space Frechet Error via Efficient Incremental Graph Search., , and . CoRR, (2017)Planning, Learning and Reasoning Framework for Robot Truck Unloading., , , , , and . ICRA, page 5011-5017. IEEE, (2020)Simple and efficient bi-objective search algorithms via fast dominance checks., , , , , , and . Artif. Intell., (2023)Densification strategies for anytime motion planning over large dense roadmaps., , , and . ICRA, page 3770-3777. IEEE, (2017)Optimal motion planning for a tethered robot: Efficient preprocessing for fast shortest paths queries., and . ICRA, page 4161-4166. IEEE, (2015)Multi-Agent Terraforming: Efficient Multi-Agent Path Finding via Environment Manipulation., , and . CoRR, (2022)Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation., , , and . ICRA, page 12645-12651. IEEE, (2023)