WasserMan: Benchmark for Underwater Manipulation Policy Learning
Overview
This paper introduces WasserMan, the first multi-task simulation benchmark dedicated to visuomotor policy learning for articulated underwater mechanisms.
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Environment: simulation
“arXiv:2610.04536v2 Announce Type: replace Abstract: Underwater contact manipulation couples visual decisions with vehicle stabilization and mechanism interaction. To our knowledge, WasserMan is the first multi-task simulation benchmark focused on visuomotor policy learning for manipulating articulated underwater mechanisms. The suite supports demonstration-based policy learning, alternative vehicle--arm platforms and”
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“s. Expert references establish task feasibility under the same physical success tests. The experiments reveal task-dependent visual transfer and pose sensitivity, while contact, tracking and actuator measurements distinguish execution responses that completion alone hides. Complete expert candidate streams make the initial states associated with demonstration selection inspectable. Versioned code, demonstrations, che”
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- arXiv Robotics — research abstractsSignalWasserMan: Benchmark for Underwater Manipulation Policy Learning
This paper introduces WasserMan, the first multi-task simulation benchmark dedicated to visuomotor policy learning for articulated underwater mechanisms.
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