Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1926

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17th International Conference on Mechatronics Technology, October 15-18, 2013, Jeju Island, Korea
(Elsevier, 2015) Hwang, Sung Ho; Kim, Joon-wan; Dorantes-Gonzalez, Dante Jorge
In recent years, Mechatronics has gained a lot of interest as more applications have been introduced to industry and society. The need for new mechatronic technologies in the form of advanced production systems, mechatronic devices, control systems, robotics, biomedical applications, MEMS, and measurement systems, among others, is very much required in improving productivity and competitiveness in many industries. Thus, this conference was organized to address the state-of-the-art technology for the benefit of researchers and users, and this time the conference made a special focus on the topic: Sustainable Mechatronics Technology.
Citation - WoS: 7
Citation - Scopus: 8
A 32-Society Investigation of the Influence of Perceived Economic Inequality on Social Class Stereotyping
(Wiley, 2022) Ashokkumar, Ashwini; Billet, Matthew; Becker, Maja; Peters, Kim; Jetten, Joland; Barry, Oumar; Tanjitpiyanond, Porntida; Peker, Müjde
There is a growing body of work suggesting that social class stereotypes are amplified when people perceive higher levels of economic inequality—that is, the wealthy are perceived as more competent and assertive and the poor as more incompetent and unassertive. The present study tested this prediction in 32 societies and also examines the role of wealth-based categorization in explaining this relationship. We found that people who perceived higher economic inequality were indeed more likely to consider wealth as a meaningful basis for categorization. Unexpectedly, however, higher levels of perceived inequality were associated with perceiving the wealthy as less competent and assertive and the poor as more competent and assertive. Unpacking this further, exploratory analyses showed that the observed tendency to stereotype the wealthy negatively only emerged in societies with lower social mobility and democracy and higher corruption. This points to the importance of understanding how socio-structural features that co-occur with economic inequality may shape perceptions of the wealthy and the poor. © 2022 The Authors. European Journal of Social Psychology published by John Wiley & Sons Ltd.
Citation - WoS: 149
Citation - Scopus: 181
A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making
(MDPI, 2023) Abacıoğlu, Seda; Ayan, Büşra; Basilio, Marcio Pereira
In the realm of multi-criteria decision-making (MCDM) problems, the selection of a weighting method holds a critical role. Researchers from diverse fields have consistently employed MCDM techniques, utilizing both traditional and novel methods to enhance the discipline. Acknowledging the significance of staying abreast of such methodological developments, this study endeavors to contribute to the field through a comprehensive review of several novel weighting-based methods: CILOS, IDOCRIW, FUCOM, LBWA, SAPEVO-M, and MEREC. Each method is scrutinized in terms of its characteristics and steps while also drawing upon publications extracted from the Web of Science (WoS) and Scopus databases. Through bibliometric and content analyses, this study delves into the trend, research components (sources, authors, countries, and affiliations), application areas, fuzzy implementations, hybrid studies (use of other weighting and/or ranking methods), and application tools for these methods. The findings of this review offer an insightful portrayal of the applications of each novel weighting method, thereby contributing valuable knowledge for researchers and practitioners within the field of MCDM.
Citation - WoS: 3
Citation - Scopus: 1
A Configurational Analysis of the Impact of Entrepreneurial Orientation and Global Mindset on Export Performance of Smes
(SAGE Publications Inc., 2024) Matemane, R.; Mintah, R.; Şahin, F.; Karadağ, H.
Although contemporary literature provides several important insights into the role of attributes of SMEs, there is much less evidence on what configuration of entrepreneurial orientation and global mindset makes this process successful, that is, contributing to the export performance of SMEs. This study uses a fuzzy set qualitative comparative analysis on a sample of 97 SMEs in Ghana to explore the potential complementary role between the entrepreneurial orientation dimensions and global mindset for superior export performance. The results indicate two different yet equifinal configurations of these factors that lead to a high level of export performance of SMEs. One of the configurations shows that proactive and innovative SMEs with managers high on global mindset achieve superior export performance regardless of their willingness to take risks. Another configuration indicates that regardless of the global mindset of managers, SMEs can achieve higher export performance by being proactive, innovative, and willing to take high risks. Several implications for theory and practice are discussed based on the findings. © The Author(s) 2024.
