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1 – 10 of over 1000Suyong Yeon, ChangHyun Jun, Hyunga Choi, Jaehyeon Kang, Youngmok Yun and Nakju Lett Doh
– The authors aim to propose a novel plane extraction algorithm for geometric 3D indoor mapping with range scan data.
Abstract
Purpose
The authors aim to propose a novel plane extraction algorithm for geometric 3D indoor mapping with range scan data.
Design/methodology/approach
The proposed method utilizes a divide-and-conquer step to efficiently handle huge amounts of point clouds not in a whole group, but in forms of separate sub-groups with similar plane parameters. This method adopts robust principal component analysis to enhance estimation accuracy.
Findings
Experimental results verify that the method not only shows enhanced performance in the plane extraction, but also broadens the domain of interest of the plane registration to an information-poor environment (such as simple indoor corridors), while the previous method only adequately works in an information-rich environment (such as a space with many features).
Originality/value
The proposed algorithm has three advantages over the current state-of-the-art method in that it is fast, utilizes more inlier sensor data that does not become contaminated by severe sensor noise and extracts more accurate plane parameters.
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Heber Sobreira, A. Paulo Moreira, Paulo Costa and José Lima
This paper aims to address a mobile robot localization system that avoids using a dedicated laser scanner, making it possible to reduce implementation costs and the robot’s size…
Abstract
Purpose
This paper aims to address a mobile robot localization system that avoids using a dedicated laser scanner, making it possible to reduce implementation costs and the robot’s size. The system has enough precision and robustness to meet the requirements of industrial environments.
Design/methodology/approach
Using an algorithm for artificial beacon detection combined with a Kalman Filter and an outlier rejection method, it was possible to enhance the precision and robustness of the overall localization system.
Findings
Usually, industrial automatic guide vehicles feature two kinds of lasers: one for navigation placed on top of the robot and another for obstacle detection (security lasers). Recently, security lasers extended their output data with obstacle distance (contours) and reflectivity. These new features made it possible to develop a novel localization system based on a security laser.
Research limitations/implications
Once the proposed methodology is completely validated, in the future, a scheme for global localization and failure detection should be addressed.
Practical implications
This paper presents a comparison between the presented approach and a commercial localization system for industry. The proposed algorithms were tested in an industrial application under realistic working conditions.
Social implications
The presented methodology represents a gain in the effective cost of the mobile robot platform, as it discards the need for a dedicated laser for localization purposes.
Originality/value
This paper presents a novel approach that benefits from the presence of a security laser on mobile robots (mandatory sensor when considering industrial applications), using it simultaneously with other sensors, not only to guarantee safety conditions during operation but also to locate the robot in the environment. This paper is also valuable because of the comparison made with a commercialized system, as well as the tests conducted in real industrial environments, which prove that the approach presented is suitable for working under these demanding conditions.
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Construction contract auctions are characterized by (1) a heavy emphasis on the lowest bid as it is that which usually determines the winner of the auction, (2) anticipated high…
Abstract
Construction contract auctions are characterized by (1) a heavy emphasis on the lowest bid as it is that which usually determines the winner of the auction, (2) anticipated high outliers because of the presence of non‐competitive bids, (3) very small samples, and (4) uncertainty of the appropriate underlying density function model of the bids. This paper describes a method for simultaneously identifying outliers and density function by systematically identifying and removing candidate (high) outliers and examining the composite goodness‐of‐fit of the resulting reduced samples with censored normal and lognormal density function. The special importance of the lowest bid value in this context is utilized in the goodness‐of‐fit test by the probability of the lowest bid recorded for each auction as a lowest order statistic. Six different identification strategies are tested empirically by application, both independently and in pooled form, to eight sets of auction data gathered from around the world. The results indicate the most conservative identification strategy to be a multiple of the auction standard deviation assuming a lognormal composite density. Surprisingly, the normal density alternative was the second most conservative solution. The method is also used to evaluate some methods used in practice and to identify potential improvements.
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In this paper, an emerging state-of-the-art machine intelligence technique called the Hierarchical Temporal Memory (HTM) is applied to the task of short-term load forecasting…
Abstract
In this paper, an emerging state-of-the-art machine intelligence technique called the Hierarchical Temporal Memory (HTM) is applied to the task of short-term load forecasting (STLF). A HTM Spatial Pooler (HTM-SP) stage is used to continually form sparse distributed representations (SDRs) from a univariate load time series data, a temporal aggregator is used to transform the SDRs into a sequential bivariate representation space and an overlap classifier makes temporal classifications from the bivariate SDRs through time. The comparative performance of HTM on several daily electrical load time series data including the Eunite competition dataset and the Polish power system dataset from 2002 to 2004 are presented. The robustness performance of HTM is also further validated using hourly load data from three more recent electricity markets. The results obtained from experimenting with the Eunite and Polish dataset indicated that HTM will perform better than the existing techniques reported in the literature. In general, the robustness test also shows that the error distribution performance of the proposed HTM technique is positively skewed for most of the years considered and with kurtosis values mostly lower than a base value of 3 indicating a reasonable level of outlier rejections.
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Yue Wang, Shusheng Zhang, Sen Yang, Weiping He and Xiaoliang Bai
This paper aims to propose a real-time augmented reality (AR)-based assembly assistance system using a coarse-to-fine marker-less tracking strategy. The system automatically…
Abstract
Purpose
This paper aims to propose a real-time augmented reality (AR)-based assembly assistance system using a coarse-to-fine marker-less tracking strategy. The system automatically adapts to tracking requirement when the topological structure of the assembly changes after each assembly step.
Design/methodology/approach
The prototype system’s process can be divided into two stages: the offline preparation stage and online execution stage. In the offline preparation stage, planning results (assembly sequence, parts position, rotation, etc.) and image features [gradient and oriented FAST and rotated BRIEF (ORB)features] are extracted automatically from the assembly planning process. In the online execution stage, too, image features are extracted and matched with those generated offline to compute the camera pose, and planning results stored in XML files are parsed to generate the assembly instructions for manipulators. In the prototype system, the working range of template matching algorithm, LINE-MOD, is first extended by using depth information; then, a fast and robust marker-less tracker that combines the modified LINE-MOD algorithm and ORB tracker is designed to update the camera pose continuously. Furthermore, to track the camera pose stably, a tracking strategy according to the characteristic of assembly is presented herein.
Findings
The tracking accuracy and time of the proposed marker-less tracking approach were evaluated, and the results showed that the tracking method could run at 30 fps and the position and pose tracking accuracy was slightly superior to ARToolKit.
Originality/value
The main contributions of this work are as follows: First, the authors present a coarse-to-fine marker-less tracking method that uses modified state-of-the-art template matching algorithm, LINE-MOD, to find the coarse camera pose. Then, a feature point tracker ORB is activated to calculate the accurate camera pose. The whole tracking pipeline needs, on average, 24.35 ms for each frame, which can satisfy the real-time requirement for AR assembly. On basis of this algorithm, the authors present a generic tracking strategy according to the characteristics of the assembly and develop a generic AR-based assembly assistance platform. Second, the authors present a feature point mismatch-eliminating rule based on the orientation vector. By obtaining stable matching feature points, the proposed system can achieve accurate tracking results. The evaluation of the camera position and pose tracking accuracy result show that the study’s method is slightly superior to ARToolKit markers.
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Jun Liu, Junyuan Dong, Mingming Hu and Xu Lu
Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic…
Abstract
Purpose
Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.
Design/methodology/approach
In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.
Findings
Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.
Originality/value
In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.
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Khalil Nakib, Abdelrazzak Charbaji and Jamal Hamdan
The purpose of this study was to examine three different socialization tactics (social, context, and content) used by Lebanese commercial banks. A survey instrument was…
Abstract
The purpose of this study was to examine three different socialization tactics (social, context, and content) used by Lebanese commercial banks. A survey instrument was distributed to 115 newcomer employees. It was found that Lebanese commercial banks socialize their new employees to be effective members.
Ivana Blažková and Ondřej Dvouletý
The purpose of this paper is to analyse to what extent industry, year and firm effects influence the profitability of the firms operating in the Czech food processing industry…
Abstract
Purpose
The purpose of this paper is to analyse to what extent industry, year and firm effects influence the profitability of the firms operating in the Czech food processing industry. The authors’ interest is also to investigate whether the profitability of a few firms (regarded as outliers) is able to influence the relative importance of year, firm and industry effects and to find out the relative importance of these effects for the majority of the firms.
