Flying in Clutter on Monocular RGB by Learning in 3D Radiance Fields with Domain Adaptation

This article describes a research paper focusing on a specific problem in computer vision and robotics: enabling autonomous navigation in complex, cluttered environments using only monocular RGB images. The approach involves learning 3D representations (radiance fields) and adapting them to different visual domains. The title suggests a focus on practical application (flying) and the challenges of real-world environments (clutter). The use of 'domain adaptation' indicates an attempt to generalize the learned models across different visual conditions.

• •Focuses on autonomous navigation using monocular RGB.
• •Employs 3D radiance fields for scene representation.
• •Utilizes domain adaptation to improve generalization.
• •Addresses the challenge of navigating in cluttered environments.