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Existing calibration methods mainly focus on the camera laser-plane calibration of a single laser-line length, which is not convenient and cannot guarantee the consistency of the results when several three-dimensional (3D) scanners are involved. Thus, this study aims to provide a unified step for different laser-line length calibration requirements for laser profile measurement (LPM) systems.

3D LPM is the process of converting physical objects into 3D digital models, wherein camera laser-plane calibration is critical for ensuring system precision. However, conventional calibration methods for 3D LPM typically use a calibration target to calibrate the system for a single laser-line length, which needs multiple calibration patterns and makes the procedure complicated. In this paper, a unified calibration method was proposed to automatically calibrate the camera laser-plane parameters for the LPM systems with different laser-line lengths. The authors designed an elaborate planar calibration target with different-sized rings that mounted on a motorized linear platform to calculate the laser-plane parameters of the LPM systems. Then, the camera coordinates of the control points are obtained using the intersection line between the laser line and the planar target. With a new proposed error correction model, the errors caused by hardware assembly can be corrected. To validate the proposed method, three LPM devices with different laser-line lengths are used to verify the proposed system. Experimental results show that the proposed method can calibrate the LPM systems with different laser-line lengths conveniently with standard steps.

The repeatability and accuracy of the proposed calibration prototypes were evaluated with high-precision workpieces. The experiments have shown that the proposed method is highly adaptive and can automatically calibrate the LPM system with different laser-line lengths with high accuracy.

In the repeatability experiments, there were errors in the measured heights of the test workpieces, and this is because the laser emitter had the best working distance and laser-line length.

By using this proposed method and device, the calibration of the 3D scanning laser device can be done in an automatic way.

The calibration efficiency of a laser camera device is increased.

The authors proposed a unified calibration method for LPM systems with different laser-line lengths that consist of a motorized linear joint and a calibration target with elaborately designed ring patterns; the authors realized the automatic parameter calibration.

Scattered parts are laid randomly during the manufacturing process and have difficulty to recognize and manipulate. This study aims to complete the grasp of the scattered parts by a manipulator with a camera and learning method.

In this paper, a cascaded convolutional neural network (CNN) method for robotic grasping based on monocular vision and small data set of scattered parts is proposed. This method can be divided into three steps: object detection, monocular depth estimation and keypoint estimation. In the first stage, an object detection network is improved to effectively locate the candidate parts. Then, it contains a neural network structure and corresponding training method to learn and reason high-resolution input images to obtain depth estimation. The keypoint estimation in the third step is expressed as a cumulative form of multi-scale prediction from a network to use an red green blue depth (RGBD) map that is acquired from the object detection and depth map estimation. Finally, a grasping strategy is studied to achieve successful and continuous grasping. In the experiments, different workpieces are used to validate the proposed method. The best grasping success rate is more than 80%.

By using the CNN-based method to extract the key points of the scattered parts and calculating the possibility of grasp, the successful rate is increased.

This method and robotic systems can be used in picking and placing of most industrial automatic manufacturing or assembly processes.

Unlike standard parts, scattered parts are randomly laid and have difficulty recognizing and grasping for the robot. This study uses a cascaded CNN network to extract the keypoints of the scattered parts, which are also labeled with the possibility of successful grasping. Experiments are conducted to demonstrate the grasping of those scattered parts.

This paper aims to develop a climbing robot to help people inspect lamps of high-mast lighting.

The robot consists of driving mechanism, suspension mechanism and compression mechanism. The driving mechanism is realized by link chains and sprockets, which are arranged opposite to each other, to form a dual caterpillar mechanism. The compression mechanism squeezes the caterpillar, and rubber feet “grasps” the steel rope to generate enough adhesion forces. The suspension mechanism is used to compensate the contraction or extension of the chains. The robot is equipped with a DC motor with a rated power of 250 W and a wireless module to communicate with the operator’s console. The dynamic model of the robot and the control strategy is derived, and the stability of the controller is proofed.

The payload experiment shows the robot can afford up to 3.7 times payload versus its own weight. Even when the payload is 30 kg, the robot can maintain a speed of the 1 m/s. The experiments also show that the tracking error of the robot reaches zero.

The proposed moving mechanism has a high load/weight ratio, which is a verified solution for the cable inspection purpose.

A rope climbing robot for high mast lighting inspection is proposed. The developed mechanism can reach a speed of 1 m/s with the payload of 30 kg, while its own weight is only 15.6 kg. The payload/weight ratio of the robot is 2.24; this value is rather good in many climbing robots reported in other renowned journal.

Multi-robot laser-based simultaneous localization and mapping (SLAM) in large-scale environments is an essential but challenging issue in mobile robotics, especially in situations wherein no prior knowledge is available between robots. Moreover, the cumulative errors of every individual robot exert a serious negative effect on loop detection and map fusion. To address these problems, this paper aims to propose an efficient approach that combines laser and vision measurements.

A multi-robot visual laser-SLAM is developed to realize robust and efficient SLAM in large-scale environments; both vision and laser loop detections are integrated to detect robust loops. A method based on oriented brief (ORB) feature detection and bag of words (BoW) is developed, to ensure the robustness and computational effectiveness of the multi-robot SLAM system. A robust and efficient graph fusion algorithm is proposed to merge pose graphs from different robots.

The proposed method can detect loops more quickly and accurately than the laser-only SLAM, and it can fuse the submaps of each single robot to promote the efficiency, accuracy and robustness of the system.

Compared with the state of art of multi-robot SLAM approaches, the paper proposed a novel and more sophisticated approach. The vision-based and laser-based loops are integrated to realize a robust loop detection. The ORB features and BoW technologies are further utilized to gain real-time performance. Finally, random sample consensus and least-square methodologies are used to remove the outlier loops among robots.

This study investigates the effect of authentic leadership on service employees’ emotional labour strategies, surface acting and deep acting, from a human energy perspective.

A three-wave survey was conducted in a hotel chain in China, and 347 valid responses were obtained. Mplus software was used for structural equation modelling and bootstrapping analysis.

This study finds the following: authentic leadership predicts service employees’ emotional labour strategies; job insecurity mediates the influence of authentic leadership on surface acting but not on deep acting; relational energy mediates both surface and deep acting; and relational energy has more negative (positive) indirect effects than job insecurity.

The findings provide hospitality managers with insights into how to improve service employees’ capacity for emotional regulation. Hospitality managers should show more authenticity, pay attention to subordinates’ energy level and select and recruit candidates with positive energy traits. Hospitality organisations should encourage, select and train managers to behave as authentic leaders.

This study links authentic leadership with service employees’ emotional management in the hospitality industry. Moreover, it demonstrates the energising function of authentic leadership and introduces the new perspective of human energy to emotional labour research.

Previous research about online recommendation systems has focused largely on their impact on customers' purchase decisions regarding the products being recommended, but it has mostly ignored how they may affect focal product evaluation. This research aimed to examine the influence of recommendation type (i.e. substitute-based vs complement-based) on focal product evaluation dependent on the brand image (i.e. warm vs competent).

Four laboratory experiments were conducted. Study 1 adopted an implicit association task. Studies 2 and 3 used a 2 (image: warmth vs competence) × 2 (product display: complements vs substitutes) between-subjects experimental design. Study 4 used a 2 (decision stage) × 2 (image) × 2 (product display) × continuous (need for cognition) between-subjects design.

Study 1 demonstrated a general “complementation (competition)—warmth (competence)” association. Studies 2 and 3 found that when a focal product had a warm (competent) image, complement-based (substitute-based) recommendations led customers to evaluate it more favorably than substitute-based (complement-based) recommendations. Study 3 further demonstrated that processing fluency mediates the above effect. Study 4 showed that this effect relies on heuristic processing and disappears for those who are in the screening stage or have a high need for cognition.

Theoretically, this research extends the understanding of the stereotype content model of focal product brand image, the feelings-as-information process, and moderating roles of processing stage and need for cognition in e-commerce contexts. Practically, the findings provide online retailers a guideline for customizing their recommendation systems.

This study aims to solve the problem of the existing metal foreign object (MFO) detecting systems, which are not sensitive to the small size MFO in wireless charging region of electric vehicle (EV) because of the extremely complex signal noise in the process of wireless charging of EV.