Citation - WoS: 1
Citation - Scopus: 1
A Decomposition Algorithm for Single and Multiobjective Integrated Market Selection and Production Planning
(Informs, 2023) van den Heuvel, Wilco; Ağralı, Semra; Taşkın, Z. Caner
We study an integrated market selection and production planning problem. There is a set of markets with deterministic demand, and each market has a certain revenue that is obtained if the market's demand is satisfied throughout a planning horizon. The demand is satisfied with a production scheme that has a lot-sizing structure. The problem is to decide on which markets' demand to satisfy and plan the production simultaneously. We consider both single and multiobjective settings. The single objective problem maximizes the profit, whereas the multiobjective problem includes the maximization of the revenue and the minimization of the production cost objectives. We develop a decomposition-based exact solution algorithm for the single objective setting and show how it can be used in a proposed three-phase algorithm for the multiobjective setting. The master problem chooses a subset of markets, and the subproblem calculates an optimal production plan to satisfy the selected markets' demand. We investigate the subproblem from a cooperative game theory perspective to devise cuts and strengthen them based on lifting. We also propose a set of valid inequalities and preprocessing rules to improve the proposed algorithm. We test the efficacy of our solution method over a suite of problem instances and show that our algorithm substantially decreases solution times for all problem instances.
A Lot-Sizing Problem in Deliberated and Controlled Co-Production Systems
(Taylor and Francis, 2021) Kabakulak, Banu; Ağralı, Semra; Taşkın, Z. Caner; Pamuk, Bahadır
We consider an uncapacitated lot sizing problem in co-production systems, in which it is possible to produce multiple items simultaneously in a single production run. Each product has a deterministic demand to be satisfied on time. The decision is to choose which items to co-produce and the amount of production throughout a predetermined planning horizon. We show that the lot sizing problem with co-production is strongly NP-Hard. Then, we develop various mixed-integer linear programming (MILP) formulation of the problem and show that LP relaxations of all MILPs are equal. We develop a separation algorithm based on a set of valid inequalities, lower bounds based on a dynamic lot-sizing relaxation of our problem and a constructive heuristic that is used to obtain an initial solution for the solver, which form the basis of our proposed Branch & Cut algorithm for the problem. We test our models and algorithms on different data sets and provide the results.
Citation - WoS: 3
Citation - Scopus: 4
A Machine Learning Approach To Resolving Conflicts in Physical Human-Robot Interaction
(Association for Computing Machinery, 2025) Ulas Dincer, Enes; Al-Saadi, Zaid; Hamad, Y.M.; Aydın, Yusuf; Kucukyilmaz, A.; Basdogan, C.
As artificial intelligence techniques become more sophisticated, we anticipate that robots collaborating with humans will develop their own intentions, leading to potential conflicts in interaction. This development calls for advanced conflict resolution strategies in physical human-robot interaction (pHRI), a key focus of our research. We use a machine learning (ML) classifier to detect conflicts during co-manipulation tasks to adapt the robot's behavior accordingly using an admittance controller. In our approach, we focus on two groups of interactions, namely "harmonious"and "conflicting,"corresponding respectively to the cases of the human and the robot working in harmony to transport an object when they aim for the same target, and human and robot are in conflict when human changes the manipulation plan, e.g. due to a change in the direction of movement or parking location of the object.Co-manipulation scenarios were designed to investigate the efficacy of the proposed ML approach, involving 20 participants. Task performance achieved by the ML approach was compared against three alternative approaches: (a) a rule-based (RB) Approach, where interaction behaviors were rule-derived from statistical distributions of haptic features; (b) an unyielding robot that is proactive during harmonious interactions but does not resolve conflicts otherwise, and (c) a passive robot which always follows the human partner. This mode of cooperation is known as "hand guidance"in pHRI literature and is frequently used in industrial settings for so-called "teaching"a trajectory to a collaborative robot.The results show that the proposed ML approach is superior to the others in task performance. However, a detailed questionnaire administered after the experiments, which contains several metrics, covering a spectrum of dimensions to measure the subjective opinion of the participants, reveals that the most preferred mode of interaction with the robot is surprisingly passive. This preference indicates a strong inclination toward an interaction mode that gives more control to humans and offers less demanding interaction, even if it is not the most efficient in task performance. Hence, there is a clear trade-off between task performance and the preferred mode of interaction of humans with a robot, and a well-balanced approach is necessary for designing effective pHRI systems in the future. © 2025 Copyright held by the owner/author(s).
