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Geometric errors are common in metallic bent tubular parts. Thus, tubes should be inspected and fixed before welding with the joints first. After welding, the relative position of the joints is also necessary to be inspected to judge whether the tube can be assembled reliably. Therefore, the inspection plays an important role in the tube’s assembly. The purpose of this paper is to propose a multi-vision-based system designed to inspect the tube and the relative position of the joints.

For the tube inspection, the small cylinders are taken as the primitives to reconstruct the tube using the multi- vision-based system. Then, any geometric error in the tube can be inspected by comparing the reconstructed models and designed ones. For joints’ inspection, authors designed an adapter with marked points, by which the system can calculate the relative position of the joints.

The reconstruction idea can recognise the line and arc segments of a tube automatically and resolve the textureless deficiency of the tube’s surface. The joints’ inspection method is simple in operation, and any kinds of joints can be inspected by designing the structure of the adapters accordingly.

By experimental verification, the inspection precision of the proposed system was 0.17 mm; the inspection time was within 2 min. Thus, the system developed can inspect a tube effectively and automatically. Moreover, authors can determine how the springback of the arcs behaves, allowing in-process springback prediction and compensation, which can reduce geometric errors in the tubes given the present bending machine accuracy.

This paper aims to solve the problem of free-form tubes’ machining errors which are caused by their complex geometries and material properties.

In this paper, the authors propose a multi-view vision-based method for measuring free-form tubes. The authors apply photogrammetry theory to construct the initial model and then optimize the model using an energy function. The energy function is based on the features of the image of the tube. Solving the energy function allows to use the gray features of the images to reconstruct centerline point clouds and thus obtain the pertinent geometric parameters.

According to the experiments, the measurement process takes less than 2 min and the precision of the proposed system is 0.2 mm. The authors used simple operations to carry out the measurements, and the process is fully automatic.

This paper proposes a method for measuring free-form tubes based on multi-view vision, which has not been attempted to the best of authors’ knowledge. This method differs from traditional multi-view vision measurement methods, because it does not rely on the data of the design model of the tube. The application of the energy function also avoids the problem of matching corresponding points and thus simplifying the calculation and improving its stability.

In multi-robot cooperation, the cloud can share sensor data, which can help robots better perceive the environment. For cloud robotics, robot grasping is an important ability that must be mastered. Usually, the information source of grasping mainly comes from visual sensors. However, due to the uncertainty of the working environment, the information acquisition of the vision sensor may encounter the situation of being blocked by unknown objects. This paper aims to propose a solution to the problem in robot grasping when the vision sensor information is blocked by sharing the information of multi-vision sensors in the cloud.

First, the random sampling consensus algorithm and principal component analysis (PCA) algorithms are used to detect the desktop range. Then, the minimum bounding rectangle of the occlusion area is obtained by the PCA algorithm. The candidate camera view range is obtained by plane segmentation. Then the candidate camera view range is combined with the manipulator workspace to obtain the camera posture and drive the arm to take pictures of the desktop occlusion area. Finally, the Gaussian mixture model (GMM) is used to approximate the shape of the object projection and for every single Gaussian model, the grabbing rectangle is generated and evaluated to get the most suitable one.

In this paper, a variety of cloud robotic being blocked are tested. Experimental results show that the proposed algorithm can capture the image of the occluded desktop and grab the objects in the occluded area successfully.

In the existing work, there are few research studies on using active multi-sensor to solve the occlusion problem. This paper presents a new solution to the occlusion problem. The proposed method can be applied to the multi-cloud robotics working environment through cloud sharing, which helps the robot to perceive the environment better. In addition, this paper proposes a method to obtain the object-grabbing rectangle based on GMM shape approximation of point cloud projection. Experiments show that the proposed methods can work well.

The purpose of this paper is to present an integrated model of didactic, practice and interdisciplinary service learning in healthcare education, and determine the students’ perceptions on the benefits of this integration.

A pre and post survey design was utilized to examine health professions students’ perspectives with respect to learning outcomes relevant to professional benefits of a service learning capstone. The surveys consisted of 36 items for measuring the interdisciplinary course characteristics and perceived benefits of the integrated approach. The required interdisciplinary (used interchangeably with interprofessional) course was constructed as an integrated didactic, practice interdisciplinary service learning model. The sample consisted of undergraduate students (n=53) who completed the interdisciplinary senior seminar capstone course taught by one faculty member in one of three course sections. Structural equation modeling based on partial least squares was used to analyze the significance of constructs. Students’ reflections on interdisciplinary service learning were also collected and summarized.

The study demonstrated the significance of interdisciplinary course and team preparation on perceived professional benefits and positive community service learning experience.

