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Because of their large field of view, omnistereo vision systems have been widely used as primary vision sensors in autonomous mobile robot tasks. The purpose of this article is to achieve real-time and accurate tracking by the omnidirectional vision robot system.

The authors provide in this study the key techniques required to obtain an accurate omnistereo target tracking and location robot system, including stereo rectification and target tracking in complex environment. A simple rectification model is proposed, and a local image processing method is used to reduce the computation time in the localization process. A target tracking method is improved to make it suitable for omnidirectional vision system. Using the proposed methods and some existing methods, an omnistereo target tracking and location system is established.

The experiments are conducted with all the necessary stages involved in obtaining a high-performance omnistereo vision system. The proposed correction algorithm can process the image in real time. The experimental results of the improved tracking algorithm are better than the original algorithm. The statistical analysis of the experimental results demonstrates the effectiveness of the system.

A simple rectification model is proposed, and a local image processing method is used to reduce the computation time in the localization process. A target tracking method is improved to make it suitable for omnidirectional vision system. Using the proposed methods and some existing methods, an omnistereo target tracking and location system is established.

The paper seeks to develop a stereo vision system based on a new binocular device. It aims to present an explicit‐implicit correction method to correct radial and tangential distortion of image synchronously. It also aims to propose a step‐rotation rectification method to rectify epipolar error between stereo pairs.

Least squares technique was used in solving the explicit‐implicit correction model. When the step‐rotation rectification method was implemented, the technology of rotating image space was used.

The paper finds that the stereo vision system based on a new binocular device can be used in different circumstances, and it can obtain more eyeshot of cameras. The explicit‐implicit correction method can eliminate radial and tangential distortion of images, and the solution to this method is so easy that it can be solved by least squares technique. The theory of step‐rotation rectification is simple, and it is effective for rectifying epipolar error.

The explicit‐implicit correction method and step‐rotation rectification method can be used in correcting image distortion and epipolar error in stereo pairs collected by a stereo vision system. The new binocular device can be used in building a stereo vision system.

A new binocular device is developed in the paper. Explicit distortion method and implicit distortion method are united to correct image distortion. A step‐rotation rectification method is proposed to rectify epipolar error.

Complicated tubes extensively exist in the industrial equipment. The manufacturing precision of the tubes is difficult to be ensured with bending machine. Therefore, the tubes’ 3D geometric error should be fixed according to measurement results. However, there are no convenient methods to accomplish the measurement accurately and effectively. Thus, this paper aims to propose a new tube measurement method to achieve tube's automatic measurement. The accurate measurement results can be used to fix the geometric error of the tube to achieve stress-free assembly.

Tubes’ shape can be determined by control points. First, the point clouds of the centre line by multi-stereo-vision technology are reconstructed. Then, the point clouds to the spine of the tube are thinned by moving least-squares and segmented into lines and arcs. Finally, the control points are calculated and the model is reconstructed. The authors can get the tube’s geometric dimensions from the model.

The experiment results indicate that the multi-stereo-vision technology can solve the occlusion problem and measure the complicated tubes efficiently and accurately.

The paper proposed a tube measurement method. The repeatability measuring precision was 0.12 mm, and the absolute measuring precision was within 0.78 mm. The tube spectra assessed in this paper are in the range of angles between two adjacent line segments of 3-177° and the shortest length of the line segment is greater than 5 mm, confirming that the proposed algorithm can measure various complicated tubes effectively and accurately.

The mass electronics sector is one of the most critical sources of waste, in terms of volume and content with dangerous effects on the environment. The purpose of this study is to provide an automated and accurate dismantling system that can improve the outcome of recycling.

Following a short introduction, the paper details the implementation layout and highlights the advantages of using a custom architecture for the automated dismantling of printed circuit board waste.

Currently, the amount of electronic waste is impressive while manual dismantling is a very common and non-efficient approach. Designing an automatic procedure that can be replicated, is one of the tasks for efficient electronic waste recovery. This paper proposes an automated dismantling system for the advanced recovery of particular waste materials from computer and telecommunications equipment. The automated dismantling architecture is built using a robotic system, a custom device and an eye-to-hand configuration for a stereo vision system.

The proposed approach is innovative because of its custom device design. The custom device is built using a programmable screwdriver combined with an innovative rotary dismantling tool. The dismantling torque can be tuned empirically.

The purpose of this research is to develop closed‐loop control of robotic welding processes.

The approach being developed is the creation of three‐dimensional models of the weld pool using stereo imagining. These models will be used in a model‐based feedback control system. Fusion of more than one sensor type in the controller is used.

Three‐dimensional images can be produced from stereo images of GMAW‐p weld pools. This requires coordinating the image capture with the arc pulse to allow observation of the pool.

This is a work in progress. The imaging is not being done in real time at this point in time. Future work will address this issue. Also, how the image information is to be used to make corrections within the controller is future work.

