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Open AccessArticle

Heading Estimation of Robot Combine Harvesters during Turning Maneuveres

1
Graduate School of Agriculture, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, Japan
2
Department of Food Engineering and Tea Technology, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh
3
Research Faculty of Agriculture, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo 060-8589, Japan
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(5), 1390; https://doi.org/10.3390/s18051390
Received: 9 March 2018 / Revised: 17 April 2018 / Accepted: 17 April 2018 / Published: 1 May 2018
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
Absolute heading is an important parameter for a robot combine harvester or a robot tracked combine harvester, especially while it is turning, but due to the rapid turning of robot combine harvesters, its inertial measurement unit gives a gyro measurement bias that causes heading drift. Our research goal is to estimate the absolute heading of robot combine harvesters by compensating this gyro measurement bias during non-linear turning maneuvers. A sensor fusion method like the extended Kalman filter combined with the tracked combine harvester dynamic model and sensor measurements was used to estimate the absolute heading of a robot combine harvester. Circular, sinusoidal and concave shapes were used to evaluate the estimated heading produced by the sensor fusion method. The results indicate that the estimated heading is better than measured heading which was calculated from the integration of yaw rate gyro measurements, and the root mean square errors (RMSEs) for estimated headings are smaller than the measured headings. In practics, the target of this paper is thus the estimation of a heading or absolute heading that is bias compensated, and can be further used to calculate the exact crop periphery for automatic path planning of robot combine harvesters. View Full-Text
Keywords: tracked combine harvester; dynamic model; extended Kalman filter; global positioning system; inertial measurement unit; crop periphery tracked combine harvester; dynamic model; extended Kalman filter; global positioning system; inertial measurement unit; crop periphery
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Rahman, M.M.; Ishii, K. Heading Estimation of Robot Combine Harvesters during Turning Maneuveres. Sensors 2018, 18, 1390.

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