Citation - WoS: 6
Citation - Scopus: 6
A New Approach for Measuring Viscoelastic Properties of Soft Materials Using the Dynamic Response of a Spherical Object Placed at the Sample Interface
(Springer, 2023) Besli, Ayça; Koç,Ömer Hayati; Körük,Hasan; Yurdaer, Berk Salih
Background: There are several techniques to characterize the mechanical properties of soft materials, such as the indentation method and the method based on the application of a spherical object placed inside the sample. The indentation systems usually yield the elastic properties of materials and their mathematical models do not consider the inertia of the sample involved in motion and radiation damping, while placing an object inside the sample is not practical and this procedure can alter the mechanical properties of the sample for the method based on the application of a bubble/sphere placed inside the sample. Objective: A new approach for the identification of the viscoelastic properties of soft materials using the dynamic response of a spherical object placed at the sample interface was proposed. Methods: The spherical object placed at the sample interface was pressed using an electromagnet and the dynamic response of the spherical object was tracked using a high-speed camera, while the dynamic response of the spherical object placed at the sample interface was estimated using a comprehensive analytical model. The effects of the shear modulus, viscosity, Poisson’s ratio and density of the soft sample, the radius and density of the spherical object and the damping due to radiation were considered in this mathematical model. The shear modulus and viscosity of the soft sample were determined by matching the experimentally identified and theoretically estimated responses of the spherical object. Results: The shear moduli and viscosities of the three phantoms with the gelatin mass ratios of 0.20, 0.25 and 0.29 were measured to be 3450, 4300 and 4950 Pa and 12.5, 14.0 and 15.0 Pa⋅s, respectively. The shear modulus and viscosity of the phantom increases as the gelatin mass ratio increases. The frequency of oscillations of the hemisphere placed at the phantom interface increases as the gelatin mass ratio increases due to stiffness increase. Conclusions: After matching the experimental and theoretical steady-state displacements and amplitudes of oscillations of the hemisphere at the sample interface, the comparison of the experimentally identified and theoretically predicted frequency of oscillations further confirmed the identified material properties of the samples. The approach presented here is expected to provide valuable information on material properties in biomedical and industrial applications.
A New Benchmark Dataset for P300 Erp-Based Bci Applications
(Academic Press Inc Elsevier Science, 2023) Çakar, Tuna; Özkan, Hüseyin; Musellim, Serkan; Arslan, Suayb S.; Yağan, Mehmet; Alp, Nihan
Because of its non-invasive nature, one of the most commonly used event-related potentials in brain -computer interface (BCI) system designs is the P300 electroencephalogram (EEG) signal. The fact that the P300 response can easily be stimulated and measured is particularly important for participants with severe motor disabilities. In order to train and test P300-based BCI speller systems in more realistic high-speed settings, there is a pressing need for a large and challenging benchmark dataset. Various datasets already exist in the literature but most of them are not publicly available, and they either have a limited number of participants or utilize relatively long stimulus duration (SD) and inter-stimulus intervals (ISI). They are also typically based on a 36 target (6 x 6) character matrix. The use of long ISI, in particular, not only reduces the speed and the information transfer rates (ITRs) but also oversimplifies the P300 detection. This leaves a limited challenge to state-of-the-art machine learning and signal processing algorithms. In fact, near-perfect P300 classification accuracies are reported with the existing datasets. Therefore, one certainly needs a large-scale dataset with challenging settings to fully exploit the recent advancements in algorithm design (machine learning and signal processing) and achieve high-performance speller results. To this end, in this article we introduce a new freely-and publicly-accessible P300 dataset obtained using 32-channel EEG, in the hope that it will lead to new research findings and eventually more efficient BCI designs. The introduced dataset comprises 18 participants performing a 40 -target (5 x 8) cued-spelling task, with reduced SD (66.6 ms) and ISI (33.3 ms) for fast spelling. We have also processed, analyzed, and character-classified the introduced dataset and we presented the accuracy and ITR results as a benchmark. The introduced dataset and the codes of our experiments are publicly accessible at https://data .mendeley.com /datasets /vyczny2r4w.(c) 2023 Elsevier Inc. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 2
A New Learning Community for Educating Future Teachers: Online Baboratory School
(Taylor and Francis Ltd., 2022) Pekkan, Tunç Zelha; Taylan, Didem Rukiye
To provide quality mathematics education for disadvantaged groups of middle school students and continue to offer quality practicum experience to future teachers during the Covid 19 outbreak, we founded the Online Laboratory School. This school was free and open to public school students: 130 middle school students throughout Turkey attended for a 5-week period. There were 25 pre-service teachers actively involved in teaching, under the close supervision of 7 university supervisors. The entire gamut of planning, teaching and reflection sessions for each virtual class were recorded via an e-learning platform. Additionally, survey data was collected from the participating students, parents, pre-service teachers and supervisors. Our findings indicate that we were able to build a unique and virtual learning community. While pre-service teachers and middle school students benefited the most, university supervisors also reported improving their skills on when and how to give feedback. We describe how the school functioned and the range of opportunities it provided to all participants considering situated-learning perspectives and building online-learning communities. We also discuss how this model can be used in the future as a strong asset for teacher education programs and adaptation of fieldwork practices.
