Autonomous guidance for rice transplanting using global positioning and gyroscopes

Nagasaka, Yoshisada; Umeda, Naonobu; Kanetai, Yutaka; Taniwaki, Ken; Sasaki, Yasuhiro

doi:10.1016/j.compag.2004.01.005

Cited by 136 publications

(59 citation statements)

References 7 publications

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“…Beside GPS errors of 1-2 cm, positioning inaccuracy observed in this study predominantly originated from undirected vehicle movements due to heaps and hollows of the ground surface. These errors could be compensated for by a gyroscope, which can level out unbalanced sensor movements caused by the vehicle (Nagasaka et al, 2004). Further, measurement signal processing delays caused position offsets, which have in part been addressed in other studies but are very specific to the respective vehicle construction.…”

Section: Assessment Of Position Accuracymentioning

confidence: 99%

Comparing mobile and static assessment of biomass in heterogeneous grassland with a multi-sensor system

Safari

Fricke

Reddersen

et al. 2016

J. Sens. Sens. Syst.

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Abstract. The present study aimed to test a mobile device equipped with ultrasonic and spectral sensors for the assessment of biomass from diverse pastures and to compare its prediction accuracy to that from static measurements. Prediction of biomass by mobile application of sensors explained > 63 % of the variation in manually determined reference plots representing the biomass range of each paddock. Accuracy of biomass prediction improved with increasing grazing intensity. A slight overestimation of the true values was observed at low levels of biomass, whereas an underestimation occurred at high values, irrespective of stocking rate and years. Prediction accuracy with a mobile application of sensors was always lower than when sensors were applied statically. Differences between mobile and static measurements may be caused by position errors, which accounted for 8.5 cm on average. Beside GPS errors (±1-2 cm horizontal accuracy and twice that vertically), position inaccuracy predominantly originated from undirected vehicle movements due to heaps and hollows on the ground surface. However, the mobile sensor system in connection with biomass prediction models may provide acceptable prediction accuracies for practical application, such as mapping. The findings also show the limits even sophisticated sensor combinations have in the assessment of biomass of extremely heterogeneous grasslands, which is typical for very leniently stocked pastures. Thus, further research is needed to develop improved sensor systems for supporting practical grassland farming.

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Section: Assessment Of Position Accuracymentioning

confidence: 99%

Comparing mobile and static assessment of biomass in heterogeneous grassland with a multi-sensor system

Safari

Fricke

Reddersen

et al. 2016

J. Sens. Sens. Syst.

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show abstract

“…A number of studies used the GPS as a base sensor for the navigation of agricultural tractors [1][2][3][4][5]. A GPS-based rice transplanter was developed, but it was limited by tree canopies and high-rise buildings that interfered with the signals [6]. To improve the GPS-based applications, studies related to signal acquisition in steel structures or buildings were established [7,8].…”

Section: Introductionmentioning

confidence: 99%

Navigation of an Autonomous Tractor for a Row-Type Tree Plantation Using a Laser Range Finder—Development of a Point-to-Go Algorithm

2015

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Abstract:It is challenging to develop a control algorithm that uses only one sensor to guide an autonomous vehicle. The objective of this research was to develop a control algorithm with a single sensor for an autonomous agricultural vehicle that could identify landmarks in the row-type plantation environment and navigate a vehicle to a point-to-go target location through the plantation. To enable such a navigation system for the plantation system, a laser range finder (LRF) was used as a single sensor to detect objects and navigate a full-size autonomous agricultural tractor. The LRF was used to control the tractor as it followed a path, and landmarks were detected "on-the-go" in real time. The landmarks were selected based on data for their distances calculated by comparison with the surrounding objects. Once the landmarks were selected, a target point was calculated from the landmarks, and the tractor was navigated toward the target. Navigation experiments were successfully conducted on the selected paths without colliding with the surrounding objects. A real time kinematic global positioning system (RTK GPS) was used to compare the positioning between the autonomous control and manual control. The results of this study showed that this control system could navigate the autonomous tractor to follow the paths, and the vehicle position differed from the manually driven paths by 0.264, 0.370 and 0.542 m for the wide, tight, and U-turn paths, respectively, with directional accuracies of 3.139°, 4.394°, and 5.217°, respectively, which are satisfactory for the autonomous operation of tractors on OPEN ACCESSRobotics 2015, 4 342 rubber or palm plantations. Therefore, this laser-based landmark detection and navigation system can be adapted to an autonomous navigation system to reduce the vehicle`s sensor cost and improve the accuracy of the positioning.

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“…The objective of this study is to develop an automatic navigation system that was developed on PZ60 rice transplanter based on RTK-GNSS navigation technology in the paper. The steering, transmission and transplanting control system of the rice transplanter were modified from manual control system to electronic control system [4][5][6][7] . The automatic navigation system integrating GNSS technology and fuzzy control strategies can control the rice transplanter trace the presetted path and achieve automatic navigation transplanting.…”

Section: Introductionmentioning

confidence: 99%

Automatic Navigation System Research for PZ60 Rice Planter

Wei

Zhang

Quan

et al. 2015

Computer and Computing Technologies in Agriculture VIII

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Abstract. In order to satisfy the agricultural demond of rice transplanting, the transplanter work should guarantee the escapement even in straight line transplanting that is convenient for field management and harvest later. Because of variable soil conditions and hard work environment, the driver driving level and the long boring driving to follow line is a big influence to the accuracy of the rice transplant. It is easy to produce overline, leak line and cause losses in yield. Aimed at above problem, this text introduces an automatic navigation system developed on PZ60 rice transplanter based on global navigation satellite system (GNSS). The steering, transmission and transplanting control system of the rice transplanter were modified from manual control system to electrohydraulic control system using electro-hydraulic proportional valve. According to the position information of the rice transplanter acquired from GNSS receiver and vehicle sensors, the close-loop feedback control system of steering was builded. The system can accurately control rice transplanter to follow row navigating and turn around at the end of field by the self-adaptive fuzzy control method. The road and field experiment results indicated that the lateral tracking error could be kept within 100 mm when the speed of the rice transplant is not greater than 1.0m/s. The control system can satisfy the requirment of rice transplanting.

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Autonomous guidance for rice transplanting using global positioning and gyroscopes

Cited by 136 publications

References 7 publications

Comparing mobile and static assessment of biomass in heterogeneous grassland with a multi-sensor system

Comparing mobile and static assessment of biomass in heterogeneous grassland with a multi-sensor system

Navigation of an Autonomous Tractor for a Row-Type Tree Plantation Using a Laser Range Finder—Development of a Point-to-Go Algorithm

Automatic Navigation System Research for PZ60 Rice Planter

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