Where urban life meets embodied intelligence
Tsinghua University EmbodiedCity Team
Latest Projects
Check out our creative works.
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Benchmark
Embodied City
We release a new benchmark platform, named embodied-city, for embodied intelligence in urban environments.
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Benchmark
UrbanVideo-Bench
We introduce a benchmark to evaluate whether video-large language models (Video-LLMs) can naturally process continuous first-person visual observations like humans, enabling recall, perception, reasoning, and navigation.
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Benchmark
Open3DVQA
Open3DVQA is a benchamrk to comprehensively evaluate the spatial reasoning capacities of current SOTA foundation models in open 3D space. It consists of 9k VOA samples, collected using aneffcient semi-automated tool in a high-fdelity urban simulator.
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Task
CityEQA
We introduce CityEQA, a new task where an embodied agent answers open-vocabulary questions through active exploration in dynamic city spaces.
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Framework
Embodied-R
A comprehensive framework for embodied reasoning in urban environments, enabling agents to perform complex spatial reasoning and decision-making tasks through multi-modal perception and interaction.
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World model
AirScape
We introduce AirScape, an aerial generative world model with motion controllability that enables 6DoF aerial agents to predict future observations based on egocentric views and natural language motion intentions.
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Workshop
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Conference
ICLR 2025 Workshop
This workshop is motivated by a fact: human beings have strong embodied intelligence in an open environment, but it is still challenging for large language models and LLM agents. Depsite some progresses on embodied AI on static and indoor environment, the LLM agents are still struggling in tasks in large-scale outdoor environment, such as navigation, search, spatial reasoning, task planning, etc. Therefore, we propose this workshop to discuss the recent advances on the related research area and looking forward to the future development. Specifically, it delves into topics of outdoor embodied intelligence, such as spatial intelligence and embodied perception, reasoning and planning, decision-making and action, multi-agent and human-agent collaboration, and the development of simulators, testbeds, datasets, and benchmarks. This comprehensive exploration of embodied LLM agents in open city environment holds the potential to advance the field of artificial intelligence and open up new applications in various domains.We also have a special poster/short paper session for those solutions that perform best in the Open Urban Environment Embodied Intelligence Competition. See Project