Uses a CVL (Curiosity-driven Vision-Language) score to prioritize exploring unknown areas that align with human descriptions.
"In rigorous testing, including the , VL-Nav achieved a 75–83% success rate across indoor and outdoor settings. In real-world deployments, it maintained an 86.3% success rate , demonstrating reliability over long-range trajectories of up to 483 meters." Resources for Further Development Sandris Dubovs V L Nav Neka
is an advanced robotic navigation framework that combines neural reasoning (the "brain") with symbolic guidance (the "logic") to help robots navigate complex environments. Unlike traditional methods that might lead to aimless wandering, VL-Nav uses a NeSy (Neuro-Symbolic) Task Planner and an Exploration System to understand abstract human instructions. Useful Text Blocks 1. The "Problem & Solution" Pitch (Good for Intros) Unlike traditional methods that might lead to aimless
Leverages a 3D scene graph and image memory to help Vision Language Models (VLMs) replan tasks in real-time. You can find the full technical details on arXiv: VL-Nav
You can find the full technical details on arXiv: VL-Nav .