RF-Enhanced Pavement Markings for Mobile Robot Lane Detection - Suo, Dajiang; Li, Heyi; Bhattacharyya, Rahul; Melia-Segui, Joan; Sarma, Sanjay E. (IEEE International Conference on Automation Science and Engineering (CASE), 2023)
The ability to detect and keep in lanes is crucial for the safe operation of autonomous mobile robots in construction sites and their coordination with humans in autonomous ports or logistic centers. While computer vision-based lane detection algorithms perform well under normal conditions, their performance may degrade under low visibility conditions and in adverse weather. Since robots are not constrained by human perception limits, this paper proposes a radio frequency (RF) pavement marking system that builds on Radio Frequency Identification (RFID), a short-range communication technology, to provide lane-detection assistance. We present not only the hardware designs for the RFID systems on both vehicles and roads but also a filtering algorithm to mitigate the noise in the backscattered RF signals for lane detection. Experimental results show that the information on lane keeping provided by the RF pavement markings aligns with the visual channel when mobile robots move at a speed of less than 40 miles per hour.