A dual-mode SDF trajectory optimizer, using object and robot body neural SDFs plus memory, is reported to achieve 98% success in simulated dynamic indoor navigation.
V oxblox: Incremental 3d euclidean signed distance fields for on- board mav planning,
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Differentiable Composite Neural Signed Distance Fields for Robot Navigation in Dynamic Indoor Environments
A dual-mode SDF trajectory optimizer, using object and robot body neural SDFs plus memory, is reported to achieve 98% success in simulated dynamic indoor navigation.