Advanced Robotics最新文献

{"title":"Stochastic approach for modeling soft fingers with creep behavior","authors":"Sumitaka Honji, Hikaru Arita, Kenji Tahara","doi":"10.1080/01691864.2023.2279600","DOIUrl":"https://doi.org/10.1080/01691864.2023.2279600","url":null,"abstract":"AbstractSoft robots have high adaptability and safety due to their softness and are therefore widely used in human society. However, the controllability of soft robots to perform dexterous behaviors is insufficient when considering soft robots as alternative laborers for humans. Model-based control methods are effective for achieving dexterous behaviors. To build a suitable control model, problems based on specific properties, such as creep behavior and variable motions, must be addressed. In this paper, a lumped parameterized model for soft fingers with viscoelastic joints is established to address creep behavior. The parameters are expressed as distributions, which allows the model to account for motion variability. Furthermore, stochastic analyzes are performed based on the parameter distributions. The model results are consistent with the experimental results, and the model enables the investigation of the effects of various parameters related to robot variability.Keywords: Lumped parameterized modeldistributed viscoelastic parameterrandom variable transformationsensitivity analysis AcknowledgmentsWe greatly appreciate the funding sources. Additionally, we would like to thank the members of the HCR lab for their useful discussions.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Grant-in-Aid for Scientific Research (A) No. 20H00610 of the Japan Society for the Promotion of Science (JSPS).Notes on contributorsSumitaka HonjiSumitaka Honji received the B.S. and M.S. degrees from the Department of Mechanical Engineering in the School of Engineering, Kyushu University, Japan, in 2019 and 2021, respectively. He is now a doctoral student at Kyushu University. His interests include the modeling and control of soft robotic systems.Hikaru AritaHikaru Arita received his B.S., M.S., and Ph.D. in engineering from the University of Electro-Communications, Japan, in 2012, 2014, and 2019. He served several institutions, including OMRON Corporation, Kyoto, Japan, where he worked from 2014 to 2016, and Ritsumeikan University, where he was an Assistant Professor from 2019 to 2022. He is currently an Assistant Professor at the Department of Mechanical Engineering, Faculty of Engineering, Kyushu University, Japan. His current research interests include proximity sensors, sensor-based control, musculoskeletal robots, robot hands, manipulation, and soft robots.Kenji TaharaKenji Tahara received a B.S. degree in Mech. Eng. in 1998, an M.S. degree in Info. Sci. and Syst. in 2000, and a Ph.D. degree in Robotics in 2003, all from Ritsumeikan University, Japan. From 2003 to 2007, he joined the Bio-mimetic Control Research Center of RIKEN as a Research Scientist. In 2007, he joined Kyushu University as a tenure-track Associate Professor, and in 2011, he was an Associate Professor at the Department of Mechanical Engineering, Faculty of Engineering, Kyushu University, Japan. Since","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"30 14","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136281679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the relationship between user response to dialog breakdown and personality traits","authors":"Kazuya Tsubokura, Yurie Iribe, Norihide Kitaoka","doi":"10.1080/01691864.2023.2279610","DOIUrl":"https://doi.org/10.1080/01691864.2023.2279610","url":null,"abstract":"AbstractAlthough automated dialog systems are now being used in various applications, it is difficult to say whether they will ever be able to acquire the ability to converse as naturally as people do. As a result, various methods for detecting dialog breakdowns have been proposed. However, the effect of the user's personality on breakdown detection accuracy and user response to these breakdowns have not been sufficiently examined. Therefore, in this study we analyze the relationship between user personality traits and individual differences in responses to dialog breakdowns by conducting dialog experiments.Keywords: Dialog systemdialog breakdownpersonality traits AcknowledgmentThis work was supported by JSPS KAKENHI Grant Numbers JP22K19793, JP23H00493.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 https://taku910.github.io/mecab/.2 When we first calculated the correlations between the part of speech features and the overall personality trait scores, no strong correlations were observed, so we then used the personality trait scores of the upper and lower groups for each personality trait when performing the U-tests, in order to reveal possible relationships.Additional informationNotes on contributorsKazuya TsubokuraKazuya Tsubokura recieved his B.S. and M.S. degrees in Information Science and Technology from Aichi Prefectural University in 2021 and 2023, respectively. He is currently a Ph.D. student in Aichi Prefectural University. His research interests include spoken dialogue systems.Yurie IribeYurie Iribe received the B.E. degree in Systems Engineering from Nagoya Institute of Technology and M.S. degree in Human Informatics from Nagoya University in 1999 and 2001. She became a research associate in the Information and Media Center at Toyohashi University of Technology in 2004. She received her Ph.D. degree from Nagoya University in 2007. She is currently an