2025/09/21 by Gokul B. Nair, Alejandro Fontan, Nair, Gokul B. +5
Computer Science · Engineering · #Advanced Optical Imaging Technologies #Advanced Vision and Imaging #CCD and CMOS Imaging Sensors #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2509.17287
openalex publication_date 2025/09/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Visual teach-and-repeat (VT&R) navigation enables robots to autonomously traverse previously demonstrated paths using visual feedback. We present a novel event-camera-based VT&R system. Our system formulates event-stream matching as frequency-domain cross-correlation, transforming spatial convolutions into efficient Fourier-space multiplications. By exploiting the binary structure of event frames and applying image compression techniques, we achieve a processing latency of just 2.88 ms, about 3.5 times faster than conventional camera-based baselines that are optimised for runtime efficiency. Experiments using a Prophesee EVK4 HD event camera mounted on an AgileX Scout Mini robot demonstrate successful autonomous navigation across 3000+ meters of indoor and outdoor trajectories in daytime and nighttime conditions. Our system maintains Cross-Track Errors (XTE) below 15 cm, demonstrating the practical viability of event-based perception for real-time VT&R navigation.