Citation - WoS: 1
Citation - Scopus: 2
A Novel Genetic Algorithm-Based Improvement Model for Online Communities and Trust Networks
(IOS Press, 2020) Bekmezci, ilker; Cimen, Egemen Berkic; Ermiş, Murat
Social network analysis offers an understanding of our modern world, and it affords the ability to represent, analyze and even simulate complex structures. While an unweighted model can be used for online communities, trust or friendship networks should be analyzed with weighted models. To analyze social networks, it is essential to produce realistic social models. However, there are serious differences between social network models and real-life data in terms of their fundamental statistical parameters. In this paper, a genetic algorithm (GA)-based social network improvement method is proposed to produce social networks more similar to real-life data sets. First, it creates a social model based on existing studies in the literature, and then it improves the model with the proposed GA-based approach based on the similarity of the average degree, the k-nearest neighbor, the clustering coefficient, degree distribution and link overlap. This study can be used to model the structural and statistical properties of large-scale societies more realistically. The performance results show that our approach can reduce the dissimilarity between the created social networks and the real-life data sets in terms of their primary statistical properties. It has been shown that the proposed GA-based approach can be used effectively not only in unweighted networks but also in weighted networks.
Citation - WoS: 3
Citation - Scopus: 4
A Novel Graph Transformation Strategy for Optimizing Sptrsv on Cpus
(Wiley, 2023) Yılmaz, Buse
Sparse triangular solve (SpTRSV) is an extensively studied computational kernel. An important obstacle in parallel SpTRSV implementations is that in some parts of a sparse matrix the computation is serial. By transforming the dependency graph, it is possible to increase the parallelism of the parts that lack it. In this work, we present a novel graph transformation strategy to increase the parallelism degree of a sparse matrix and compare it to our previous strategy. It is seen that our transformation strategy can provide a speedup as high as 1.42x$$ 1.42x $$.
Citation - WoS: 1
Citation - Scopus: 1
A Novel Plasma-Facing Ndb6 Particulate Reinforced W1ni Matrix Composite: Powder Metallurgical Fabrication, Microstructural and Mechanical Characterization
(Elsevier Sci Ltd, 2024) Boztemur, Burçak; Öveçoğlu, Mustafa Lutfi; Luo, Laima; Ağaoğulları, Duygu; Xu, Yue; Alkraidi, Ammar
Tungsten (W) is one of best candidate metal for plasma-facing materials (PFM), especially due to its high melting temperature and neutron absorption capability. However, converting W into bulk PFM is hard because of its high melting point. This problem can be solved by adding metallic sintering aids with low melting points. In this study, W matrix with 1 wt% Ni aid was reinforced by adding NdB6 particles (1, 5, and 10 wt%). It can be introduced as a novel potential PFM, thanks to its low volatility and high neutron absorbability. The ceramic and composite powders produced via mechanochemical synthesis and mechanical alloying were examined in terms of composition, particle size, crystallite size, and lattice strain. Samples sintered via pressureless sintering (PS) and spark plasma sintering (SPS) were microstructurally analyzed by using an X-ray diffractometer (XRD), a scanning electron microscope (SEM) attached with an energy dispersive spectroscope (EDS), and mechanically analyzed in terms of microhardness and wear behavior. Based on the results, W2B and WB phases emerged in the SPS'ed W1Ni-5NdB6 and PS'ed./SPS'ed W1Ni-10NdB6 composites. SPS'ed W1Ni-10NdB6 composite had the highest hardness value and the lowest specific wear rate. The SPS'ed W1Ni-5NdB6 composite showed fewer surface damages and higher irradiation resistance as compared with other samples after exposure of He+ irradiation.
