TY - GEN
T1 - Desgin and Implementation of ROS2-based Autonomous Tiny Robot Car with Integration of Multiple ROS2 FPGA Nodes
AU - Mori, Hayato
AU - Amano, Hayato
AU - Mizutani, Akinobu
AU - Okazaki, Eisuke
AU - Konno, Yuki
AU - Sada, Kohei
AU - Ono, Tomohiro
AU - Yoshimoto, Yuma
AU - Tamukoh, Hakaru
AU - Ohkawa, Takeshi
AU - Sugaya, Midori
N1 - Funding Information:
ACKNOWLEDGMENT This work was partly supported by JST CREST Grant Number JPMJCR19K1, Japan.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper introduces an autonomous tiny robot car equipped with a camera-based lane detection function and a traffic signal/obstacle, pedestrian recognition function. Each function is integrated by Robot Operating System 2 (ROS2), a middleware for robot system development. Autonomous driving without the need for a driver requires not only lane-following driving but also traffic signal recognition and obstacle recognition. These functions are implemented on FPGA, and we evaluated them. According to these results, the execution time of traffic signal recognition by FPGA was 1.2 to 3.4 times faster than CPU execution. YOLOv4 is used for obstacle recognition, which improved mAP by 3.79 points compared to YOLO v3-Tiny.
AB - This paper introduces an autonomous tiny robot car equipped with a camera-based lane detection function and a traffic signal/obstacle, pedestrian recognition function. Each function is integrated by Robot Operating System 2 (ROS2), a middleware for robot system development. Autonomous driving without the need for a driver requires not only lane-following driving but also traffic signal recognition and obstacle recognition. These functions are implemented on FPGA, and we evaluated them. According to these results, the execution time of traffic signal recognition by FPGA was 1.2 to 3.4 times faster than CPU execution. YOLOv4 is used for obstacle recognition, which improved mAP by 3.79 points compared to YOLO v3-Tiny.
KW - FPGA
KW - Robot Operating System 2
KW - YOLOv4-tiny
UR - http://www.scopus.com/inward/record.url?scp=85145559746&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85145559746&partnerID=8YFLogxK
U2 - 10.1109/ICFPT56656.2022.9974433
DO - 10.1109/ICFPT56656.2022.9974433
M3 - Conference contribution
AN - SCOPUS:85145559746
T3 - FPT 2022 - 21st International Conference on Field-Programmable Technology, Proceedings
BT - FPT 2022 - 21st International Conference on Field-Programmable Technology, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International Conference on Field-Programmable Technology, FPT 2022
Y2 - 5 December 2022 through 9 December 2022
ER -