Research on Combine Harvester Positioning algorithm and Aided-navigation System

Chen, Jin; Yang, Guangjing; Xu, Kai; Cai, Yangyang

doi:10.2991/ameii-15.2015.158

Cited by 2 publications

(1 citation statement)

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“…However, during harvest the driver needs to continuously adjust those parameters such as speed, direction as well as cutting width [1,2], which inevitably increases operator fatigue. The invention of the automatic navigation technology of the harvester can effectively reduce the driver s work intensity while improving the operating efficiency, which is of great significance [3].…”

Section: Introductionmentioning

confidence: 99%

Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision

et al. 2020

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A cut-edge detection method based on machine vision was developed for obtaining the navigation path of a combine harvester. First, the Cr component in the YCbCr color model was selected as the grayscale feature factor. Then, by detecting the end of the crop row, judging the target demarcation and getting the feature points, the region of interest (ROI) was automatically gained. Subsequently, the vertical projection was applied to reduce the noise. All the points in the ROI were calculated, and a dividing point was found in each row. The hierarchical clustering method was used to extract the outliers. At last, the polynomial fitting method was used to acquire the straight or curved cut-edge. The results gained from the samples showed that the average error for locating the cut-edge was 2.84 cm. The method was capable of providing support for the automatic navigation of a combine harvester.

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Section: Introductionmentioning

confidence: 99%

Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision

et al. 2020

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Harvester Evaluation Using Real-Time Kinematic GNSS and Hiring Service Model

et al. 2021

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To reduce human drudgery and the risk of labor shortages in the Asian developing countries, the appropriate introduction of agricultural machinery, especially combine harvesters, is an urgent task. Custom hiring services (CHSs) are expected to contribute to making paddy harvesters prevalent in developing countries; however, the economic performance has been rarely quantified. The study was carried out to precisely evaluate the machine performance attributes of medium and large combine harvesters using the real-time kinematic (RTK) global navigation satellite system (GNSS) and to estimate the economic performance of CHSs of paddy harvesters in Japan, as a typical case of Asian countries. The financial profitability was evaluated by four major indicators: net present value, benefit–cost ratio, internal rate of return, and payback period. The financial indicators showed that both types of harvester could be considered financially viable. Thus, the investment in combine harvesters can be highly profitable for CHS business by a local service provider and custom-hire entrepreneur, providing a great opportunity to use a combine harvester without initial investment by general farmers. The findings demonstrated the high feasibility of CHSs of paddy harvesters in Japan, while they highlighted that further study is needed to estimate the feasibility of CHS in the other Asian developing countries.

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Research on Combine Harvester Positioning algorithm and Aided-navigation System

Cited by 2 publications

References 0 publications

Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision

Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision

Harvester Evaluation Using Real-Time Kinematic GNSS and Hiring Service Model

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