AquaJEPA: Action-Conditioned Multimodal Predictive Representations for Underwater Robot Dynamics

AquaWAM: A Dynamics-aware World Action Model for Underwater Embodied Agents

World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequences of candidate actions before interacting with the physical environment. However, underwater robots are usually subject to passive dynamics, such as inertia, buoyancy,...

AquaCap: A Training-Free Underwater Embodied Agent with Code-as-Policy

Recent advances in vision-language-action models have stimulated growing interest in underwater embodied intelligence. However, their reliance on large-scale interaction data limits their applicability underwater, where data collection is costly and scarce. To address this challenge, we present AquaCap, a training-free...

AquaWorld: Structure-Consistent Underwater World Generation for Robot Simulation

Underwater robot simulation requires diverse environments in which terrain, scene composition, tasks, and currents remain mutually consistent. We present AquaWorld, a world-generation framework that preserves these relationships through shared terrain structure. A language-conditioned plan generates 3D terrain and shar...

WasserMan: Benchmark for Underwater Manipulation Policy Learning

Underwater manipulation couples visual decisions, contact forces and a thruster-controlled floating base. We introduce WasserMan, to our knowledge the first multi-task simulation benchmark for visuomotor learning of floating-base underwater contact manipulation. It provides ten expert-solvable tasks, two vehicle-arm pl...

Evaluating Early Multimodal Fusion in Discrete Latent World Models for Robot Navigation

BCNav: Bearing-Conditioned Depth Policies for Sound Source Navigation

The ability to navigate toward sound sources extends a robot's reach beyond its visual field, enabling response to auditory events in unknown environments. To equip robots with this capability, existing methods couple acoustic and visual information through joint audio-visual learning in acoustic simulators. However, a...