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Proceedings Paper

A UGV-based laser scanner system for measuring tree geometric characteristics
Author(s): Yonghui Wang; Yubin Lan; Yongjun Zheng; Kevin Lee; Suxia Cui; Jian-ao Lian
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Paper Abstract

This paper introduces a laser scanner based measurement system for measuring crop/tree geometric characteristics. The measurement system, which is mounted on a Unmanned Ground Vehicle (UGV), contains a SICK LMS511 PRO laser scanner, a GPS, and a computer. The LMS511 PRO scans objects within distance up to 80 meters with a scanning frequency of 25 up to 100Hz and with an angular resolution of 0.1667° up to 1°. With an Ethernet connection, this scanner can output the measured values in real time. The UGV is a WIFI based remotely controlled agricultural robotics system. During field tests, the laser scanner was mounted on the UGV vertically to scan crops or trees. The UGV moved along the row direction with certain average travel speed. The experimental results show that the UGV's travel speed significantly affects the measurement accuracy. A slower speed produces more accurate measuring results. With the developed measurement system, crop/tree canopy height, width, and volume can be accurately measured in a real-time manner. With a higher spatial resolution, the original data set may even provide useful information in predicting crop/tree growth and productivity. In summary, the UGV based measurement system developed in this research can measure the crop/tree geometric characteristics with good accuracy and will work as a step stone for our future UGV based intelligent agriculture system, which will include variable rate spray and crop/tree growth and productivity prediction through analyzing the measured results of the laser scanner system.

Paper Details

Date Published: 19 September 2013
PDF: 8 pages
Proc. SPIE 8905, International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications, 890532 (19 September 2013); doi: 10.1117/12.2042341
Show Author Affiliations
Yonghui Wang, Prairie View A&M Univ. (United States)
Yubin Lan, Southern Plains Agricultural Research Ctr. (United States)
Yongjun Zheng, China Agricultural Univ. (China)
Kevin Lee, Prairie View A&M Univ. (United States)
Suxia Cui, Prairie View A&M Univ. (United States)
Jian-ao Lian, Prairie View A&M Univ. (United States)

Published in SPIE Proceedings Vol. 8905:
International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications
Farzin Amzajerdian; Astrid Aksnes; Weibiao Chen; Chunqing Gao; Yongchao Zheng; Cheng Wang, Editor(s)

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