• Title/Summary/Keyword: 냄새 발생지 추적

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Odor Source Tracking of Mobile Robot with Vision and Odor Sensors (비전과 후각 센서를 이용한 이동로봇의 냄새 발생지 추적)

  • Ji, Dong-Min;Lee, Jeong-Jun;Kang, Geun-Taek;Lee, Won-Chang
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.6
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    • pp.698-703
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    • 2006
  • This paper proposes an approach to search for the odor source using an autonomous mobile robot equipped with vision and odor sensors. The robot is initially navigating around the specific area with vision system until it looks for an object in the camera image. The robot approaches the object found in the field of view and checks it with the odor sensors if it is releasing odor. If so, the odor is classified and localized with the classification algorithm based on neural network The AMOR(Autonomous Mobile Olfactory Robot) was built up and used for the experiments. Experimental results on the classification and localization of odor sources show the validity of the proposed algorithm.

Odor Cognition and Source Tracking of an Intelligent Robot based upon Wireless Sensor Network (센서 네트워크 기반 지능 로봇의 냄새 인식 및 추적)

  • Lee, Jae-Yeon;Kang, Geun-Taek;Lee, Won-Chang
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.1
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    • pp.49-54
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    • 2011
  • In this paper, we represent a mobile robot which can recognize chemical odor, measure concentration, and track its source indoors. The mobile robot has the function of smell that can sort several gases in experiment such as ammonia, ethanol, and their mixture with neural network algorithm and measure each gas concentration with fuzzy rules. In addition, it can not only navigate to the desired position with vision system by avoiding obstacles but also transmit odor information and warning messages earned from its own operations to other nodes by multi-hop communication in wireless sensor network. We suggest the way of odor sorting, concentration measurement, and source tracking for a mobile robot in wireless sensor network using a hybrid algorithm with vision system and gas sensors. The experimental studies prove that the efficiency of the proposed algorithm for odor recognition, concentration measurement, and source tracking.