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Policies may succeed in tasks but still violate deformation tolerances, revealing a critical gap in current evaluation methods for deformable-object manipulation.
Push-Wiper's innovative approach to robotic cleaning can remove up to 130% more stains than traditional methods while adapting seamlessly to different surfaces and stain types.
Training-Distribution Hallucination is a critical challenge in robot manipulation, but ST-WAM's innovative use of DINOv3 features dramatically boosts performance under visual shifts.
Achieve robust SLAM in dynamic environments without semantic labels or depth sensors by disentangling scene dynamics with a generalizable motion model.
Navigate to objects forever: OVAL enables robots to continuously explore and remember new environments, unlocking truly lifelong object goal navigation.
