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Dead-reckoning sensor system and tracking algorithm for 3-D pipeline mapping
Authors:Dongjun Hyun  Hyun Seok Yang  Hyuk-Sung Park  Hyo-Jun Kim
Affiliation:1. Department of Mechanical Engineering, Yonsei University, 262, Seongsanno, Seodamun-gu, Seoul 120-749, Republic of Korea;2. Robogen, RM133, Yonsei Engineering Research Park, 262, Seongsanno, Seodaemun-gu, Seoul 120-749, Republic of Korea;3. Department of Mechanical Engineering, Kangwon National University, KyoDong, Samcheok, Kangwon Do 245-711, Republic of Korea;1. China Academy of Launch Vehicle Technology, Beijing 100076, People’s Republic of China;2. School of Instrumentation Science and Optoelectronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, People’s Republic of China;1. Departamento de Física, Universidade Estadual de Londrina, Caixa Postal 6001, Londrina, Paraná, Brazil;2. Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland;1. EPHE-CHArt, 4-14 rue Ferrus, 75014 Paris, France;2. University of Bordeaux and CNRS USR 3413: Sommeil, Attention et Neuropsychiatrie, Bordeaux, France;3. Institut de recherche biomédicale des armées (IRBA), BP 73, 91223 Brétigny-sur-Orge cedex, France;4. Medical Engineering and Rehabilitation, Pierre and Marie Curie University, 4, Place Jussieu, 75005 Paris, France;1. School of Display and Chemical Engineering, Yeungnam University, 214-1, Dae-dong, Gyeongsan, Gyeongbuk 712-749, Republic of Korea;2. Department of Advanced Energy Material Science and Engineering, Catholic University of Daegu, Gyeongbuk 712-702, Republic of Korea;1. Wireless Technologies Laboratory of the ICT Centre at CSIRO, Australia;2. School of Civil and Environmental Engineering, University of New South Wales, Sydney NSW 2052, Australia;1. Key Laboratory of Brain Functional Genomics (MOE & STCSM), Key Laboratory of Magnetic Resonance, Institute of Cognitive Neuroscience, School of Psychology and Cognitive Science, East China Normal University, Shanghai 20062, China;2. Shanghai Medical Instrumentation College, University of Shanghai Science and Technology, Shanghai 200093, China;3. Center for Developmental Neuropsychiatry, Columbia University Department of Psychiatry & New York State Psychiatric Institute, Unit 74, 1051 Riverside Drive, New York, NY 10032, USA;4. Epidemiology Division & MRI Unit, Columbia University Department of Psychiatry & New York State Psychiatric Institute, Unit 24, 1051 Riverside Drive, New York, NY 10032, USA
Abstract:A dead-reckoning sensor system and a tracking algorithm for 3-D pipeline mapping are proposed for a tap water pipeline for which the diameter is small and the inner surface is rough due to pipe scales. The goals of this study are to overcome the performance limitations of small and low-grade sensors by combining various sensors with complementary functions and achieve robustness against a severe environment. A dead-reckoning sensor system consists of a small, low-cost micro electromechanical system inertial measurement unit (MEMS IMU) and an optical navigation sensor (used in laser mice). A tracking algorithm consists of a multi-rate extended Kalman filter (EKF) to fuse redundant and complementary data from the MEMS IMU and the optical navigation sensor and a geometry compensation method to reduce position estimation error using the end point of the pipeline. Two sets of experimental data have been obtained by driving a radio-controlled car equipped with the sensor system in a 3-D pipeline and on asphalt pavement. Our study can be used to estimate the path of a 3-D pipeline or mobile robots.
Keywords:
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