Anttwo/MACARONS

(CVPR 2023) Official code of MACARONS: Mapping And Coverage Anticipation with RGB ONline Self-supervision. Also contains an updated and improved implementation of our previous work SCONE (NeurIPS 2022), on which this work is built.

27
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Experimental

This project helps autonomous robots or drones efficiently explore and map large, unknown environments in 3D using only color images. It takes raw color video streams as input and generates an optimized path for the robot to follow, along with a detailed 3D reconstruction of the environment. The primary users are robotics engineers, drone operators, and researchers working on autonomous navigation and 3D scene understanding.

No commits in the last 6 months.

Use this if you need an autonomous system to systematically explore and create accurate 3D maps of unfamiliar large spaces without prior knowledge or external supervision.

Not ideal if you require mapping extremely small objects or need highly precise measurements from structured light sensors, as this focuses on broad environmental coverage from color imagery.

autonomous-navigation robotics 3D-reconstruction environmental-mapping drone-operations
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 10 / 25

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Last pushed

Dec 23, 2023

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