Associate Professor in Aichi Prefectural University from 2017. Her research interests include speech processing and human interface.Norihide KitaokaNorihide Kitaoka received his B.S. and M.S. degrees from Kyoto University, Japan. In 1994, he joined DENSO CORPORATION. In 2000, he received his Ph.D. degree from Toyohashi University of Technology (TUT), Japan. He joined TUT as a research associate in 2001 and was a lecturer from 2003 to 2006. He was an associate professor at Nagoya University, Japan, from 2006 to 2014 and joined Tokushima University, Japan, as a professor in 2014. He has been a professor at TUT since 2018. His research interests include speech processing, speech recognition, and spoken dialog systems. He is a member of IEEE, International Speech Communication Association (ISCA), Asia Pacific Signal and Information Processing Association (APSIPA), The Institute of Electronics, Information and Communication Engineers (IEICE), Information Processing Society of Japan (IPSJ), Acoustical Society of Japan (ASJ), The Japanese Society for Ar","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"30 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136281683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting cultural identity via robotic sensor data to understand differences during human-robot interaction","authors":"Jinjae Lee, Casey C. Bennett, Cedomir Stanojevic, Seongcheol Kim, Zachary Henkel, Kenna Baugus, Jennifer A. Piatt, Cindy Bethel, Selma Sabanovic","doi":"10.1080/01691864.2023.2277159","DOIUrl":"https://doi.org/10.1080/01691864.2023.2277159","url":null,"abstract":"AbstractSocially-assistive robots (SARs) have significant potential to help manage chronic diseases (e.g. dementia, depression, diabetes) in spaces where people live, averse to clinic-based care. However, the challenge is designing SARs so that they perform appropriate interactions with people who have different characteristics, such as age, gender, and cultural identity. Those characteristics impact how human behaviors are performed as well as user expectations of robot responses. Although cross-cultural studies with robots have been conducted to understand differing population characteristics, they have mainly focused on statistical comparisons of groups. In this study, we utilize deep learning (DL) and machine learning (ML) models to evaluate whether cultural differences show up in robotic sensor data during human-robot interaction (HRI). To do so, a SAR was distributed to user's homes for three weeks in the US and Korea (25 participants), while collecting data on the human activity and the surrounding environment through on-board sensor devices. DL models based on that data were able to predict the user’s cultural identity with roughly 95% accuracy. Such findings have potential implications for the design and development of culturally-adaptive SARs to provide services across diverse cultural locales and multi-cultural environments where users’ cultural background cannot be assumed a priori.KEYWORDS: Human-robot interactiondeep learningcross-cultural roboticsadaptive robot designhuman activity recognition Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by separate funding mechanisms in South Korea and the United States: KOR – Hanyang University Research Fund [grant number HY-2020]; USA – National Science Foundation [grant number IIS-1900683].Notes on contributorsJinjae LeeJinjae Lee is currently a Master’s student in Data Science at the Department of Intelligence Computing at Hanyang University. He is interested in the application of machine learning and human-robot interaction to healthcare problems.Casey C. BennettDr. Casey C. Bennett is an Associate Professor in the Department of Intelligence Computing at Hanyang University in Seoul, Korea. He specializes in artificial intelligence and robotics in healthcare, including the use of data science and machine learning to create better human-robot interaction. He completed his Ph.D. at Indiana University in the US.Cedomir StanojevicDr. Cedomir Stanojevic is an Assistant Professor in the Department of Parks, Recreation & Tourism Management at Clemson University’s College of Behavioral, Social and Health Sciences, SC, U.S.A. He specializes in recreational therapy and interventions related to leisure and improved quality of life, focusing on socially assistive robotics and ecological momentary assessment to improve various populations’ health outcomes. He completed his Ph.D. at Indiana University in the US.Seong","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"30 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136281680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Special Issue on Multimodal processing and robotics for dialogue systems (Part 1)","authors":"David Traum, Gabriel Skantze, Hiromitsu Nishizaki, Ryuichiro Higashinaka, Takashi Minato, Takayuki Nagai","doi":"10.1080/01691864.2023.2276549","DOIUrl":"https://doi.org/10.1080/01691864.2023.2276549","url":null,"abstract":"\"Special Issue on Multimodal processing and robotics for dialogue systems (Part 1).