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- W4386963175 abstract "The motion planning problem of the robot is modelled as a graph search problem by discretizing states and actions and subsequently post-processing the path to correct for smoothness. The search can be done by incorporating the robot kinematics, where the sampled robot’s controls become the edges. The D* algorithm adapts the plan in case of a change of the map by reprocessing affected nodes. A node with an increased cost increases the cost of the children, propagating a raised wave (similar to lowered wave propagated by a reduced edge cost or finding a better parent). The re-planning can also be done by propagating inconsistencies using the Lifelong Planning A* algorithm, which in turn is used to make a faster D*-lite algorithm that also incorporates heuristics. The Anytime A* algorithm makes a path always available, which improves with time. The heuristics are further learnt by successive traversals using the Learning Real-Time A*." @default.
- W4386963175 created "2023-09-23" @default.
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- W4386963175 date "2024-01-01" @default.
- W4386963175 modified "2023-10-03" @default.
- W4386963175 title "Graph search-based motion planning" @default.
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- W4386963175 doi "https://doi.org/10.1016/b978-0-443-18908-1.00008-x" @default.
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