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http://dx.doi.org/10.5370/KIEE.2018.67.8.1089

Autonomous Feeding Robot and its Ultrasonic Obstacle Classification System  

Kim, Seung-Gi (Korea Orthopedics & Rehabilitation Engineering Center)
Lee, Yong-Chan (School of EE, Kyungpook National University)
Ahn, Sung-Su (Daegu Mechatronics & Materials Institute)
Lee, Yun-Jung (School of Electronics Engineering, Kyungpook National University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.67, no.8, 2018 , pp. 1089-1098 More about this Journal
Abstract
In this paper, we propose an autonomous feeding robot and its obstacle classification system using ultrasonic sensors to secure the driving safety of the robot and efficient feeding operation. The developed feeding robot is verified by operation experiments in a cattle shed. In the proposed classification algorithm, not only the maximum amplitude of the ultrasonic echo signal but also two gradients of the signal and the variation of amplitude are considered as the feature parameters for object classification. The experimental results show the efficiency of the proposed classification method based on the Support Vector Machine, which is able to classify objects or obstacles such as a human, a cow, a fence and a wall.
Keywords
Autonomous feeding robot; Ultrasonic sensor; Object classification; Support vector machine;
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Times Cited By KSCI : 2  (Citation Analysis)
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