RVN-Bench: A Benchmark for Reactive Visual Navigation
Safe visual navigation is critical for indoor mobile robots operating in cluttered environments. Existing benchmarks, however, often neglect collisions or are designed for outdoor scenarios, making them unsuitable for indoor visual navigation. To address this limitation, we introduce the reactive visual navigation benchmark (RVN-Bench), a collision-aware benchmark for indoor mobile robots. In RVN-Bench, an agent must reach sequential goal positions in previously unseen environments using only visual observations and no prior map, while avoiding collisions. Built on the Habitat 2.0 simulator and leveraging high-fidelity HM3D scenes, RVN-Bench provides large-scale, diverse indoor environmen...
| Authors | Jaewon Lee, Jaeseok Heo, Gunmin Lee et al. |
|---|---|
| Primary category | cs.RO |
| Published | 4 March 2026 |
| Last updated at source | 11 July 2026 |
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