Design/methodology/approach
The effects are tested using the fixed effects regression models on the unbalanced panel dataset which consists of 10,509 observations for 1,804 enterprises across the ten food sectors over the period 2003-2014. To ensure the consistency of the results, the authors use the three different measures of profitability: return on assets, return on equity and price-cost margin.
Findings
The results suggest that, on average, industry and year effects have little impact on firm profitability variance, and firm-specific effects dominate when seeking to explain firm profitability variance. To the best of the authors’ knowledge, the obtained results are supported by most of the previously published studies.
Practical implications
Based on the findings, the authors encourage future researchers to add, as explanatory factors, governmental policies and to test their impact on firm profitability.
Originality/value
The study helps to fill in the research gap in the field of agribusiness, as, to the best of the authors’ knowledge, no study has been conducted yet in the Czech agribusiness environment. Considering the approach distinguishing the “average” and dominant firms in the sectors, they aim at a methodological contribution to this field of research dealing with firm profitability variation.
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Bo Wang and Tingting Xie
According to construal level theory, close (versus far) psychological distance is associated with low (versus high) construal level. Despite the evidence for discount frame…
Abstract
Purpose
According to construal level theory, close (versus far) psychological distance is associated with low (versus high) construal level. Despite the evidence for discount frame effect, it is unclear whether psychological distance and product nature play moderating roles. In addition, little has been known whether the effect of discount frame can extend to other dependent variables such as willingness to pay (WTP). Driven by construal level theory, five experiments were conducted to explore whether the effect of discount frame is dependent on psychological distance and product nature (i.e. utilitarian versus hedonic product).
Design/methodology/approach
The experimental method was used, with discount frame, psychological distance and product type as the independent variables and purchase intention, attitude towards the advertisement, perceived value and WTP as the dependent variables. Participants were presented with promotion scenarios in which psychological distance and discount format were manipulated. In order to test the generalizability of results, promotional scenarios for both utilitarian (i.e. backpack bag and shampoo) and hedonic products (i.e. scenery ticket and perfume) were presented. Data were collected via the online experiment platform (i.e. www.Credamo.com).
Findings
The authors found an interaction between discount frame and spatial distance in that consumers had more positive attitude toward percent off than amount off under near-spatial distance. However, no interaction was observed between discount frame and temporal, social or hypothetical distance.
Originality/value
Taken together, the current study for the first time reveals that the effect of discount frame is contingent on a specific dimension of psychological distance (i.e. spatial distance), regardless of whether the product is utilitarian or hedonic. Findings from this study for the first time pose a challenge to the notion that construal-level match necessarily leads to more favorable consumer responses, suggesting that there may be a unique mechanism underlying the joint effects of spatial distance and discount frame. The current findings can provide important implications for marketers and retailers in an effort to design effective promotional messages.
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Xianglong Kong, Wenqi Wu, Lilian Zhang, Xiaofeng He and Yujie Wang
This paper aims to present a method for improving the performance of the visual-inertial navigation system (VINS) by using a bio-inspired polarized light compass.
Abstract
Purpose
This paper aims to present a method for improving the performance of the visual-inertial navigation system (VINS) by using a bio-inspired polarized light compass.
Design/methodology/approach
The measurement model of each sensor module is derived, and a robust stochastic cloning extended Kalman filter (RSC-EKF) is implemented for data fusion. This fusion framework can not only handle multiple relative and absolute measurements, but can also deal with outliers, sensor outages of each measurement module.
Findings
The paper tests the approach on data sets acquired by a land vehicle moving in different environments and compares its performance against other methods. The results demonstrate the effectiveness of the proposed method for reducing the error growth of the VINS in the long run.
Originality/value
The main contribution of this paper lies in the design/implementation of the RSC-EKF for incorporating the homemade polarized light compass into visual-inertial navigation pipeline. The real-world tests in different environments demonstrate the effectiveness and feasibility of the proposed approach.
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