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cs.RO2026
AquaCap: A Training-Free Underwater Embodied Agent with Code-as-Policy
Xiaoshi Li, Yule Xu, Chunghiu Kong +5
Recent advances in vision-language-action models have stimulated growing interest in underwater embodied intelligence. However, their reliance on large-scale interaction data limit…
cs.RO2026
PileBelief: Persistent Physical State for Interaction-Driven World Modeling
Hongyi Lin, Song Zhang, Haiquan Liu +3
World models allow robots to anticipate action consequences before execution. This capability is especially valuable in excavation, where each scoop reshapes the terrain and affect…
cs.RO2026
Physical-Touch Observability from Wrist Wrench in Granular Scooping
Hongyi Lin, Song Zhang, Xubo Liu +1
Mining and earthmoving are important real-world deployment settings for embodied intelligence. Autonomous transport and driving systems have improved substantially, but loading and…