IR-SIM: A Lightweight Declarative Simulator for Navigation Learning and Benchmarking
Developing navigation policies requires simulation scenarios that support repeatable training and evaluation. Despite the availability of numerous simulators, constructing diverse navigation scenarios often involves writing simulator-specific code, using complex graphical interfaces, performing substantial manual configuration, or relying on resource-intensive computing platforms, making scenarios difficult to reproduce and reuse across experiments. To this end, we develop the Intelligent Robot Simulator (IR-SIM), a lightweight declarative simulator implemented as a Python library to support navigation learning and benchmarking through rapid construction of reusable and diverse scenarios ...
| Authors | Ruihua Han, Shuai Wang, Chengyang Li et al. |
|---|---|
| Primary category | cs.RO |
| Published | 7 June 2026 |
| Last updated at source | 29 September 2026 |
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