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Improvement of Position Error Rate of Docking of Autonomous Mobile Robot with Object Recognition and Ultrasonic Sensor

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Intelligent Autonomous Systems 18 (IAS 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 795))

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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.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea

    Sang-Min Lee, Kyeong-** Joo, Gun-Gyo In & Tae-Yong Kuc

Authors
  1. Sang-Min Lee
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  2. Kyeong-** Joo
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  3. Gun-Gyo In
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  4. Tae-Yong Kuc
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Corresponding author

Correspondence to Tae-Yong Kuc .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Kyung Hee University, Yongin-si, Korea (Republic of)

    Soon-Geul Lee

  2. Department of Interdisciplinary Engineering, Daegu Gyeongbuk Institute of Science and DGIST R4-708, Daegu, Korea (Republic of)

    **ung An

  3. School of Information Science, Human Information Science Research Area, Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Nak Young Chong

  4. DHBW Karlsruhe, Cooperative State University Baden-Wuerttemberg Karlsruhe, Karlsruhe, Germany

    Marcus Strand

  5. Department of Mechanical and Aerospace Engineering, New York University, New York, NY, USA

    Joo H. Kim

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Lee, SM., Joo, KJ., In, GG., Kuc, TY. (2024). Improvement of Position Error Rate of Docking of Autonomous Mobile Robot with Object Recognition and Ultrasonic Sensor. In: Lee, SG., An, J., Chong, N.Y., Strand, M., Kim, J.H. (eds) Intelligent Autonomous Systems 18. IAS 2023. Lecture Notes in Networks and Systems, vol 795. Springer, Cham. https://doi.org/10.1007/978-3-031-44851-5_10

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