Aerial 3D Mapping with UAVs: NeRF-Based Environment Reconstruction
This project aims to develop a system where UAVs (Unmanned Aerial Vehicles) capture high-resolution aerial images and generate detailed 3D reconstructions of various environments using Neural Radiance Fields (NeRFs). The project will involve the entire pipeline from data collection to the generation of accurate 3D models, leveraging the power of UAVs and advanced computer vision techniques.
The project tasks include flying one or multiple UAVs equipped with high-resolution cameras to systematically capture aerial imagery of targeted environments followed by implementing a NeRF-based pipeline that processes the collected images into high-quality 3D reconstructions.
Research in this lab directly addresses critical challenges in robotics, including improving navigation in uncharted environments, enhancing sensor fusion techniques, and developing robust autonomous systems. These applications extend beyond space exploration to fields like autonomous vehicles, drones, and smartphones. Key student outcomes are:
- Students in the lab will emerge with a broad and valuable skill set, having collaborated across robotics, aerospace engineering, computer vision, and AI.
- Students will gain hands-on experience with cutting-edge robotics platforms, advanced sensors, and powerful computational tools, and exposure to advanced programming, machine learning, deep learning, sensor fusion, and hardware integration.
- Students will be equipped to develop novel solutions to complex robotics challenges by using creative thinking and engineering prototyping.
- Students will gain the opportunity to collaborate with either industry or government organizations on impactful projects, leading to real-world applications.