Have You Seen It Clearly? Uncertainty-Guided Belief Refinement for Zero-Shot Object Navigation
cs.RO
Submitted: 2026-10-11
Updated: 2026-10-11
Code: https://github.com/kim-os/RefBeliefNav
Sources
- Matterport3D: Learning from RGB-D Data in Indoor Environments
- AECNav: Active Evidence Consolidation for Efficient Zero-Shot Open-Vocabulary Object Navigation
- Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI
- Dual-Layer Semantic-Spatial Belief Mapping for Aerial Object Goal Navigation
- Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
- IGV-RRT: Prior-Real-Time Observation Fusion for Active Object Search in Changing Environments
Related papers
- FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
- MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
- RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
- ARC: A Reasoning Recipe for Robot Foundation Models
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies