Media: Performance_Evaluation_of_Autonomous_Driving_Contr.pdf

Media Performance_Evaluation_of_Autonomous_Driving_Contr.pdf

Source https://www.researchgate.net/publication/342730706_Performance_Evaluation_of_Autonomous_Driving_Control_Algorithm_for_a_Crawler-Type_Agricultural_Vehicle_Based_on_Low-Cost_Multi-Sensor_Fusion_Positioning
Authors Joong‐hee Han, Chi‐ho Park, Jay Hyoun Kwon, Jisun Lee, Tae Soo Kim, Young Yoon Jang
Received 15 June 2020
Accepted 3 July 2020
Published 6 July 2020
Upload Saturday, August 13, 2022; wabis
Size 1.40 MB


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


AU - Han, Joong-hee
AU - Park, Chi-ho
AU - Kwon, Jay
AU - Lee, Jisun
AU - Kim, Tae
AU - Jang, Young
PY - 2020/07/06
SP - 4667
T1 - Performance Evaluation of Autonomous Driving Control Algorithm for a Crawler-Type Agricultural Vehicle Based on Low-Cost Multi-Sensor Fusion Positioning
VL - 10
DO - 10.3390/app10134667
JO - Applied Sciences
ER -

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