A Strategy to Engage Students in Inquiry-Based Learning of Mathematics: Predict, Observe and Explain
(Springer, 2025) Karakoc, Gokhan; Alacaci, Cengiz; Ayas, Alipasa
The current research implemented the Predict Observe and Explain (POE) instructional approach in mathematics and examined its efficacy in enhancing students' understanding of functions in terms of their ability to connect algebraic and graphical representations in optimization problems. Two grade 11 classes (40 students in total) and two grade 10 classes (42 students in total) participated in this study, for a combined total of 82 students. Following a quasi-experimental design, students in the experimental group solved six open mathematical tasks in a small group setting. They were explicitly asked to predict the outcome before attempting to solve the tasks, make observations using concrete materials and finally attempt a solution. They were then expected to reflect on their observation and initial predictions to interpret their findings. The control group students were given the same tasks without an explicit heuristic. They directly attempted to solve the same problems without prediction and observation. The data were collected using students' written responses to each task. Students' responses to the tasks were assessed based on the following criteria: understanding, constructing, using a mathematical model, communicating and interpreting results. An independent samples t-test showed that the POE strategy improved students' learning in cognitive domains. The POE strategy helped students better understand the problem, select and apply appropriate mathematical methods and interpret their findings. Students in the control group spent more time discussing and integrating clues into possible solutions to the given tasks. The results were interpreted within the framework of inquiry-based education, informed by semiotic representation theory.
Citation - WoS: 9
Citation - Scopus: 11
A Value-Adding Approach To Reliability Under Preventive Maintenance Costs and Its Applications
(2014) Dubey, Rameshwar; Kılıç, Erdem; Ali, Sadia Samar; Weber, Gerhard Wilhelm
No equipment (system) can be perfectly reliable in spite of the utmost care and best efforts on the part of the designer, decision-maker and manufacturer. The two sides of maintenance are corrective and preventive maintenance. It is generally assumed that a preventive maintenance action is less costly than a repair maintenance action. We examine this proposition in detail on the basis of a failure-time model that relates conformance quality to reliability. Illustratively, we present reliability in the context of contracts with asymmetric information. The model shows how to overcome information rents through price distortions and quantity rationing. The paper ends with a conclusion and an outlook to future studies.
Citation - WoS: 13
Citation - Scopus: 17
Acoustic Streaming in a Soft Tissue Microenvironment
(Elsevier, 2019) El Ghamrawy, Ahmed; Mohammed, Ali; Jones, Julian R; Körük, Hasan; Choi, James J; de Comtes, Florentina
We demonstrated that sound can push fluid through a tissue-mimicking material. Although acousticstreaming in tissue has been proposed as a mechanism for biomedical ultrasound applications, such as neuromodu-lation and enhanced drug penetration, streaming in tissue or acoustic phantoms has not been directly observed. Wedeveloped a material that mimics the porous structure of tissue and used a dye and a video camera to track fluidmovement. When applied above an acoustic intensity threshold, a continuous focused ultrasound beam (spatialpeak time average intensity: 238 W/cm2, centre frequency: 5 MHz) was found to push the dye axially, that is, in thedirection of wave propagation and in the radial direction. Dye clearance increased with ultrasound intensity andwas modelled using an adapted version of Eckart’s acoustic streaming velocity equation. No microstructuralchanges were observed in the sonicated region when assessed using scanning electron microscopy. Our study indi-cates that acoustic streaming can occur in soft porous materials and provides a mechanistic basis for future use ofstreaming for therapeutic or diagnostic purposes.
Citation - WoS: 42
Citation - Scopus: 50
Adaptive Human Force Scaling Via Admittance Control for Physical Human-Robot Interaction
(IEEE, 2021) Başdoğan, Çağatay; Aydın, Yusuf; Hamad, Yahya M.
The goal of this article is to design an admittance controller for a robot to adaptively change its contribution to a collaborative manipulation task executed with a human partner to improve the task performance. This has been achieved by adaptive scaling of human force based on her/his movement intention while paying attention to the requirements of different task phases. In our approach, movement intentions of human are estimated from measured human force and velocity of manipulated object, and converted to a quantitative value using a fuzzy logic scheme. This value is then utilized as a variable gain in an admittance controller to adaptively adjust the contribution of robot to the task without changing the admittance time constant. We demonstrate the benefits of the proposed approach by a pHRI experiment utilizing Fitts’ reaching movement task. The results of the experiment show that there is a) an optimum admittance time constant maximizing the human force amplification and b) a desirable admittance gain profile which leads to a more effective co-manipulation in terms of overall task performance.
