Shengshu's Motus2 Robot World Model Closes the Loop: Act, Predict, Self-Evaluate

量子位 · wechat · 2026-09-12

Shengshu (生数科技) released Motus2, a robot world model unifying three skills in one model — action (WAM), prediction (AC-WM), and evaluation (VM) — forming a closed self-improvement loop: generate action → predict outcome → evaluate → update policy. The original Motus beat Pi-0.5 by 35+ points absolute success rate across 50 tasks.

Key techniques:

Deployed on 22-DoF SharpaWave and 20-DoF WUJI Hand2 dexterous hands for bulb-screwing, page-turning and multi-finger manipulation. Under Shengshu's L1-L5 world-model roadmap, Motus2 reaches L3 (acting in the world) and begins touching L4 recursive self-improvement; long-horizon open-world learning remains open.

Related event: Shengshu Unveils Motus2, a Self-Evolving Robot World Model(2 posts)→

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