Depth map construction with stereo vision for humanoid robot navigation

2016 ◽  
Author(s):  
M. I. Vargas-Signoret ◽  
M. Rojas-Romero ◽  
I. Trejo-Avila ◽  
J. Velasco-Avella ◽  
E. E. Robles-Martinez ◽  
...  
Keyword(s):  
Stereo Vision ◽  
Humanoid Robot ◽  
Robot Navigation ◽  
Depth Map ◽  
Map Construction

scholarly journals Estimation of Soil Surface Roughness Using Stereo Vision Approach

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4386
Author(s):  
Afshin Azizi ◽  
Yousef Abbaspour-Gilandeh ◽  
Tarahom Mesri-Gundoshmian ◽  
Aitazaz A. Farooque ◽  
Hassan Afzaal
Keyword(s):  
Surface Roughness ◽  
Stereo Vision ◽  
Agricultural Soils ◽  
Depth Map ◽  
Soil Surface ◽  
Regression Equations ◽  
Height Profile ◽  
Peak Fitting ◽  
Soil Surface Roughness ◽  
Tillage Operations

Soil roughness is one of the most challenging issues in the agricultural domain and plays a crucial role in soil quality. The objective of this research was to develop a computerized method based on stereo vision technique to estimate the roughness formed on the agricultural soils. Additionally, soil till quality was investigated by analyzing the height of plow layers. An image dataset was provided in the real conditions of the field. For determining the soil surface roughness, the elevation of clods obtained from tillage operations was computed using a depth map. This map was obtained by extracting and matching corresponding keypoints as super pixels of images. Regression equations and coefficients of determination between the measured and estimated values indicate that the proposed method has a strong potential for the estimation of soil shallow roughness as an important physical parameter in tillage operations. In addition, peak fitting of tilled layers was applied to the height profile to evaluate the till quality. The results of this suggest that the peak fitting is an effective method of judging tillage quality in the fields.

Active stereo vision-based mobile robot navigation for person tracking

2006 ◽  
Vol 13 (3) ◽  
pp. 203-222 ◽  
Author(s):  
V. Enescu ◽  
G. De Cubber ◽  
K. Cauwerts ◽  
H. Sahli ◽  
E. Demeester ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Stereo Vision ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Person Tracking ◽  
Active Stereo

Fast and accurate humanoid robot navigation guided by stereovision

2009 ◽  
Author(s):  
Chen Guod ◽  
Ming Xie ◽  
Zeyang Xia ◽  
Lining Sun ◽  
Junhong Ji ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Robot Navigation

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.

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