@inproceedings{d31a2a746a6f43b58ecda14a48115098,
title = "Improvement of Position Error Rate of Docking of Autonomous Mobile Robot with Object Recognition and Ultrasonic Sensor",
abstract = "In this paper, we present docking performance using only the ultrasonic sensor and docking performance by fusing ultrasonic and object recognition data. In an autonomous mobile robot, the angle is calculated using only ultrasonic data, and the resulting position error rate is docked by fusing the ultrasonic sensor and the object recognition data, and the resulting position error rate is compared. Through this experiment, we confirmed the improvement of the position error rate of the two experiments.",
keywords = "AMR, Docking, Object recognition, SSD-MobileNet, Ultrasonic",
author = "Lee, \{Sang Min\} and Joo, \{Kyeong Jin\} and In, \{Gun Gyo\} and Kuc, \{Tae Yong\}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 18th International Conference on Intelligent Autonomous Systems, IAS18 2023 ; Conference date: 04-07-2023 Through 07-07-2023",
year = "2024",
doi = "10.1007/978-3-031-44851-5\_10",
language = "English",
isbn = "9783031448508",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "123--131",
editor = "Soon-Geul Lee and Jinung An and Chong, \{Nak Young\} and Marcus Strand and Kim, \{Joo H.\}",
booktitle = "Intelligent Autonomous Systems 18 - Volume 1 Proceedings of the 18th International Conference IAS18-2023",
}