PSG-Nav: Probabilistic Scene Graph Navigation via Multiverse Decision Making
Open-vocabulary navigation requires embodied agents to manage significant perception uncertainty stemming from semantic ambiguity and model errors. However, most existing works settle for local optimal deterministic approaches, depriving complex navigation decision-making over multiple composite possibilities that are critical for globally better solutions. In this paper, we propose Probabilistic Scene Graph Navigation (PSG-Nav), which constructs a 3D Probabilistic Scene Graph that uses full semantic categorical distributions to account for perception uncertainty. To efficiently use the local distributions to compose and reason about the optimal navigation landmarks, we propose Multiverse...
| Authors | Rufeng Chen, Yue Chang, Xiaqiang Tang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 31 May 2026 |
| Last updated at source | 31 May 2026 |
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