RTNav: Towards Real-Time Zero-Shot Object Navigation

arXiv:2608.26496 · cs.RO, cs.AI, cs.CV · Submitted 2026-08-27 · Read on arXiv

cs.RO, cs.AI, cs.CV

Submitted: 2026-08-27

Updated: 2026-08-27

Code: https://github.com/openai/simple-evals

Terminology

• Benchmark — 36× in this paper · explained in 2 episodes
• Foundation Model — 10× in this paper · explained in 3 episodes
• Verification — 10× in this paper · explained in 2 episodes
• Success Rate — 8× in this paper
• Foundation Models — 7× in this paper · explained in 7 episodes
• Embodied AI — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Distance to Goal — 1× in this paper
• Embeddings — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes

Sources

• BeliefMapNav: 3D Voxel-Based Belief Map for Zero-Shot Object Navigation
• Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI
• AI2-THOR: An Interactive 3D Environment for Visual AI
• LiveVLN: Breaking the Stop-and-Go Loop in Vision-Language Navigation
• Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Tasks
• Embodied Navigation Foundation Model
• JanusVLN: Decoupling Semantics and Spatiality with Dual Implicit Memory for Vision-Language Navigation
• Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

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