Further studies are needed and being pursued to address practitioners’ perceptions of interdisciplinary education. To fully complete the assessment of interdisciplinary education, longitudinal studies must be pursued with graduates and their employers. A larger sample size could be used to repeat this study.

The model employed in this study may be utilized as a component of practice education and clinical practice to address accreditation requirements, quality patient-centred care, and engaging students in valuing interprofessionalism and service.

This study presents an integrated model of didactic, practice and interdisciplinary service learning in health professions education, and demonstrates the benefits of the model with health profession students’ perceptions of interprofessional education (IPE). This study contributes to professional learning research as the impact of IPE has been questionable due to lack of rigorous evidence.

The aim of this paper is to propose a grasping method based on intelligent perception for implementing a grasp task with human conduct.

First, the authors leverage Kinect to collect the environment information including both image and voice. The target object is located and segmented by gesture recognition and speech analysis and finally grasped through path teaching. To obtain the posture of the human gesture accurately, the authors use the Kalman filtering (KF) algorithm to calibrate the posture use the Gaussian mixture model (GMM) for human motion modeling, and then use Gaussian mixed regression (GMR) to predict human motion posture.

In the point-cloud information, many of which are useless, the authors combined human’s gesture to remove irrelevant objects in the environment as much as possible, which can help to reduce the computation while dividing and recognizing objects; at the same time to reduce the computation, the authors used the sampling algorithm based on the voxel grid.

The authors used the down-sampling algorithm, kd-tree algorithm and viewpoint feature histogram algorithm to remove the impact of unrelated objects and to get a better grasp of the state.

The paper aims to evaluate the knowledge-based urban development (KBUD) dynamics of a rapidly emerging knowledge city-region, Tampere region, Finland.

The paper empirically investigates Tampere region’s development achievements and progress from the knowledge perspective.

The research, through qualitative and quantitative analyses, reveals the regional development strengths, weaknesses, opportunities and threats of Tampere region.

The paper provides useful suggestions based on the lessons learned from the Tampere case investigation that could shed light on the KBUD journey of city-regions.

HEADING a Government committee charged with the task of recommending the registration and licensing of engineers is Sir Montague Finniston, President of the Institute. One would think that the task is impossible, if only for lack of definition.

Cylindrical components are common in industry assembly areas. It is necessary to obtain their precise positions and orientations for their assemblies. But some measurement approaches relying on measuring targets are not allowed, as they may not meet the efficiency requirement of on-line measurement or may cause surface damages to the components. Thus, this paper aims to provide a precise on-line non-target scanning method based on 3D vision.

First, a laser profile sensor is used to acquire point cloud of the side surface of the measured cylindrical component. Then a composite process is conducted to estimate the pose and position of the axis. Aiming at this purpose, two fitting approaches, i.e., axis fitting and generatrix fitting, are tried respectively to estimate the pose parameters from the point cloud.

The results of Monte Carlo simulations demonstrate that neither the axis fitting nor the generatrix fitting could solely obtain the needed accuracy and precisions roundly. Thus, a new synthesis method is presented. And the results of prototype experiments validate the excellent accuracy and precision of the synthesis method.

This proposed new synthesis method combines the advantages of both the above fitting methods and can be easily integrated into the assembly line to guide the automation assembly process of the cylindrical components precisely.

Continuum manipulators are often used in complex and narrow space in recent years because of their flexibility and safety. Vision is considered to be one of the most direct methods to obtain its spatial shape. However, with the improvement of the cooperation requirements of multiple continuum manipulators and the increase of space limitation, it is impossible to obtain the complete spatial shape information of multiple continuum manipulators only by several cameras.

This paper proposes a fusion method using inertial navigation sensors and cameras to reconstruct the shape of continuum manipulators in the whole workspace. The camera is used to obtain the position information, and the inertial navigation sensor is used to obtain the attitude information. Based on the above two information, the shape of the continuum manipulator is reconstructed by fitting Bézier curve.

The experiment result of single continuum manipulator shows that the cubic Bézier curves is applicable to curve fitting of variable curvature, the maximum fitting error is about 2 mm. Meanwhile, the experiment result shows that this method is not affected by obstacles and can still reconstruct the shape of the continuum manipulators in 3-D space by detecting the position and attitude information of the end.

According to the authors’ knowledge, this is the first study on spatial shape reconstruction of multiple continuum manipulators and the first study to introduce inertial navigation sensors and cameras into the field of shape reconstruction of multiple continuum manipulators in narrow space. This method is suitable for shape reconstruction of manipulator with variable curvature continuum manipulator. When the vision of multiple continuum manipulators is blocked by obstacles, the spatial shape can still be reconstructed only by exposing the end point. The structure is simple, but it has certain accuracy within a certain range.