Citation - WoS: 18
Citation - Scopus: 18
Adding Rapid-Acting Insulin or Glp-1 Receptor Agonist To Basal Insulin: Outcomes in a Community Setting
(2015) Dalal, Mehul R; DiGenio, Andres; Xie, Lin; Başer, Onur
To evaluate real-world outcomes in patients with type 2 diabetes mellitus (T2DM)receiving basal insulin, who initiate add-on therapy with a rapid-acting insulin (RAI) or aglucagon-like peptide 1 (GLP-1) receptor agonist.Data were extracted retrospectively from a U.S. health claims database. Adults withT2DM on basal insulin who added an RAI (basal+RAI) or GLP-1 receptor agonist (basal+GLP-1) were included. Propensity score matching (1 up to 3 ratio) was used to control for differencesin baseline demographics, clinical characteristics, and health resource utilization. Endpointsincluded prevalence of hypoglycemia, pancreatic events, all-cause and diabetes-relatedresource utilization, and costs at 1 year follow-up. Overall, 6,718 matched patients were included: 5,013 basal+RAI and 1,705basal+GLP1. Patients in both groups experienced a similar proportion of any hypoglycemicevent (P = .4079). Hypoglycemic events leading to hospitalization were higher in the basal+RAIcohort (2.7% vs. 1.8%; P = .0444). The basal+GLP-1 cohort experienced fewer all-cause(13.55% vs. 18.61%; P<.0001) and diabetes-related hospitalizations (11.79% vs. 15.68%;P<.0001). The basal+GLP-1 cohort had lower total all-cause health care costs ($18,413 vs.$20,821; P = .0002), but similar diabetes-related costs ($9,134 vs. $8,985; P<.0001) comparedwith the basal+RAI cohort. Add-on therapy with a GLP-1 receptor agonist in T2DM patients receiving basalinsulin was associated with fewer hospitalizations and lower total all-cause costs compared withadd-on therapy using a RAI, and could be considered an alternative to a RAI in certain patientswith T2DM, who do not achieve effective glycemic control with basal insulin.
Citation - WoS: 47
Citation - Scopus: 71
Adoption and Use of Learning Management Systems in Education: the Role of Playfulness and Self-Management
(MDPI [Commercial Publisher], 2021) Akküçük, Ulaş; Balkaya, Selen
This article investigates the factors affecting primary and secondary education teachers' behavioral intention to adopt learning management systems (LMSs). Information technology (IT) innovations have the power to change the way we work, educate, learn, and basically the way we live. The effect of IT innovations on education makes it critical to understand the current usage situation of LMSs and the factors affecting their adoption by teachers. The unified theory of acceptance and use of technology (UTAUT) was extended with factors from education and game-based learning literature. In order to see the effect of individual- and organizational-level characteristics, multi-group structural equation modeling (SEM) analysis was conducted and discrepancies in relationships were reported. Evaluation of users and non-users and teachers of different fields were also compared to each other. The findings of this study not only contribute to theory through the development and testing of a thorough model relating technology features and individual characteristics to behavioral intention to use, but also offer strong implications for practitioners who would like to increase LMS usage and create a more effective learning environment.
Citation - WoS: 22
Citation - Scopus: 24
An Adaptive Admittance Controller for Collaborative Drilling With a Robot Based on Subtask Classification Via Deep Learning
(Elsevier, 2022) Başdoğan, Çağatay; Niaz, P. Pouya; Aydın, Yusuf; Güler, Berk; Madani, Alireza
In this paper, we propose a supervised learning approach based on an Artificial Neural Network (ANN) model for real-time classification of subtasks in a physical human–robot interaction (pHRI) task involving contact with a stiff environment. In this regard, we consider three subtasks for a given pHRI task: Idle, Driving, and Contact. Based on this classification, the parameters of an admittance controller that regulates the interaction between human and robot are adjusted adaptively in real time to make the robot more transparent to the operator (i.e. less resistant) during the Driving phase and more stable during the Contact phase. The Idle phase is primarily used to detect the initiation of task. Experimental results have shown that the ANN model can learn to detect the subtasks under different admittance controller conditions with an accuracy of 98% for 12 participants. Finally, we show that the admittance adaptation based on the proposed subtask classifier leads to 20% lower human effort (i.e. higher transparency) in the Driving phase and 25% lower oscillation amplitude (i.e. higher stability) during drilling in the Contact phase compared to an admittance controller with fixed parameters.

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