Closing the loop on GMAW welding will allow robotic automation of welding to proceed to a much broader degree of application.

This paper demonstrates that stereo imaging of out‐of‐position GMAW‐p weld pools is possible and the useful information can be obtained from these images. It also provides insights into the analysis required within the model‐based controller if one is to close the loop on the process specifically with regard to weld pool stability.

To present a stereo matching algorithm which satisfies the need of visual navigation on outdoor natural terrain for lunar rover or other mobile robots.

A feature‐assisted matching algorithm is presented to generate dense and accurate disparity map of natural terrain. Multi‐feature matching strategy produces reliable matching results for edge points. Disparity monotony constraint is derived and other geometrical constraints are introduced. With these constraints the edge‐matching results are used to limit the search region in area‐matching. As a result the algorithm produces dense disparity maps with fairly high accuracy and demonstrates advantages over straightforward area‐matching algorithm in improving matching accuracy.

With the help of several constraints, the feature‐assisted matching algorithm performs well in the matching of stereo image pairs of natural terrain.

The algorithm focus on improving the accuracy of stereo image pairs matching of natural terrain and computation complexity is not an important designing factor. Only with the assistance of special hardware or other technique can the algorithm be used for real‐time navigation.

The algorithm is able to produce dense disparity map of natural terrain with rather high accuracy and can be used for the navigation of lunar rover or other outdoor mobile robots.

The paper provides a new approach to produce accurate and dense disparity map of natural terrain.

This research aims to address the issue of safe navigation for autonomous vehicles in highly challenging outdoor environments. Indeed, robust navigation of autonomous mobile robots over long distances requires advanced perception means for terrain traversability assessment.

The use of visual systems may represent an efficient solution. This paper discusses recent findings in terrain traversability analysis from RGB-D images. In this context, the concept of point as described only by its Cartesian coordinates is reinterpreted in terms of local description. As a result, a novel descriptor for inferring the traversability of a terrain through its 3D representation, referred to as the unevenness point descriptor (UPD), is conceived. This descriptor features robustness and simplicity.

The UPD-based algorithm shows robust terrain perception capabilities in both indoor and outdoor environment. The algorithm is able to detect obstacles and terrain irregularities. The system performance is validated in field experiments in both indoor and outdoor environments.

The UPD enhances the interpretation of 3D scene to improve the ambient awareness of unmanned vehicles. The larger implications of this method reside in its applicability for path planning purposes.

This paper describes a visual algorithm for traversability assessment based on normal vectors analysis. The algorithm is simple and efficient providing fast real-time implementation, since the UPD does not require any data processing or previously generated digital elevation map to classify the scene. Moreover, it defines a local descriptor, which can be of general value for segmentation purposes of 3D point clouds and allows the underlining geometric pattern associated with each single 3D point to be fully captured and difficult scenarios to be correctly handled.

The aim is to obtain a dense and reliable disparity map from a stereoscopic pair under any luminosity condition. From the disparity map it is possible to obtain some information about the objects appearing in the scene, such as their position and their distance to the camera.

The disparity map is obtained using a correspondence method based on a multiresolution scheme. It also uses the simulated annealing algorithm to minimize the energy function, which integrates information coming from several sources: grey levels, non‐parametric transforms, edges and geometrical constraints. The multiresolution scheme allows us to interpolate the disparity map obtained in each level and to use it as an initial estimation for the simulating annealing process in the following level.

The multiresolution scheme speeds up the convergence. The fact of adding information about the neighbourhood improves the results. A simple and suitable energy function has been proposed. A simple efficient scaling scheme has been used. Their results are as good as other costly techniques such as block‐to‐point.

The use of grey level images has the drawback that some bright areas can be confused. As a solution, some other additional features are proposed.

A new metric is proposed to evaluate the quality of a disparity map. A low‐cost energy function is proposed. It integrates several type information to add robustness to the method. The convergence of the method is dramatically speeded up reusing the results of the algorithm thanks to the multiresolution scheme.

The purpose of this paper is to introduce the design of a training tool intended to improve deminers' technique during close‐in detection tasks.

Following an introduction that highlights the impact of mines and improvised explosive devices (IEDs), and the importance of training for enhancing the safety and the efficiency of the deminers, this paper considers the utilization of a sensory tracking system to study the skill of the hand‐held detector expert operators. With the compiled information, some critical performance variables can be extracted, assessed, and quantified, so that they can be used afterwards as reference values for the training task. In a second stage, the sensory tracking system is used for analysing the trainee skills. The experimentation phase aims to test the effectiveness of the elements that compose the sensory system to track the hand‐held detector during the training sessions.

The proposed training tool will be able to evaluate the deminers' efficiency during the scanning tasks and will provide important information for improving their competences.

This paper highlights the need of introducing emerging technologies for enhancing the current training techniques for deminers and proposes a sensory tracking system that can be successfully utilised for evaluating trainees' performance with hand‐held detectors.