TY - GEN
T1 - Proposal of an Environmental Recognition Method for Automatic Parking by an Image-based CNN
AU - Yamamoto, Kazuki
AU - Watanabe, Keigo
AU - Nagai, Isaku
PY - 2019/8
Y1 - 2019/8
N2 - In recent years, researches on autonomous mobile robots are being advanced, and among them, practical use of automatic driving cars is expected particularly. In this realization, there is a parking problem as one of the problems to be solved. Currently, although various sensors such as infrared lasers and millimeter wave radars are used for parking problems, it is desirable to use the less number of sensors and select cheaper ones when considering the cost. This research aims to recognize the surrounding environment for parking control by only images obtained from using a monocular camera. For safe parking, it needs to detect the parking position and check the space to turn the wheel. A technique called Convolutional Neural Network (CNN), which is now a mainstream in image recognition fields, is used to archive them. This paper constructs a system for judging a parking possibility using object detection and a system for classifying several patterns of the space to turn the wheel using depth images. Some simulations are conducted to verify whether the surrounding environment in parking can be integratedly judged by the proposed system.
AB - In recent years, researches on autonomous mobile robots are being advanced, and among them, practical use of automatic driving cars is expected particularly. In this realization, there is a parking problem as one of the problems to be solved. Currently, although various sensors such as infrared lasers and millimeter wave radars are used for parking problems, it is desirable to use the less number of sensors and select cheaper ones when considering the cost. This research aims to recognize the surrounding environment for parking control by only images obtained from using a monocular camera. For safe parking, it needs to detect the parking position and check the space to turn the wheel. A technique called Convolutional Neural Network (CNN), which is now a mainstream in image recognition fields, is used to archive them. This paper constructs a system for judging a parking possibility using object detection and a system for classifying several patterns of the space to turn the wheel using depth images. Some simulations are conducted to verify whether the surrounding environment in parking can be integratedly judged by the proposed system.
KW - Autonomous Mobile Robot
KW - Convolutional Neural Network
KW - Paking Problem
UR - http://www.scopus.com/inward/record.url?scp=85072393995&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072393995&partnerID=8YFLogxK
U2 - 10.1109/ICMA.2019.8816556
DO - 10.1109/ICMA.2019.8816556
M3 - Conference contribution
AN - SCOPUS:85072393995
T3 - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
SP - 833
EP - 838
BT - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Mechatronics and Automation, ICMA 2019
Y2 - 4 August 2019 through 7 August 2019
ER -