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A defining feature of sampling-based motion planning is the reliance on an implicit representation of the state space, which is enabled by a set of probing samples.
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Janson, L., Ichter, B. & Pavone, M. (2018), ‘Deterministic sampling-based motion planning: Optimality, complexity, and performance’, International Journal of Robotics Research
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Schmerling, E., Leung, K., Vollprecht, W. & Pavone, M. (2018), ‘Multimodal probabilistic model-based planning for human-robot interaction’, IEEE International Conference on Robotics and Automation (ICRA)
2018
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