Intelligent Design and Algorithms to Control a Stereoscopic Camera on a Robotic Workspace

Papoutsidakis, Michail; Kalovrektis, Κonstantinos; Drosos, Christos; Stamoulis, George

doi:10.5120/ijca2017914495

Cited by 6 publications

(6 citation statements)

References 8 publications

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“…The calibration process used a toolbox by Jean-Yves Bouguet [14,15]. Both cameras connected to the computer via a USB port [20][21] [22]. Figure 1 and Figure 2 show our experimental robot this study.…”

Section: Methodsmentioning

confidence: 99%

Early Model of Vision-Based Obstacle Mapping Utilizing Grid-Edge-Depth Map

Rahmani,

Harjoko,

Priyambodo

et al. 2019

IJEAT

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This paper described a new method of obstacle mapping in an indoor environment utilizing a Grid-edge-depth map. The Grid-edge-depth map contained the information of distance and relative position of the object in the front of the robot. This mapping method utilized this information to mark off the visible obstacle/s in a particular virtual map. The 2D map created as a representative of the environment using a 300 by 500 pixels image. Every pixel represents a one by one cm of the environment and the obstacle's size. The obstacle's size was 30 by 30 pixels when it mapped by the system. It was a fixed size in the mapping process since the system cannot calculate the dimension of the detected obstacle. If the obstacle detected, the system checked its distance in GED-map. Then the system calculated the obstacle’s position against the goal, and finally map it in the 2D map. In this case, the proposed method in building a 2D map of the obstacle in the indoor environment combined with the rules to decide the direction of the mobile robot. The rules used to avoid the collision to the obstacle. The evaluation of the method showed that the system could map the detected obstacles, the initial position, and the goal’s relatif distance and position. The robot also reaches the goal position while avoiding the collision to the obstacle.

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Section: Methodsmentioning

confidence: 99%

Early Model of Vision-Based Obstacle Mapping Utilizing Grid-Edge-Depth Map

Rahmani,

Harjoko,

Priyambodo

et al. 2019

IJEAT

View full text Add to dashboard Cite

show abstract

“…If the physical size of each pixel is obtained by the calibrated internal parameters as s x = 1/ dx , s y = 1/ dy , the dimensions of which are 1/mm, the conversion formula, as shown in Equation (3) [ 29 , 30 , 31 ], is able to facilitate the coordinate transformation from ICS to CCS:

…”

Section: Related Workmentioning

confidence: 99%

Least-Square-Method-Based Optimal Laser Spots Acquisition and Position in Cooperative Target Measurement

Feng

et al. 2022

Sensors

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The relative positioning precisions of coordinate points is an important indicator that affects the final accuracy in the visual measurement system of space cooperative targets. Many factors, such as measurement methods, environmental conditions, data processing principles and equipment parameters, are supposed to influence the cooperative target’s acquisition and determine the precision of the cooperative target’s position in a ground simulation experiment with laser projected spots on parallel screens. To overcome the precision insufficiencies of cooperative target measurement, the factors of the laser diode supply current and charge couple device (CCD) camera exposure time are studied in this article. On the hypothesis of the optimal experimental conditions, the state equations under the image coordinates’ system that describe the laser spot position’s variation are established. The novel optimizing method is proposed by taking laser spot position as state variables, diode supply current and exposure time as controllable variables, calculating the optimal controllable variables through intersecting the focal spot centroid line and the 3-D surface, and avoiding the inconvenience of solving nonlinear equations. The experiment based on the new algorithm shows that the optimal solution can guarantee the focal spot’s variation range in 5–10 pixels under image coordinates’ system equivalent to the space with a 3 m distance and 0.6–1.2 mm positioning accuracy.

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“…Approaches that leverage computer vision data from robots closely relate to our implementation and comparison study, and such approaches have been explored for various environments and activities (e.g., indoor workspaces [15]). These approaches also consist of outdoor visual identification activities in populated environments using UAVs, which involve low-altitude aerial photography capabilities for capturing photographs from low altitudes.…”

Section: Computer Vision Approachmentioning

confidence: 99%

Identifying Potential Mosquito Breeding Grounds: Assessing the Efficiency of UAV Technology in Public Health

et al. 2020

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Human ecology has played an essential role in the spread of mosquito-borne diseases. With standing water as a significant factor contributing to mosquito breeding, artificial containers disposed of as trash—which are capable of holding standing water—provide suitable environments for mosquito larvae to develop. The development of these larvae further contributes to the possibility for local transmission of mosquito-borne diseases in urban areas such as Zika virus. One potential solution to address this issue involves leveraging unmanned aerial vehicles that are already systematically becoming more utilized in the field of geospatial technology. With higher pixel resolution in comparison to satellite imagery, as well as having the ability to update spatial data more frequently, we are interested in investigating the feasibility of unmanned aerial vehicles as a potential technology for efficiently mapping potential breeding grounds. Therefore, we conducted a comparative study that evaluated the performance of an unmanned aerial vehicle for identifying artificial containers to that of conventionally utilized GPS receivers. The study was designed to better inform researchers on the current viability of such devices for locating a potential factor (i.e., small form factor artificial containers that can host mosquito breeding grounds) in the local transmission of mosquito-borne diseases. By assessing the performance of an unmanned aerial vehicle against ground-truth global position system technology, we can determine the effectiveness of unmanned aerial vehicles on this problem through our selected metrics of: timeliness, sensitivity, and specificity. For the study, we investigated these effectiveness metrics between the two technologies of interest in surveying a study area: unmanned aerial vehicles (i.e., DJI Phantom 3 Standard) and global position system-based receivers (i.e., Garmin GPSMAP 76Cx and the Garmin GPSMAP 78). We first conducted a design study with nine external participants, who collected 678 waypoint data and 214 aerial images from commercial GPS receivers and UAV, respectively. The participants then processed these data with professional mapping software for visually identifying and spatially marking artificial containers between the aerial imagery and the ground truth GPS data, respectively. From applying statistical methods (i.e., two-tailed, paired t-test) on the participants’ data for comparing how the two technologies performed against each other, our data analysis revealed that the GPS method performed better than the UAV method for the study task of identifying the target small form factor artificial containers.

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Intelligent Design and Algorithms to Control a Stereoscopic Camera on a Robotic Workspace

Cited by 6 publications

References 8 publications

Early Model of Vision-Based Obstacle Mapping Utilizing Grid-Edge-Depth Map

Early Model of Vision-Based Obstacle Mapping Utilizing Grid-Edge-Depth Map

Least-Square-Method-Based Optimal Laser Spots Acquisition and Position in Cooperative Target Measurement

Identifying Potential Mosquito Breeding Grounds: Assessing the Efficiency of UAV Technology in Public Health

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