Real-Time 3D Modeling with a RGB-D Camera and On-Board Processing

Aguilar, Wilbert G.; Rodríguez, Guillermo A.; Álvarez, Leandro; Sandoval, Sebastián; Quisaguano, Fernando J.; Limaico, Alex

doi:10.1007/978-3-319-60928-7_35

Cited by 17 publications

(6 citation statements)

References 26 publications

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“…Te graph nodes store camera odometry, along with visual information from depth images, RGB images, and SURF features quantized into an incremental visual dictionary (visual words), used by the closed-loop detection algorithm [30,31]. Te algorithm allows establishing matches between the current camera location and previous locations of already visited sites employing the bag-of-words method [32].…”

Section: Rtab-mapmentioning

confidence: 99%

Three-Dimensional Location and Mapping Analysis in Mobile Robotics Based on Visual SLAM Methods

Acosta-Amaya,

Cadavid-Jimenez,

Jimenez-Builes

2023

Journal of Robotics

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One of the essential tasks required from a mobile robot is the autonomous and safe navigation of its working environment. However, in many cases, a model of the environment or map is not available to execute this task. Indeed, navigation requires a permanent estimation of the location for a map, which is not available for unknown environments. In such a scenario, the robot must have extended capabilities to solve, concurrently, the problems of localization and mapping. The simultaneous solution of these two problems is known as SLAM (simultaneous localization and mapping) and is a complex problem, not yet fully solved by the scientific community. This is due to the fact that localization requires a map that is not yet available since it is still under construction. In turn, the elaboration of a map requires the estimation of the robot’s location. This is the reason why SLAM has been categorized as similar to the chicken and egg problem. In the case of a robot facing an unknown environment, it would be something like what to solve first, localization or mapping? The answer to this question is that the robot will have to solve both problems at the same time. This article presents a study of some of the most representative open source visual SLAM (vSLAM) methods, beginning from an analysis of their characteristics and presenting criteria selection for an experimental design that allows contrasting their advantages and disadvantages. Two of the most representative algorithms for solving vSLAM were considered (RTAB-Map and ORB-SLAM2). The experiments were validated with a robotic system designed for this purpose, which is fully compatible with ROS (robot operating system).

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Section: Rtab-mapmentioning

confidence: 99%

Three-Dimensional Location and Mapping Analysis in Mobile Robotics Based on Visual SLAM Methods

Acosta-Amaya,

Cadavid-Jimenez,

Jimenez-Builes

2023

Journal of Robotics

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“…The work by Chen et al 23 evaluates a system of planning a route concurrently for UAV and UGV, with the limitations to the space of road networks. The works by Aguilar et al and Lakas et al 24,25 focus on algorithms of route planning in moving UGV, navigation, and avoidance of obstacles using laser radar or visual sensors. And last but not least, a comprehensive planning system for maneuvers of structured military forces and equipment and the interconnection of maneuvers of units and their fire support are given in the work by Harder.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The route planning algorithms described in previous studies 21–25 primarily address the obstacle detection and avoidance, in order to find the shortest movement route on the plane or using a network of routes without other combined effects of the terrain surface and topography, weather, or enemy activity. LIDAR (light detection and ranging) or the optical instruments of UAV were used to identify obstacles in practical tests of the functionality of these algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Multiple maneuver model of cooperating ground combat troops

Nohel

Stodola

Flasar

et al. 2022

Journal of Defense Modeling & Simulation

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The article describes the possibilities of using the Maneuver Control System CZ (MCS CZ) in creating a multiple maneuver of a group of cooperating units. It is a tactical information system designed to support the decision-making of commanders in order to effectively deploy their units on the battlefield. The system evaluates the geographical and hydrometeorological battlefield influences as well as the enemy’s situation to calculate the maneuver axes of a unit composed of up to three teams with the same goal. To verify the calculations of mathematical-algorithmic models of the system, two measurements were performed on model situations. In the first of them, a group of three unmanned systems carried out an attack on an identified delivery system of weapons of mass destruction. The second model situation included a hasty attack by three infantry squads on anti-aircraft equipment. In both cases, the resulting group of maneuvers used the fastest and safe axes of advance, spatially synchronized according to tactical principles. In both cases, the enemy’s weapon systems were quickly attacked and destroyed immediately after their identification from three directions. The commander’s decision-making process was largely replaced by the MCS CZ calculations in model situations, which significantly shortened its duration.

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“…A new low-cost approach to reconstruct real-time of a 3D object with Kinect sensor uses a SLAM algorithm (Simultaneous Localization and Mapping) [24]. SLAM provides an approximated solution of 3D reconstruction because the accuracy of the system often depends on a heuristic algorithm for obtaining relevant reference points.…”

mentioning

confidence: 99%

“…We propose to utilize a graph-based SLAM algorithm [24] with loop closure detection using dense color and depth images obtained from the RGB-D camera. We show that our system is able to perform the SLAM for three-dimensional modeling in real-time.…”

mentioning

confidence: 99%

Accuracy analysis of 3D object reconstruction using RGB-D sensor

Ruchay

Dorofeev

Kober³

2018

Collection of Selected Papers of the IV International Conference on Information Technology and Nanotechnology

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The geometry of an object can be reconstructed from laser range scans, a set of different photos, monocular cameras and stereo cameras; each technology possesses disadvantages and limitations. RGB-D cameras like Microsoft Kinect or ASUS Xtion Pro are sensing systems equipped with an RGB camera, infrared projector, and infrared sensor. They can gather RGB information and the depth map simultaneously. The ICP (Iterative Closest Point) is one of the most commonly used methods for pairwise alignment, where the rotation and translation to align two point clouds are determined. Many variants on the base ICP algorithm were proposed because of the limitations in the ICP algorithm: different cost functions [11] and others [12]; two-Pass ICP with color constraint to improve the error minimization process [13]; 3D representation using a set of planes to perform the registration [14]; point-to-plane matchings instead of point-to-point matchings in standard

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Real-Time 3D Modeling with a RGB-D Camera and On-Board Processing

Cited by 17 publications

References 26 publications

Three-Dimensional Location and Mapping Analysis in Mobile Robotics Based on Visual SLAM Methods

Three-Dimensional Location and Mapping Analysis in Mobile Robotics Based on Visual SLAM Methods

Multiple maneuver model of cooperating ground combat troops

Accuracy analysis of 3D object reconstruction using RGB-D sensor

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