Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing

arXiv:2405.01054v1 Announce Type: cross
Abstract: In autonomous and mobile robotics, a principal challenge is resilient real-time environmental perception, particularly in situations characterized by unknown and dynamic elements, as exemplified in the context of autonomous drone racing. This study introduces a perception technique for detecting drone racing gates under illumination variations, which is common during high-speed drone flights. The proposed technique relies upon a lightweight neural network backbone augmented with capabilities for continual learning. The envisaged approach amalgamates predictions of the …

abstract arxiv autonomous challenge context continual cs.cv cs.lg cs.ro detection drone drone racing dynamic environmental gate gates lighting mobile perception racing real-time resilient robotics robust study type