Lingjing: A Simulation Testbed for Multi-Agent Embodied Tasks in Open-Ended Cities
Urban embodied intelligence requires coordination among heterogeneous agents (e.g., UAVs, ground robots, and autonomous vehicles) in dynamic cities. Simulators therefore provide a scalable foundation for developing and evaluating such coordination. Existing platforms nevertheless isolate different embodiments and decouple them from task design and evaluation. We present \textbf{Lingjing}, a simulation platform for heterogeneous multi-agent embodied intelligence in open-ended urban environments. Lingjing reconstructs and renders evolving cities from geographic data, synchronizes multiple physics engines, and exposes shared physical and structured urban state to agents. Its Gym-like interfa...
| Authors | Xiaohe Li, Yiru Wang, Junhao Fan et al. |
|---|---|
| Primary category | cs.AI |
| Published | 8 August 2026 |
| Last updated at source | 8 August 2026 |
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