An experimental study on feature-based SLAM for multi-legged robots with RGB-D sensors

Author(s):  
Michał R. Nowicki ◽  
Dominik Belter ◽  
Aleksander Kostusiak ◽  
Petr Cížek ◽  
Jan Faigl ◽  
...  

Purpose This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics. Design/methodology/approach Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process. Findings The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory. Research limitations/implications The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research. Practical implications The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining. Originality/value The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Minh Thanh Vo ◽  
Anh H. Vo ◽  
Tuong Le

PurposeMedical images are increasingly popular; therefore, the analysis of these images based on deep learning helps diagnose diseases become more and more essential and necessary. Recently, the shoulder implant X-ray image classification (SIXIC) dataset that includes X-ray images of implanted shoulder prostheses produced by four manufacturers was released. The implant's model detection helps to select the correct equipment and procedures in the upcoming surgery.Design/methodology/approachThis study proposes a robust model named X-Net to improve the predictability for shoulder implants X-ray image classification in the SIXIC dataset. The X-Net model utilizes the Squeeze and Excitation (SE) block integrated into Residual Network (ResNet) module. The SE module aims to weigh each feature map extracted from ResNet, which aids in improving the performance. The feature extraction process of X-Net model is performed by both modules: ResNet and SE modules. The final feature is obtained by incorporating the extracted features from the above steps, which brings more important characteristics of X-ray images in the input dataset. Next, X-Net uses this fine-grained feature to classify the input images into four classes (Cofield, Depuy, Zimmer and Tornier) in the SIXIC dataset.FindingsExperiments are conducted to show the proposed approach's effectiveness compared with other state-of-the-art methods for SIXIC. The experimental results indicate that the approach outperforms the various experimental methods in terms of several performance metrics. In addition, the proposed approach provides the new state of the art results in all performance metrics, such as accuracy, precision, recall, F1-score and area under the curve (AUC), for the experimental dataset.Originality/valueThe proposed method with high predictive performance can be used to assist in the treatment of injured shoulder joints.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mostafa El Habib Daho ◽  
Nesma Settouti ◽  
Mohammed El Amine Bechar ◽  
Amina Boublenza ◽  
Mohammed Amine Chikh

PurposeEnsemble methods have been widely used in the field of pattern recognition due to the difficulty of finding a single classifier that performs well on a wide variety of problems. Despite the effectiveness of these techniques, studies have shown that ensemble methods generate a large number of hypotheses and that contain redundant classifiers in most cases. Several works proposed in the state of the art attempt to reduce all hypotheses without affecting performance.Design/methodology/approachIn this work, the authors are proposing a pruning method that takes into consideration the correlation between classifiers/classes and each classifier with the rest of the set. The authors have used the random forest algorithm as trees-based ensemble classifiers and the pruning was made by a technique inspired by the CFS (correlation feature selection) algorithm.FindingsThe proposed method CES (correlation-based Ensemble Selection) was evaluated on ten datasets from the UCI machine learning repository, and the performances were compared to six ensemble pruning techniques. The results showed that our proposed pruning method selects a small ensemble in a smaller amount of time while improving classification rates compared to the state-of-the-art methods.Originality/valueCES is a new ordering-based method that uses the CFS algorithm. CES selects, in a short time, a small sub-ensemble that outperforms results obtained from the whole forest and the other state-of-the-art techniques used in this study.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Rong Yang ◽  
Dianhua Wang

Product ratings are popular tools to support buying decisions of consumers, which are also valuable for online retailers. In online marketplaces, vendors can use rating systems to build trust and reputation. To build trust, it is really important to evaluate the aggregate score for an item or a service. An accurate aggregation of ratings can embody the true quality of offerings, which is not only beneficial for providers in adjusting operation and sales tactics, but also helpful for consumers in discovery and purchase decisions. In this paper, we propose a hierarchical aggregation model for reputation feedback, where the state-of-the-art feature-based matrix factorization models are used. We first present our motivation. Then, we propose feature-based matrix factorization models. Finally, we address how to utilize the above modes to formulate the hierarchical aggregation model. Through a set of experiments, we can get that the aggregate score calculated by our model is greater than the corresponding value obtained by the state-of-the-art IRURe; i.e., the outputs of our models can better match the true rank orders.


