ESCAPE combines spatio-temporal fusion mapping for depth-free 3D memory with a memory-driven grounding module and adaptive execution policy to reach 65.09% success on ALFRED test-seen long-horizon mobile manipulation tasks.
In: Conference on robot learning
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BoxerNet lifts 2D bounding boxes to metric 3D boxes via transformer regression with aleatoric uncertainty and median depth encoding, then fuses multi-view results to outperform CuTR by large margins on open-world benchmarks.
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ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation
ESCAPE combines spatio-temporal fusion mapping for depth-free 3D memory with a memory-driven grounding module and adaptive execution policy to reach 65.09% success on ALFRED test-seen long-horizon mobile manipulation tasks.
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Boxer: Robust Lifting of Open-World 2D Bounding Boxes to 3D
BoxerNet lifts 2D bounding boxes to metric 3D boxes via transformer regression with aleatoric uncertainty and median depth encoding, then fuses multi-view results to outperform CuTR by large margins on open-world benchmarks.