How Far Can GPT-6-Astra Go? Evaluating Capabilities in Zero-Shot Vision-and-Language Navigation
cs.RO
Submitted: 2026-09-17
Updated: 2026-09-18
Project page: https://daiguangzhao.github.io/gpt-6-astra-vln
Terminology
Sources
- HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness
- SpatialAnt: Autonomous Zero-Shot Robot Navigation via Active Scene Reconstruction and Visual Anticipation
- AgenticNav: Zero-Shot Vision-and-Language Navigation as a Tool-Calling Harness
- NavBench: Probing Multimodal Large Language Models for Embodied Navigation
- Fast-SmartWay: Panoramic-Free End-to-End Zero-Shot Vision-and-Language Navigation
- DreamNav: A Trajectory-Based Imaginative Framework for Zero-Shot Vision-and-Language Navigation
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
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving