Thank you!
Yea we also went through a lot of the papers that tried to do long range perception for the LAGR project.
Really cool to take inspiration from works almost 20 years old but still very relevant :)
🔥 Key insight: Robots can reason further by learning to identify distant affordable frontiers as intermediate goals.
🧠 How it works: It uses a pre-trained SAM2 backbone + small head to find frontiers in images. Given a goal, it selects the highest-scoring one to navigate to.
🧵3/6
This work is a collaboration between the Personal Robotics Lab (@siddhss5.bsky.social) and Robot Learning Lab at the University of Washington @uwrobotics.bsky.social @uwcse.bsky.social
🧵5/6
❗️Problem: Robots navigating with no prior maps relying only on local sensors have a limited mapping range (due to sparse/noisy depth) causing myopic decisions.
🧵2/6
Long Range Navigator (LRN) 🧭— an approach to extend planning horizons for off-road navigation given no prior maps. Using vision LRN makes longer-range decisions by spotting navigation frontiers far beyond the range of metric maps.
personalrobotics.github.io/lrn/
🧵1/6