arXiv:2507.18623v4 Announce Type: replace-cross Abstract: The ability to adapt to physical actions and constraints in an environment is crucial for embodied agents (e.g., robots) to effectively collaborate with humans. Such physically grounded human-AI collaboration must account for the increased complexity of the continuous state-action space and constrained dynamics caused by physical constraints. However, most existing collaboration benchmarks are discrete or do not consider physical attributes and constraints. To address this, we introduce Moving Out, a human-AI collaboration benchmark tha
The increasing focus on embodied AI and robotics necessitates more realistic benchmarks for human-AI collaboration, moving beyond discrete simulations to physical interactions.
This development is crucial for advancing AI's ability to operate effectively in the real world alongside humans, particularly in complex physical tasks.
The introduction of a physically-grounded benchmark for human-AI collaboration will accelerate research and development in making embodied AI more practical and robust.
- · Robotics companies
- · AI research institutions
- · Automation sector
- · Developers of purely discrete AI collaboration models (without physical groundin
Improved performance of embodied AI agents in complex physical environments.
Faster integration of AI into physical labor and service industries requiring human interaction.
New safety standards and ethical considerations emerging from more sophisticated human-robot physical collaboration.
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