AICVFeb 5, 2024

V-IRL: Grounding Virtual Intelligence in Real Life

arXiv:2402.03310v344 citationsh-index: 17ECCV
AI Analysis

This addresses the challenge of developing flexible AI agents for real-world settings without hardware constraints, though it appears incremental as a platform for existing methods.

The paper tackles the problem of bridging the realism gap between digital AI agents and the physical world by introducing V-IRL, a platform that enables agents to interact scalably with realistic virtual environments based on real-world data.

There is a sensory gulf between the Earth that humans inhabit and the digital realms in which modern AI agents are created. To develop AI agents that can sense, think, and act as flexibly as humans in real-world settings, it is imperative to bridge the realism gap between the digital and physical worlds. How can we embody agents in an environment as rich and diverse as the one we inhabit, without the constraints imposed by real hardware and control? Towards this end, we introduce V-IRL: a platform that enables agents to scalably interact with the real world in a virtual yet realistic environment. Our platform serves as a playground for developing agents that can accomplish various practical tasks and as a vast testbed for measuring progress in capabilities spanning perception, decision-making, and interaction with real-world data across the entire globe.

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Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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