TELEOPERATION PLATFORM FOR HST DRIVE AGRICULTURAL VEHICLE

Agriculture in the U.K. has, since the late 1940s, enjoyed government subsidy and insulation from free market forces. However, the post-war philosophy of ‘every acre counts’ no longer holds true in the face of surplus production and a growing public awareness of the countryside and environmental issues. Legislation relating to water pollution, public rights of way and price support mechanisms are all contributory factors to the radical changes which agriculture is undergoing at the present time. Investigations have shown a need within agriculture for the efficient use and handling of data relating to the land, and a need for new technology to exploit the inherent spatial variability of, for example, the soil. This paper will discuss the development of an agricultural vehicle positioning instrument and future research which will address the needs which have been identified.

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Performance Evaluation of Autonomous Driving Control Algorithm for a Crawler-Type Agricultural Vehicle Based on Low-Cost Multi-Sensor Fusion Positioning

Applied Sciences ◽

10.3390/app10134667 ◽

2020 ◽

Vol 10 (13) ◽

pp. 4667 ◽

Cited By ~ 1

Author(s):

Joong-hee Han ◽

Chi-ho Park ◽

Jay Hyoun Kwon ◽

Jisun Lee ◽

Tae Soo Kim ◽

...

Keyword(s):

Control Algorithm ◽

Low Cost ◽

Autonomous Driving ◽

Maximum Error ◽

Sensor Technology ◽

Motion Sensor ◽

Integration Algorithm ◽

Sensor Module ◽

Agricultural Vehicle ◽

Mean Square Errors

The agriculture sector is currently facing the problems of aging and decreasing skilled labor, meaning that the future direction of agriculture will be a transition to automation and mechanization that can maximize efficiency and decrease costs. Moreover, interest in the development of autonomous agricultural vehicles is increasing due to advances in sensor technology and information and communication technology (ICT). Therefore, an autonomous driving control algorithm using a low-cost global navigation satellite system (GNSS)-real-time kinematic (RTK) module and a low-cost motion sensor module was developed to commercialize an autonomous driving system for a crawler-type agricultural vehicle. Moreover, an autonomous driving control algorithm, including the GNSS-RTK/motion sensor integration algorithm and the path-tracking control algorithm, was proposed. Then, the performance of the proposed algorithm was evaluated based on three trajectories. The Root Mean Square Errors (RMSEs) of the path-following of each trajectory are calculated to be 9, 7, and 7 cm, respectively, and the maximum error is smaller than 30 cm. Thus, it is expected that the proposed algorithm could be used to conduct autonomous driving with about a 10 cm-level of accuracy.

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