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

Han, Joong-hee; Park, Chi-Ho; Kwon, Jae-Sool; Lee, Jisun; Kim, Tae Soo; Jang, Young Yoon

doi:10.3390/app10134667

Cited by 29 publications

(20 citation statements)

References 9 publications

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“…The traditional literature fails to include an analysis to measure the efficiency value, which seriously affects the evaluation of the performance of agricultural GD. Therefore, an unexpected output model under the global benchmark was constructed to make up for the above shortcomings in this study [28].…”

Section: Information Communication Technologymentioning

confidence: 99%

Green Agricultural Development Based on Information Communication Technology and the Panel Space Measurement Model

Zhang

Chen

2021

Sustainability

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This study was conducted to promote the construction of China’s ecological civilization; to reduce harm to the environment; to quantify the performance of agricultural green development (GD); and to truly achieve green, sustainable, and healthy agricultural development. From the perspectives of resources and the environment, first, information communication technology and the panel space measurement (PSM) model were adopted to analyze relevant indicator data from 2000 to 2019 in China’s 30 provinces. Second, China’s agriculture was measured to explore the overall characteristics, temporal changes, and regional differences of agricultural development. A panel data measurement model was constructed using the generalized least squares method, and the main factors affecting performance development were analyzed, which were verified by giving examples. Third, the governance countermeasures and improvement directors were proposed for agricultural GD in China. It is found that the driving force of performance of agricultural GD in China mainly depends on technological progress and that technological efficiency determines the speed of agricultural development. The regional differences in performance of agricultural GD are obvious in China. The growth in the performance of agricultural GD in the eastern region is much higher than that of the central, western, and northeast regions. In addition, the results show that the performance of agricultural GD is extremely positively correlated with the agricultural economic level, fiscal support for agriculture policy, and the industrialization process and that it is extremely negatively correlated with the level of opening-up, adjustment of agricultural structure, and the environmental regulatory capability of the government. As a result, this study can provide some ideas for the realization of agriculture GD in China.

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Section: Information Communication Technologymentioning

confidence: 99%

Green Agricultural Development Based on Information Communication Technology and the Panel Space Measurement Model

Zhang

Chen

2021

Sustainability

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“…Every frame packet is composed of 7 OFDM symbols with a duration of 86.31 ms, which are obtained due to the coherence time (10 s) [24]. One of the OFDM symbols is a pilot to estimate the channel to perform the zero-forcing equalization which is calculated as we can see in (6). The zero-forcing consists in applying the inverse of the estimated channel calculated with the pilot symbol.…”

Section: Orthogonal Frequency-division Multiplexing (Ofdm)mentioning

confidence: 99%

“…In ( 5) is shown a simple equation of a transmitted signal in which Y(f) means the signal affected by a channel, the X(f) refers to the raw signal and the H(f) means the channel response. The received pilot is compared to the transmitted one to take a value of how the channel changes and the OFDM symbols are multiplied by the inverse of the received channel response as in (6).…”

Section: Orthogonal Frequency-division Multiplexing (Ofdm)mentioning

confidence: 99%

“…Remote sensing became an extended study focus making use of new technologies such as light detection and ranging (LIDAR), artificial intelligence (AI) [2], machine learning [3], geocoding algorithms [4], deep convolutional neural networks [5] or multi-sensor fusion positioning [6], being part of some examples of the wide range of technologies that sensing uses.…”

Section: Introductionmentioning

confidence: 99%

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NVIS Multicarrier Modulations for Remote-Sensor Applications

Maso

Gonzalez

Male

et al. 2020

Sensors

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The number of Internet of Things (IoT) devices has experienced a large growth during the last decade, as well as the data volume gathered from remote sensors. Satellites are still a suitable communication method and may be preferable for a remote ubiquitous sensor network (USN), which sometimes are located in places without much communications infrastructure where coverage is the principal drawback. Alternatively, the proposed solution for this article aims at a near-vertical incidence skywave (NVIS) channel for high frequencies (HF) with a low-cost platform, allowing a low-power transmissions coverage area up to 250 km for USN. The HF standards are focused on generic communication channels not being robust for NVIS communications. In this article we study and test an alternative based on orthogonal frequency-division multiplexing (OFDM) modulations to make them more robust and less dependent on the channel NVIS communications. For that purpose, we test the HF standard modulations and a designed OFDM modulation to prove the robustness of each. This study has been tested between Barcelona and Tarragona, using different transmission power levels and modulation orders.

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“…An error state Kalman filter is used to fuse the measurements. In contrast to conventional systems where the IMU is used as a reference sensor (see [ 17 , 18 , 19 , 20 , 21 ]), here the wheel speed sensors, a yaw rate, and a dynamic model for tracked vehicles are used to propagate the filter state. This allows to propagate the vehicle’s state with higher accuracy at low dynamic applications.…”

Section: Introductionmentioning

confidence: 99%

Bridging GNSS Outages with IMU and Odometry: A Case Study for Agricultural Vehicles

Reitbauer

Schmied

2021

Sensors

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Nowadays, many precision farming applications rely on the use of GNSS-RTK. However, when it comes to autonomous agricultural vehicles, GNSS cannot be used as a stand-alone system for positioning. To ensure high availability and robustness of the positioning solution, GNSS-RTK must be fused with additional sensors. This paper presents a novel sensor fusion algorithm tailored to tracked agricultural vehicles. GNSS-RTK, an IMU and wheel speed sensors are fused in an error-state Kalman filter to estimate position and attitude of the vehicle. An odometry model for tracked vehicles is introduced which is used to propagate the filter state. By using both IMU and wheel speed sensors, specific motion characteristics of tracked vehicles such as slippage can be included in the dynamic model. The presented sensor fusion algorithm is tested at a composting site using a tracked compost turner. The sensor measurements are recorded using the Robot Operating System (ROS). To analyze the achievable accuracies for position and attitude of the vehicle, a precise reference trajectory is measured using two robotic total stations. The resulting trajectory of the error-state filter is then compared to the reference trajectory. To analyze how well the proposed error-state filter is suited to bridge GNSS outages, GNSS outages of 30 s are simulated in post-processing. During these outages, the vehicle’s state is propagated using the wheel speed sensors, IMU, and the dynamic model for tracked vehicles. The results show that after 30 s of GNSS outage, the estimated horizontal position of the vehicle still has a sub-decimetre accuracy.

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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

Cited by 29 publications

References 9 publications

Green Agricultural Development Based on Information Communication Technology and the Panel Space Measurement Model

Green Agricultural Development Based on Information Communication Technology and the Panel Space Measurement Model

NVIS Multicarrier Modulations for Remote-Sensor Applications

Bridging GNSS Outages with IMU and Odometry: A Case Study for Agricultural Vehicles

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