2015 ◽  
Vol 21 (5) ◽  
pp. 966-987 ◽  
Author(s):  
Marlen Hofmann ◽  
Hans Betke ◽  
Stefan Sackmann

Purpose – The application of business process methods in the domain of disaster response management (DRM) is seen as promising approach due to the similarity of business processes and disaster response processes at the general structure and goals. But up to now only a few approaches were able to handle the special characteristics of the DRM domain. Thus, the purpose of this paper is to identify the existing approaches and analyze them for the discussion of general requirements for applying methods and tools from business process management to DRM. Design/methodology/approach – A structured literature review covering a wide field of information system-related publications (conferences and journals) is used to identify and classify general requirements discussed as the state of the art. Findings – The work in this paper resulted in a suitable classification of requirements for the development of process-oriented DRM approaches deduced from the existing work. This was used to outline and analyze the current research landscape of this topic and identify research gaps as well as existing limitations. Research limitations/implications – Although the review of the state of the art is based on a wide set of publication databases, there may exist relevant research papers which have not been taken into consideration. Originality/value – The elaborated requirements provide value for both the research community and practitioners. They can be considered to develop new or improve existing DRM systems and, thus, to exploit the potentials of process-oriented IT in supporting DRM in the case of disaster.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Mohamad Mouazen ◽  
Ana Beatriz Hernández-Lara

Purpose Smart cities attract efficient and profitable economic activities, contribute to the societal welfare of their citizens and foster the efficient use and conservation of natural resources. Developing smart cities has become a priority for many developed countries, but as they are preferred destinations for migrants, this raises sustainability issues. They attract people who are seeking a better quality of life, smart services and solutions, a better environment and business activities. The purpose of this paper is to review the state of the art on the relationship between smart cities and migration, with a view to determining sustainability. Design/methodology/approach A bibliometric review and text mining analyses were conducted on publications between 2000 and 2019. Findings The results determined the main parameters of this research topic in terms of its growth, top journals and articles. The role of sustainability in the relationship between smart cities and migration is also identified, highlighting the special interest of its social dimension. Originality/value A bibliometric approach has not been used previously to investigate the link between smart cities and migration. However, given the current relevance of both phenomena, their emergence and growth, this approach is appropriate in determining the state of the art and its main descriptors, with special emphasis on the sustainability implications.


2020 ◽  
Vol 32 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Mauro Cavallone ◽  
Rocco Palumbo

PurposeIndustry 4.0, artificial intelligence and digitalization have got a momentum in health care. However, scholars and practitioners do not agree on their implications on health services' quality and effectiveness. The article aims at shedding light on the applications, aftermaths and drawbacks of industry 4.0 in health care, summarizing the state of the art.Design/methodology/approachA systematic literature review was undertaken. We arranged an ad hoc research design, which was tailored to the study purposes. Three citation databases were queried. We collected 1,194 scientific papers which were carefully considered for inclusion in this systematic literature review. After three rounds of analysis, 40 papers were taken into consideration.FindingsIndustry 4.0, artificial intelligence and digitalization are revolutionizing the design and the delivery of care. They are expected to enhance health services' quality and effectiveness, paving the way for more direct patient–provider relationships. In addition, they have been argued to allow a more appropriate use of available resources. There is a dark side of health care 4.0 involving both management and ethical issues.Research limitations/implicationsIndustry 4.0 in health care should not be conceived as a self-nourishing innovation; rather, it needs to be carefully steered at both the policy and management levels. On the one hand, comprehensive governance models are required to realize the full potential of health 4.0. On the other hand, the drawbacks of industry 4.0 should be timely recognized and thoroughly addressed.Originality/valueThe article contextualizes the state of the art of industry 4.0 in the health care context, providing some insights for further conceptual and empirical developments.


2015 ◽  
Vol 18 (2) ◽  
pp. 150-171 ◽  
Author(s):  
Marco Greco ◽  
Michele Grimaldi ◽  
Livio Cricelli

