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3D Reconstruction of Natural Environments for Robotic Navigation
In this project, the student will explore efficient ways of modeling a natural environment to support long-term robotic navigation.
Keywords: 3D reconstruction. Deep-Learning, Robotics, Drones
Natural environments are extremely hard to be mapped because of their unstructured nature. Foliage and branches are too thin to be properly reconstructed. So in this project, the student will explore efficient ways of modeling a natural environment to support long-term robotic navigation.
Natural environments are extremely hard to be mapped because of their unstructured nature. Foliage and branches are too thin to be properly reconstructed. So in this project, the student will explore efficient ways of modeling a natural environment to support long-term robotic navigation.
- WP1. Learn to use the hardware and software tools needed to complete the project.
- WP2. Learn the necessary theory in the field of 3D reconstruction.
- WP3. Design methods converting dense noise point clouds in robust maps for robot navigation, especially drones.
- WP4. Implement and test designed methods in desktop and mobile environments.
- WP1. Learn to use the hardware and software tools needed to complete the project. - WP2. Learn the necessary theory in the field of 3D reconstruction. - WP3. Design methods converting dense noise point clouds in robust maps for robot navigation, especially drones. - WP4. Implement and test designed methods in desktop and mobile environments.
- Interest in drones, mapping, and 3d reconstruction.
- Familiarity with Computer Vision and C++ programming.
- Interest in working with a company and performing some field work.
- Interest in drones, mapping, and 3d reconstruction. - Familiarity with Computer Vision and C++ programming. - Interest in working with a company and performing some field work.
Please send your CV and Transcripts to pilucas@ethz.ch
Please send your CV and Transcripts to pilucas@ethz.ch
