Determination of slope class at Stesen Janakuasa Sultan Mahmud, Kuala Berang, Terengganu using geological terrain mapping method

2019 ◽  
Author(s):  
Mohamad Anuri Ghazali ◽  
Mohd Rozi Umor ◽  
Khairul Ikhwan Mazlan
Keyword(s):  
Mapping Method ◽  
Terrain Mapping ◽  
Slope Class

scholarly journals RGB–D terrain perception and dense mapping for legged robots

2016 ◽  
Vol 26 (1) ◽  
pp. 81-97 ◽  
Author(s):  
Dominik Belter ◽  
Przemysław Łabecki ◽  
Péter Fankhauser ◽  
Roland Siegwart
Keyword(s):  
Stereo Vision ◽  
Uncertainty Propagation ◽  
Depth Map ◽  
Mapping Method ◽  
Spatial Uncertainty ◽  
Legged Robots ◽  
Walking Robots ◽  
Terrain Mapping ◽  
Terrain Elevation ◽  
Uncertainty Models

Abstract This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used to produce a dense depth map. The model for the uncertainty of the stereo vision camera is based on uncertainty propagation from calibration, through undistortion and rectification algorithms, allowing calculation of the uncertainty of measured 3D point coordinates. The proposed uncertainty models were used for the construction of a terrain elevation map using the Videre Design STOC stereo vision camera and Kinect-like range sensors. We provide experimental verification of the proposed mapping method, and a comparison with another recently published terrain mapping method for walking robots.

scholarly journals 3D ONLINE TERRAIN MAPPING WITH SCANNING RADAR SENSORS

2020 ◽  
Vol V-1-2020 ◽  
pp. 125-132
Author(s):  
C. Weidinger ◽  
T. Kadiofsky ◽  
P. Glira ◽  
C. Zinner ◽  
W. Kubinger
Keyword(s):  
Autonomous Vehicle ◽  
Digital Terrain Model ◽  
Ground Truth ◽  
Mapping Method ◽  
Accuracy Evaluation ◽  
Terrain Mapping ◽  
Ground Truth Data ◽  
Radar Sensors ◽  
Core Requirements ◽  
Autonomous Vehicle Navigation

Abstract. Environmental perception is one of the core requirements in autonomous vehicle navigation. If exposed to harsh conditions, commonly deployed sensors like cameras or lidars deliver poor sensing performance. Millimeter wave radars enable robust sensing of the environment, but suffer from specular reflections and large beamwidths. To incorporate the sensor noise and lateral uncertainty, a new probabilistic, voxel-based recursive mapping method is presented to enable online terrain mapping using scanning radar sensors. For map accuracy evaluation, test measurements are performed with a scanning radar sensor in an off-road area. The voxel map is used to derive a digital terrain model, which can be compared with ground-truth data from an image-based photogrammetric reconstruction of the terrain. The method evaluation shows promising results for terrain mapping solely performed with radar scanners. However, small terrain structures still pose a problem due to larger beamwidths in comparison to lidar sensors.

PHOTOGRAMMETRIC DETERMINATION OF TERRAIN SLOPE USING SIMPLE EQUIPMENT

1985 ◽  
Vol 65 (1) ◽  
pp. 123-131
Author(s):  
G. WILSON
Keyword(s):  
Key Words ◽  
Aerial Photographs ◽  
Terrain Analysis ◽  
Terrain Mapping ◽  
Contour Map ◽  
Photo Interpretation ◽  
Aerial Photos ◽  
Contour Maps ◽  
Time Element

Slope is an important factor in terrain mapping and can be determined from contour maps or aerial photographs. Previously methods have been proposed to reduce the time element using contour maps. This paper describes and demonstrates a technique whereby aerial photographs can be used effectively when photogrammetric equipment and reliable contour maps are not available. Accuracy with the method is illustrated by comparison to slope determined from a contour map and a single computation sheet is provided for inclusion in a handbook or field guide. Key words: Slope measurement, terrain analysis, pedotechnical interpretations, aerial photos, photo interpretation, photogrammetry

scholarly journals Application of the UHPLC-DIA-HRMS Method for Determination of Cheese Peptides

Foods ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 979
Author(s):  
Georg Arju ◽  
Anastassia Taivosalo ◽  
Dmitri Pismennoi ◽  
Taivo Lints ◽  
Raivo Vilu ◽  
...  
Keyword(s):  
Selection Criteria ◽  
High Performance ◽  
Milk Protein ◽  
High Resolution Mass Spectrometry ◽  
Peptide Mapping ◽  
Mapping Method ◽  
Data Independent Acquisition ◽  
Cheese Peptides ◽  
Analytical Gradients

Until now, cheese peptidomics approaches have been criticised for their lower throughput. Namely, analytical gradients that are most commonly used for mass spectrometric detection are usually over 60 or even 120 min. We developed a cheese peptide mapping method using nano ultra-high-performance chromatography data-independent acquisition high-resolution mass spectrometry (nanoUHPLC-DIA-HRMS) with a chromatographic gradient of 40 min. The 40 min gradient did not show any sign of compromise in milk protein coverage compared to 60 and 120 min methods, providing the next step towards achieving higher-throughput analysis. Top 150 most abundant peptides passing selection criteria across all samples were cross-referenced with work from other publications and a good correlation between the results was found. To achieve even faster sample turnaround enhanced DIA methods should be considered for future peptidomics applications.

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