A method for MFO detection based on the principle that MFOs can cause mistuned resonance of detection coil resonant circuit is proposed. The general scheme of detecting system is proposed. The design method for detection coils which is effective to small MFOs detection in large-area region of wireless charging of EV is presented. The design of time-sharing driving circuit and amplifying circuit of high frequency exciting signal for detection coils is introduced. The design scheme of signal processing circuit (including filter and rectifier) of detection coil terminal voltage is also proposed.

The influence of exciting frequency of detection coils on detecting sensitivity and the anti-noise feature of system are analyzed according to the experiment results.

The experiment of MFO detection indicates that the proposed method can effectively detect the coin-sized small MFO in the process of wireless charging of EV.

This paper aims to present a multiscale fuzzy optimization (FO) method to optimize both the density distribution and macrotopology of a uniform octet-truss lattice structure.

The design formulae for the strut radii are presented based on the effective mechanical properties obtained from the representative volume element. The proposed basic lattice material is applied in a normalization process to determine the material model with penalization. The solid isotropic material with penalization (SIMP) method is extended to solve the minimum compliance problem using the optimality criteria. The evolutionary deletion process is proposed to delete elements corresponding to thin-strut unit cells and to obtain the optimal macrotopology.

Both numerical cases indicate that the FO results significantly improved in structural performance compared with the results of the conventional SIMP. The deleting threshold controls the macrotopology of the graded-density lattice structures with negligible effects on the mechanical properties.

This paper presents one of the first multiscale optimization methods to optimize both the relative density and macrotopology of uniform octet-truss lattices. The material model and corresponding optimality criteria of octet-truss lattices are proposed and implemented in the optimization.

Based on the mechanical model of typical shear tests, this study aims to propose the test principle and method of freshwater/seawater ice adhesion shear strength of carbon ceramic brake pads for amphibious aircraft, designs and builds the test equipment, prepares the freshwater/seawater ice samples and completes the tests.

This study examines the influence of the icing process, mechanism, temperature and freshwater/seawater on ice adhesion shear strength of carbon ceramic brake pads and puts forward a test method for the freshwater/seawater ice adhesion shear strength of amphibious aircraft brake pads.

The obtained results examine the influence of the icing process, mechanism, temperature and freshwater/seawater on ice adhesion shear strength of carbon ceramic brake pads. The adhesion shear strength of frozen freshwater and of the seawater of Dalian, Qingdao, Fuzhou and Zhuhai on the surface of aircraft brake pads is measured at –10 to –50°C. It is found that the shear strength of freshwater increases first and then decreases with the decrease of temperature. The adhesion shear strength of seawater; however, increases mainly linear with the decrease of temperature.

The value of this paper is that the test method proposed and test results for the freshwater/seawater ice adhesion shear strength of amphibious aircraft brake pads provide technical support for the anti-icing design of amphibious aircraft brake devices.

Drawing on the dynamic managerial capability perspective and the dynamic capability perspective of business model (BM) literature, this paper aims to investigate how top management team internal social capital (TISC) promotes BM design and how such effects are moderated by market dynamics (i.e. demand uncertainty and competitive intensity).

The proposed hypotheses were tested by a questionnaire-based survey. The empirical study was conducted on a sample of 210 firms in China. The model was tested via hierarchical regression analysis.

TISC has a positive effect on BM efficiency but an inverted U-shaped effect on BM novelty. The effects of TISC on BM efficiency and novelty are contingent on demand uncertainty and competitive intensity in different ways. Specifically, this study finds that demand uncertainty strengthens the inverted U-shaped effect of TISC on BM novelty. This study also finds that competitive intensity strengthens the positive effect of TISC on BM efficiency but weakens the inverted U-shaped effect of TISC on BM novelty.

The conclusion contributes to the dynamic capability perspective of BM literature in two ways. First, it offers a dynamic managerial capability perspective for understanding the antecedents of BM design. It highlights TISC, a root of dynamic managerial capability, as an important internal antecedent of BM design. Second, it provides a more nuanced understanding of the role of TISC in BM design. The findings show the distinct effects of TISC on BM efficiency and novelty. This study also discusses the contingency role market dynamics play in the TISC–BM design relationship.