Foreign Object Debris

Foreign object debris (FOD) research focuses on detecting and removing unwanted objects in diverse environments, from underwater to space. Current efforts leverage computer vision and deep learning, employing models like YOLOv5, Faster-RCNN, and transformer-based architectures, to automate detection and classification of FOD, often using drone or underwater imagery and robotic systems for removal. This work is significant for environmental remediation (e.g., marine debris cleanup), industrial safety (e.g., preventing machinery damage), and space exploration (e.g., space debris mitigation), offering improved efficiency and reduced human risk in challenging environments.