\" Advanced Robotics, 37(21), pp. 1347–1348","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"11 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135972808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory tracking of robot manipulator with adaptive fuzzy second-order super-twisting sliding mode control","authors":"Dachang Zhu, Puchen Zhu, Yonglong He","doi":"10.1080/01691864.2023.2270792","DOIUrl":"https://doi.org/10.1080/01691864.2023.2270792","url":null,"abstract":"AbstractTo solve the influence of uncertainties such as unmodeled errors and external disturbances on the trajectory tracking accuracy of the end-effector of a robot manipulator, a novel fuzzy super-twisting second-order sliding mode control method is proposed in this paper. Based on the dynamic model of the robot manipulator, a second-order sliding mode control algorithm is proposed by using the super-twisting to determine the non-singular terminal sliding manifold. An adaptive fuzzy algorithm is presented to compensate for the super-twisting second-order sliding mode control system for handling the chattering and overestimating the controller gains. The stability of the proposed controller is verified by the Lyapunov stability theory. Simulation and experimental results show that the proposed control method can enable the robot to track the trajectory accurately under complex and uncertain conditions and effectively suppress the chattering phenomenon of the system.Keywords: Robot manipulatortrajectory trackingadaptive fuzzy super-twisting algorithmsecond-order sliding mode control Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe author would like to express his gratitude for the support of the University Scientific Research Project of Education Bureau of Guangzhou Municipality under Grant 202032821 and the Guangzhou City School Joint Project under Grant SL2023A03J00681.Notes on contributorsDachang ZhuDachang Zhu received the B.S. degree in mechanics design and the M.S. degree in theoretical mechanics from the Jiangxi University of Technology and Science, Ganzhou, China, in 1996 and 1999, respectively, the Ph.D. degree in mechanical engineering from Beijing Jiaotong University, Beijing, China, in 2008, and the Postdoctor in mechanical engineering from the South China University of Technology, Guangzhou, China, in 2012. He currently works as full professor with the School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China. His research interests include topology optimization theory and applications in compliant mechanisms, robotics, and feedback control of the dynamic systems.Puchen ZhuPuchen Zhu received his Bachelor's degree in Engineering from Guangdong University of Technology, Guangzhou, China. he is currently a Master of Philosophy student at the Mechanical and Automation Engineering department at the Chinese University of HongKong (CUHK). his research interests include Robotics, Medical Robotics, and Robotic Modeling and Control.Yonglong HeYonglong He is a student pursuing a master's degress in Mechanical Engineering from the School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, China. his research interests include Robotics, Compliant mechanism.","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136376456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual variational generative model and auxiliary retrieval for empathetic response generation by conversational robot","authors":"Yahui Fu, Koji Inoue, Divesh Lala, Kenta Yamamoto, Chenhui Chu, Tatsuya Kawahara","doi":"10.1080/01691864.2023.2270577","DOIUrl":"https://doi.org/10.1080/01691864.2023.2270577","url":null,"abstract":"Empathy in human-robot conversations aims to endow the robot with the ability to comprehend user emotion and experience, and then respond to it appropriately. Generally, empathy is embodied in the aspects of both contextual understanding and affective expression, which occur when there exist content and emotion consistencies between context and response. However, previous studies only focus on either aspect. In this paper, we propose a dual variational generative model (DVG) for empathetic response generation to achieve both. Specifically, we integrate an emotion classifier and a variational autoencoder (VAE) into a dual response and context generative model to learn the emotion and content consistencies efficiently. DVG utilizes VAE to mimic the process of context/response understanding. In addition to the generative model, our model can effectively switch to another retrieval system as a fallback solution. Automatic and human evaluations on Japanese and English EmpatheticDialogue datasets demonstrate the effectiveness of our method for empathetic response generation. Furthermore, we evaluate our model's ability in general response generation, which is not specific to empathetic but also chitchatting dialogue system. GRAPHICAL ABSTRACT","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135618418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A kinematic model generates non-circular human proxemics zones","authors":"Fanta Camara, Charles Fox","doi":"10.1080/01691864.2023.2263062","DOIUrl":"https://doi.org/10.1080/01691864.2023.2263062","url":null,"abstract":"Hall’s theory of proxemics established distinct spatial zones around humans where they experience comfort or discomfort when interacting with others. Our previous work proposed a new model of proxemics and trust and it showed how to generate proxemics zone sizes using simple equations from human kinematic behaviour. But like most work, this assumed that the zones are circular. In this paper, we refine this model to take the initial heading of the agent into account and find that this results in a non-circular outer boundary of the social zone. These new analytical results from a generative model form a step towards more advanced quantitative proxemics in dual agents’ interaction