February 12 — Alibaba-owned AutoNavi unveiled its ABot sequence embodied basis fashions: ABot-M0 for robotic manipulation and ABot-N0 for navigation. Each achieved complete SOTA outcomes throughout 10 main world benchmarks.
ABot-M0 is described because the world‘s first unified-architecture basis mannequin for robotic manipulation. It standardizes coordinate methods, management frequencies, and incremental movement modeling to combine trajectory information throughout platforms. The coaching dataset—constructed totally from public sources—consists of over 9,500 hours, 6 million trajectories, and information spanning greater than 20 embodied varieties.
Algorithmically, the staff launched an Motion Manifold Studying (AML) methodology and built-in 3D notion modules for enhanced spatial semantic understanding. On the Libero-Plus benchmark, ABot-M0 achieved an 80.5% activity success fee, almost 30 proportion factors increased than the earlier main methodology.
ABot-N0 is the primary single VLA-based navigation basis mannequin to unify 5 core navigation duties: point-to-point navigation, object navigation, instruction following, point-of-interest navigation, and pedestrian following.
It makes use of a hierarchical “mind–motion” structure: a cognition module primarily based on a pretrained giant language mannequin handles semantic understanding and activity decomposition, whereas motion specialists generate exact trajectories by way of circulation matching.
AutoNavi constructed a navigation information engine with roughly 8,000 high-fidelity 3D scenes and almost 17 million skilled demonstrations. The mannequin set new data throughout seven main benchmarks, together with CityWalker, SocNav, R2R-CE/RxR-CE, and HM3D-OVON. In SocNav closed-loop simulation, success charges improved by 40.5%, whereas object navigation success in HM3D-OVON rose by 8.8%.
AutoNavi mentioned ABot-N0 has already been deployed on real-world quadruped robots, reaching environment friendly edge-device inference and closed-loop management.
Supply: Minds in AI
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