Title: Pose and Position Estimation of Dozer Blade in 3-Dimensional by Integration of IMU with Two RTK GPSs
Abstract:Pose and Position Estimation of Dozer Blade in 3-Dimensional by Integration of IMU with Two RTK GPSs Dong-Ik Sun, Sang Ho Kim, Yong Seok Lee, Sang Keun Lee, and Chang Soo Han Pages 991-996 (2017 Proce...Pose and Position Estimation of Dozer Blade in 3-Dimensional by Integration of IMU with Two RTK GPSs Dong-Ik Sun, Sang Ho Kim, Yong Seok Lee, Sang Keun Lee, and Chang Soo Han Pages 991-996 (2017 Proceedings of the 34rd ISARC, Taipei, Taiwan, ISBN 978-80-263-1371-7, ISSN 2413-5844) Abstract: Construction equipment such as excavator, dozer, loader with automation system help the efficiency, accuracy to improve and reduces the cost. And the phenomena about avoiding particular occupation and a shortage of manpower in construction field as the low birth rate and aging has recently come up to the fore as a serious social issue. But, those automation system embeded with know-how about dozer construction would be a solution. In order to implement the automation system of dozer, machine guidance must be done before that. The term of Machine Guidance is used to describe a wide range of techniques which improve the productivity of agricultural, mining and construction equipment. Because the automation system can be performed by receiving the movement information like position, attitude, orientation, velocity etc through the sensor systems. Briefly, if machine guidance is performed greatly, the achievement of dozer machine system could be better. This paper will describe the method about attitude and position estimation of dozer blade by integration of IMU(Inertial Measurement Unit) devices with Two RTK(Real-Time Kinematic) GPSs. These sensor systems are installed to the dozer for doing experiment. Finally, the proposed method is verified by experimental result. Keywords: Machine Guidance, Dozer, Sensor Fusion DOI: https://doi.org/10.22260/ISARC2017/0137 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to MendeleyRead More
Publication Year: 2017
Publication Date: 2017-07-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 8
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