Motion Planning Explorer: Visualizing Local Minima using a Local-Minima Tree
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We present an algorithm to visualize local minima in a motion planning problem, which we call the motion planning explorer. The input to the explorer is a planning problem, a sequence of lower-dimensional projections of the configuration space, a cost functional and an optimization method. The output is a local-minima tree, which is interactively grown based on user input. The local-minima tree captures non-self-intersecting local minima of a problem. We show the motion planning explorer to faithfully capture the structure of four real-world scenarios.
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