Seeing the Invisible: Physics-Guided Visual Prompting for Temperature- and Radiation-Aware VLA Navigation
cs.RO, cs.AI, cs.LG
Submitted: 2026-10-06
Updated: 2026-10-06
Comments: 8 pages, 7 figures, 2 tables
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation System
- ABot-N0: Technical Report on the VLA Foundation Model for Versatile Embodied Navigation
- Tactile-VLA: Unlocking Vision-Language-Action Model's Physical Knowledge for Tactile Generalization
- Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines
- NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation
- OmniVLA: An Omni-Modal Vision-Language-Action Model for Robot Navigation
- StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling
- Efficient-VLN: A Simple yet Strong Baseline for Efficient Vision-Language Navigation
- SPAN-Nav: Generalized Spatial Awareness for Versatile Embodied Navigation
- SEDualVLN: A Spatially-Enhanced Dual-System Framework for Vision-Language Navigation
- OmniVLA: Physically-Grounded Multimodal VLA with Unified Multi-Sensor Perception for Robotic Manipulation
- GeoVLA: Empowering 3D Representations in Vision-Language-Action Models
- CoRE-VLA: Towards Scalable and Robust Vision-Language-Action Modeling via Conditional Routing of Experts
- Goal2Pixel: Grounding Goals to Pixels for Vision-Language Navigation
- Green for Go, Red for No: Visual Grounding via Semantic Segmentation for VLA Navigation Policies
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