Sandris Dubovs V L Nav Neka -

Leverages a 3D scene graph and image memory to help Vision Language Models (VLMs) replan tasks in real-time.

"Traditional robot navigation often fails when faced with complex, multi-step instructions or unknown environments, resulting in inefficient 'aimless wandering.' addresses this by intertwining neural semantic understanding with symbolic 3D scene graphs. This allows the robot to decompose abstract commands—like finding a waterproof jacket based on a rain report—into logical navigation goals." 2. Key Technical Features (Good for Specs) Sandris Dubovs V L Nav Neka

View demonstrations on robots like the Unitree G1 and Go2 at the SAIR Lab Project Page . Leverages a 3D scene graph and image memory

Proven to navigate successfully across different floors and transitions (e.g., using elevators or stairs) in complex building layouts. 3. Performance Summary (Good for Validation) Key Technical Features (Good for Specs) View demonstrations

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)