Purpose – The purpose of this paper is to identify the recurrences in the empirical evidences that link open innovation (OI) actions and innovation performance in European countries. It provides managers with useful strategic suggestions, emphasizes the limitations of the state of the art, and recommends future directions of research. Design/methodology/approach – The authors systematically reviewed empirical articles linking OI actions and innovation performance in European countries, published on peer reviewed journals from January 2003 until May 2013. The authors organized the evidences according to a novel taxonomy grounded in the literature. Findings – The paper shows an increasing interest in the research of empirical evidence regarding OI and innovation performance. Nonetheless, evidence of the role played by outbound OI activities are extremely rare. The authors found that process innovations are more likely to benefit from coupled OI activities rather than inbound activities. Moreover, the effect of coupled depth actions on both product and process innovation performance was always positive in the reviewed articles. The authors also discuss how scholars measure innovation performance, pointing out the criticalities. Research limitations/implications – The paper allows analysing the empirical evidences found in the literature, emphasizing the limitations of the state of the art and recommending future directions of research. Practical implications – The systematization of the empirical evidences found in the European literature provides managers with useful strategic suggestions to improve their organizations’ innovation performances. Originality/value – The paper contains a complete and extensive analysis of empirical OI literature with respect to European countries. The articles and their findings are organized according to a novel taxonomy useful to identify evidences and recurrences in a synoptic manner.


2017 ◽  
Vol 30 (3) ◽  
pp. 811-825 ◽  
Author(s):  
Kawthar Bouchemal ◽  
Christian Bories ◽  
Philippe M. Loiseau

SUMMARY The last estimated annual incidence of Trichomonas vaginalis worldwide exceeds that of chlamydia and gonorrhea combined. This critical review updates the state of the art on advances in T. vaginalis diagnostics and strategies for treatment and prevention of trichomoniasis. In particular, new data on treatment outcomes for topical administration of formulations are reviewed and discussed.


2014 ◽  
Vol 34 (2) ◽  
pp. 123-127 ◽  
Author(s):  
Eujin Pei

Purpose – This feature article aims to review state-of-the-art developments in additive manufacture, in particular, 4D printing. It discusses what it is, what research has been carried out and maps potential applications and its future impact. Design/methodology/approach – The article first defines additive manufacturing technologies and goes on to describe the state-of-the-art. Following which the paper examines several case studies and maps a trend that shows an emergence of 4D printing. Findings – The case studies highlight a particular specialization within additive manufacture where the use of adaptive, biomimetic composites can be programmed to reshape, or have embedded properties or functionality that transform themselves when subjected to external stimuli. Originality/value – This paper discusses the state-of-the-art of additive manufacture, discussing strategies that can be used to reduce the print process (such as through kinematics); and the use of smart materials where parts adapt themselves in response to the surrounding environment supporting the notion of self-assemblies.


2014 ◽  
Vol 19 (5/6) ◽  
pp. 592-608 ◽  
Author(s):  
Hella Abidi ◽  
Sander de Leeuw ◽  
Matthias Klumpp

Purpose – This paper aims to identify the state of the art of performance measurement and management in humanitarian supply chains; to categorize performance measurement indicators in the five supply chain phases of Gunasekaran and Kobu (2007) and evaluate them based on the evaluation criteria of Caplice and Sheffi (1995); and to define gaps and challenges in this field and give insights for future research in this domain. Design/methodology/approach – A literature review has been conducted using a structured method based on Denyer and Tranfield (2009) and Rousseau et al. (2008). The state of the art on humanitarian supply chain performance management with a focus on measurement frameworks and indicators and their applications in practice is classified in three categories. The first category is the definition and measurement of success in humanitarian supply chains. The second category is managing performance, which focuses on describing and analyzing the actual practice of managing performance. The third category shows the challenges in performance management that humanitarian supply chain actors deal with. Findings – Findings reveal that performance measurement and management in humanitarian supply chains is still an open area of research, especially compared to the commercial supply chain sector. Furthermore, the research indicates that performance measurement and management in humanitarian supply chains has to be developed in support of the supply chain strategy. Based on the findings of the literature review on performance measurement and management in the commercial and humanitarian field, a first classification of 94 performance measurement indicators in humanitarian supply chains is presented. Furthermore, the paper shows key problems why performance measurement and management systems have not been widely developed and systematically implemented in humanitarian supply chains and are not part of the supply chain strategy. The authors propose performance measurement guidelines that include input and output criteria. They develop a research agenda that focuses on four research questions for designing, deploying and disseminating performance measurement and management in humanitarian supply chains. Practical implications – The result helps the humanitarian supply chain community to conduct further research in this area and to develop performance measurement frameworks and indicators that suit humanitarian supply chains. Originality/value – It is the first systematic approach to categorize research output regarding performance measurement and management in humanitarian supply chains. The paper shows the state of the art in performance measurement and management in humanitarian supply chains and develops a research agenda.


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