Stereo-based visual navigation of mobile robots in unknown environments

Soltani, Hossein; Taghirad, Hamid D.; Ravari, A. R. Norouzzadeh

doi:10.1109/iraniancee.2012.6292489

Cited by 7 publications

(8 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most of the VO methods that have been proposed in existing literature used either stereo or monocular cameras. The systems that used a binocular camera can be considered as stereo VO systems, as implemented by , whereas those that used a monocular camera can be considered as monocular VO systems, as applied by . The binocular camera requires more effort in calibration than the monocular camera, and errors in calibration directly affect the motion estimation process .…”

Section: Prior Related Workmentioning

confidence: 99%

Adaptive‐search template matching technique based on vehicle acceleration for monocular visual odometry system

Aqel

Marhaban

Saripan

2016

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

One of the important tasks of an autonomous mobile vehicle is the reliable and fast estimation of its position over time. This paper presents the development of an adaptive technique to hasten and improve the quality of correlation-based template matching for monocular visual odometry systems that estimate the relative motion of ground vehicles in low-textured environments. Moreover, the factors that can affect the maximum permissible vehicle driving speed were determined and the related equations were derived. The developed system uses a single downward-facing monocular camera installed at an optimum location to avoid the negative effect of directional sunlight and shadows which can disturb the correlation. In addition, the normalized cross-correlation method is implemented to calculate the pixel displacement between image frames. Although this method is highly effective for template matching because of its invariance to linear brightness and contrast variations, it incurs high computational cost. Thus, the optimal sizes of image template and matching search area are selected and their locations are dynamically changed according to vehicle acceleration, in order to achieve a compromise between the performance and the computational cost of correlation. The proposed technique increases the allowable vehicle driving speed and reduces the probability of template false-matching. Moreover, compared to traditional full search matching techniques, the adaptive technique demonstrates high efficiency and accuracy and improves the quality and speed of the correlation with more than 87% of reduction in computational cost.

show abstract

Section: Prior Related Workmentioning

confidence: 99%

Adaptive‐search template matching technique based on vehicle acceleration for monocular visual odometry system

Aqel

Marhaban

Saripan

2016

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

show abstract

“…The systems that use binocular cameras are called stereo VO systems, as implemented by Refs. , whereas systems that use monocular cameras are called monocular VO systems, as applied by Refs. .…”

Section: Prior Related Workmentioning

confidence: 99%

Estimation of image scale variations in monocular visual odometry systems

Aqel

Marhaban

Saripan

2016

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

Reliable estimation of the vehicle position is the main prerequisite in all autonomous mobile robotic applications. Imagescale uncertainty in correlation-based monocular visual odometry systems negatively affects the accuracy of the vehicle motion estimation. This paper presents the development of a new technique and algorithm to estimate image-scale variations due to camera height fluctuations when the vehicle is driven on uneven terrains or when the height of vehicle from ground changes as a result of changes in load or number of passengers in the vehicle. This technique depends on marking the image frames by two red laser points, as independent reference points, which have a certain distance between them. The image-scale variations can be estimated by monitoring the variations in the distance between these two reference points. The proposed technique eliminates the need for camera recalibration and the use of sensors to measure the variations of camera height from ground, such as laser range finders and acceleration sensors. The developed system uses a single downward-facing monocular camera supported by a lighting module and installed underneath the test vehicle to avoid the negative effect of directional sunlight and shadows, which can disturb the correlation. Indoor and outdoor experiments have proven the efficiency of the suggested technique in resolving image-scale uncertainty and ensuring an image-scale-invariant correlation-based matching, with only less than 5% additional computational time.

show abstract

“…Vision-based mobile robot mostly equipped at least with one camera, and others equipped with dual or more camera at the same time [8]. Research has been conducted on building a map of static obstacles, for examples building an unknown outdoor environmental map as [9]. In this case, a local and global map of the environment was developed.…”

Section: Introductionmentioning

confidence: 99%

“…The method utilized the point cloud model combined with visual odometry. This combination is used to assist the robot in path planning to the desired location in the outdoor environment [9]. This model was having a shortcoming in the ability of a robot to anticipate changes of the obstacles' position since its only deal with static obstacles.…”

Section: Introductionmentioning

confidence: 99%

Grid-Edge-Depth Map Building Employing Sad With Sobel Edge Detector

Rahmani

Harjoko

Priyambodo

2017

International Journal on Smart Sensing and Intelligent Systems

View full text Add to dashboard Cite

-This paper presents a new method of a map building which is suitable for a wheeled robot. The 2D map represents the obstacle's position and distance in the environment. The information of the obstacles obtained from a calibrated stereo camera. The stereo images size were 320x240 pixels. Hereafter the images were rectified and the disparity map was built using a Sum of Absolute Difference (SAD) algorithm. The depth map was calculated using disparity map, focal length, and baseline parameter values. In order to detect the obstacles, Sobel edge detection was implemented. The edge detection image was compared and substituted with the depth map which is resulting edge-depth map. The edge-depth map was divided into 25 grids (5 grids horizontal and 5 grids vertical). Finally, the minimum depth of detected obstacles for each grid was calculated. This process was resulting in a grid-edge-depth map (GED map). The proposal has been tested with a mobile robot in 5x3 meters living environment. Finally, experimental results are presented. The average error of feature points in the previous study was 5.40 cm, whereas in this study is 3.82 cm. There has been a decrease in the measurement gap of 29.26% from the previous study.

show abstract

Stereo-based visual navigation of mobile robots in unknown environments

Cited by 7 publications

References 22 publications

Adaptive‐search template matching technique based on vehicle acceleration for monocular visual odometry system

Adaptive‐search template matching technique based on vehicle acceleration for monocular visual odometry system

Estimation of image scale variations in monocular visual odometry systems

Grid-Edge-Depth Map Building Employing Sad With Sobel Edge Detector

Contact Info

Product

Resources

About