WasserMan: Benchmark for Underwater Manipulation Policy Learning
cs.RO
Submitted: 2026-10-03
Updated: 2026-10-03
Comments: 8 pages, 8 figures. Submitted to IEEE Robotics and Automation Letters (RA-L)
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- DAVE Aquatic Virtual Environment: Toward a General Underwater Robotics Simulator
- Stonefish: Supporting Machine Learning Research in Marine Robotics
- MarineGym: Accelerated Training for Underwater Vehicles with High-Fidelity RL Simulation
- Bi-AQUA: Bilateral Control-Based Imitation Learning for Underwater Robot Arms via Lighting-Aware Action Chunking with Transformers
- UMI-Underwater: Learning Underwater Manipulation without Underwater Teleoperation
- ULOHA: An Underwater Bimanual Robot System for Robot Learning
- RLBench: The Robot Learning Benchmark & Learning Environment
- robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
- ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
- ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
- Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
- CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
- LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
- BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
- RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
- What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
- Attention Is All You Need
- Denoising Diffusion Probabilistic Models
- Denoising Diffusion Implicit Models
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