EmbodiedCity: A Benchmark Platform for Embodied Agent in Real-world City Environment
Embodied artificial intelligence emphasizes the role of an agent's body in generating human-like behaviors. The recent efforts on EmbodiedAI pay a lot of attention to building up machine learning models to possess perceiving, planning, and acting abilities, thereby enabling real-time interactio...
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Zusammenfassung: | Embodied artificial intelligence emphasizes the role of an agent's body in
generating human-like behaviors. The recent efforts on EmbodiedAI pay a lot of
attention to building up machine learning models to possess perceiving,
planning, and acting abilities, thereby enabling real-time interaction with the
world. However, most works focus on bounded indoor environments, such as
navigation in a room or manipulating a device, with limited exploration of
embodying the agents in open-world scenarios. That is, embodied intelligence in
the open and outdoor environment is less explored, for which one potential
reason is the lack of high-quality simulators, benchmarks, and datasets. To
address it, in this paper, we construct a benchmark platform for embodied
intelligence evaluation in real-world city environments. Specifically, we first
construct a highly realistic 3D simulation environment based on the real
buildings, roads, and other elements in a real city. In this environment, we
combine historically collected data and simulation algorithms to conduct
simulations of pedestrian and vehicle flows with high fidelity. Further, we
designed a set of evaluation tasks covering different EmbodiedAI abilities.
Moreover, we provide a complete set of input and output interfaces for access,
enabling embodied agents to easily take task requirements and current
environmental observations as input and then make decisions and obtain
performance evaluations. On the one hand, it expands the capability of existing
embodied intelligence to higher levels. On the other hand, it has a higher
practical value in the real world and can support more potential applications
for artificial general intelligence. Based on this platform, we evaluate some
popular large language models for embodied intelligence capabilities of
different dimensions and difficulties. |
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DOI: | 10.48550/arxiv.2410.09604 |