Requirements for agricultural and construction machinery drivetrains derived from “autonomous driving”

2018 ◽  
pp. III-105-III-106
Author(s):  
S. Prebeck ◽  
M. Hiemer
CICTP 2020 ◽  
2020 ◽  
Author(s):  
Kun Jiang ◽  
Yunlong Wang ◽  
Shengjie Kou ◽  
Diange Yang
Keyword(s):  

2013 ◽  
Vol 133 (9) ◽  
pp. 595-598
Author(s):  
Kenji SUZUKI ◽  
Hisaaki ISHIDA ◽  
Hirofumi INOSE ◽  
Rui KOBAYASHI
Keyword(s):  

2020 ◽  
Vol 2020 (14) ◽  
pp. 306-1-306-6
Author(s):  
Florian Schiffers ◽  
Lionel Fiske ◽  
Pablo Ruiz ◽  
Aggelos K. Katsaggelos ◽  
Oliver Cossairt

Imaging through scattering media finds applications in diverse fields from biomedicine to autonomous driving. However, interpreting the resulting images is difficult due to blur caused by the scattering of photons within the medium. Transient information, captured with fast temporal sensors, can be used to significantly improve the quality of images acquired in scattering conditions. Photon scattering, within a highly scattering media, is well modeled by the diffusion approximation of the Radiative Transport Equation (RTE). Its solution is easily derived which can be interpreted as a Spatio-Temporal Point Spread Function (STPSF). In this paper, we first discuss the properties of the ST-PSF and subsequently use this knowledge to simulate transient imaging through highly scattering media. We then propose a framework to invert the forward model, which assumes Poisson noise, to recover a noise-free, unblurred image by solving an optimization problem.


Author(s):  
A. D. Terenteva

In civil engineering in Russia, trenching for utilities is currently under digging. To perform such works, it is necessary to use high-precision construction machinery, because inaccurate performance of works can lead to the break down of existing utilities, thereby affecting the residents of nearby houses and demanding the additional works for renewal.The most universal labour saver to perform construction works is hydraulic driven single-bucket excavators, which provide up to 38% of works. Therefore, to improve technical characteristics that affect the accuracy of the work performed is an important task.High requirements for the performance of works are defined by existing construction regulations: an allowable soil layer to remain is at most 0.05 m. To fulfil such requirements, an exact assessment of the working mechanism position and a trench profile is necessary.Examination of a manually operated digging process shows that an operator provides operations untimely, however an automated control system can solve this problem. Dynamic phenomena in the working mechanism have the greatest impact on the accuracy of the works performed.To assess the bucket digging edge position accuracy, a mathematical model of the working mechanism has been created. Based on the cycle scheme of the working process, the excessive displacements of the hydraulic cylinder rods under the load are taken into account. By the end of the cycle, the difference between the specified and obtained positions along the vertical coordinate has been 0.0892 m.A dynamic error of the hydraulic drive system of the working mechanism is considered as a sum of the error due to excessive displacements of the hydraulic cylinder rods and the error due to delay of the hydraulic drive, with the latter being calculated for the average time of delay taking into account the data available in the literature. The total error of the bucket digging edge position of the working mechanism is 0.1176 m, which is 2 times more than the value of 0.05 mConformity of all the links with specification requirements does not guarantee compliance with the required displacement accuracy of the bucket digging edge, and, thus, the soil layer to remain in the base of the trench can exceed the regulated value of 0.05 m.


2018 ◽  
Author(s):  
Yi Chen ◽  
Sagar Manglani ◽  
Roberto Merco ◽  
Drew Bolduc

In this paper, we discuss several of major robot/vehicle platforms available and demonstrate the implementation of autonomous techniques on one such platform, the F1/10. Robot Operating System was chosen for its existing collection of software tools, libraries, and simulation environment. We build on the available information for the F1/10 vehicle and illustrate key tools that will help achieve properly functioning hardware. We provide methods to build algorithms and give examples of deploying these algorithms to complete autonomous driving tasks and build 2D maps using SLAM. Finally, we discuss the results of our findings and how they can be improved.


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