modelling.","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134944301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can smoothed particle hydrodynamics simulate physically realistic movements of underwater vehicles?","authors":"Nicolas Gartner, Niels Montanari, Mathieu Richier, Vincent Hugel, Ramprasad Sampath","doi":"10.1080/01691864.2023.2263046","DOIUrl":"https://doi.org/10.1080/01691864.2023.2263046","url":null,"abstract":"AbstractThis work presents the first results using Smoothed Particle Hydrodynamics (SPH), a mesh-free technique, to simulate underwater vehicle motion with the goal of achieving sufficient physical realism and computation time performance capabilities. The objective is not to get very accurate values for the hydrodynamic parameters, but to show that SPH can simulate hydrodynamic parameters with the same order of magnitude as the reference, in order to allow a realistic control of robots in water. First, spherical objects are simulated to check buoyancy realism, speed limit existence, and hydrodynamic parameters in comparison with reference values. Then, horizontal and vertical movements of a capsule-shape object and a real torpedo-shape underwater robot are compared. The results show that buoyancy is respected, and that spherical objects reach a speed limit in accordance with the laws of physics. In addition, added-mass is simulated with 20 % variation on average with respect to the reference and varies homothetically with respect to the object's size. In contrast, drag forces cannot not be simulated with the same level of realism without reducing the particle size, which makes the simulation last longer. SPH for underwater robotics simulation appears to be promising, and ways of further improvements are being considered.Keywords: Fluid-solid interactionunderwater roboticssmoothed particle hydrodynamicshydrodynamic parameterscomputational fluid dynamics AcknowledgmentsThis work is a result of the collaboration of Centroid LAB Inc. (Los Angeles, USA), which develops the Neutrino software, and the Laboratoire COSMER (Toulon, France).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was partly supported by the Direction Générale de l'Armement, DGA RAPID grant in partnership with SUBSEA-TECH (Marseille, France) and ROBOPEC (Six-Fours-les-Plages, France).Notes on contributorsNicolas GartnerNicolas Gartner received his Master's degree in Engineering from SIGMA Clermont in 2016, formerly Institut Français de Mécanique Avancée, and his PhD degree from the University of Toulon in 2020. This research was conducted during his postdoc at the University of Toulon. He currently serves the Centre Technologique Méditerranéen de Métrologie. His research work is focused on underwater robotics and the evaluation of hydrodynamics performance using fluid simulation techniques like SPH.Niels MontanariNiels Montanari holds Master's degrees in computer science, applied mathematics and environmental physics, from the Bordeaux Institute of Technology, Grenoble-Alpes University and Paris-Saclay University, respectively. Since 2015, he has worked for Centroid LAB as a simulation & software engineer, performing research and development work on mesh-free particle-based methods for simulating fluid flows in various industry applications.Mathieu RichierMathieu Richier graduated from the Ecole Nationale Sup","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135352319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the performance of robotic assembly systems considering the usage of tools or jigs for the task-board task in the WRS 2018","authors":"Hiroki Dobashi, Koki Ogawa, Mizuho Shibata, Wataru Uemura, Yasuyoshi Yokokohji","doi":"10.1080/01691864.2023.2263064","DOIUrl":"https://doi.org/10.1080/01691864.2023.2263064","url":null,"abstract":"AbstractA task-board task is a task in which robots perform a set of fundamental assembly operations related to the assembly of a specific product such as inserting a part into another part, tightening bolts and nuts, attaching flexible parts, etc. In the task-board task competition in the industrial robotics category of the World Robot Summit (WRS) 2018, 15 teams from around the world performed the task. In our previous work, we observed recorded videos of the competition frame by frame and manually investigated the performance of robotic systems of the top four teams, focusing only on whether robots contact target parts. In this paper, we introduce frame sets to represent mainly contact states between robots, tools, or jigs and target parts to be handled for such a frame-by-frame analysis of the recorded videos, and based on the frame sets, we analyze the performance of robotic assembly systems of other teams as well as the top four teams in the task-board task competition in the WRS 2018, considering the usage of tools or jigs.Keywords: Task-board taskrobotic assembly systemWorld Robot Summit AcknowledgementsThe authors would like to express their gratitude to everyone involved in the design and operation of the Assembly Challenge in the Industrial Robotics Category, the WRS 2018, especially those who greatly contributed to the competition as referees and health and safety inspectors.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Note that strictly speaking, analysis with films is called ‘film analysis’.2 The video is not open to the public unlike those available on the official YouTube channel of the WRS [Citation28].3 In the task-board task competition, not the tightening torque but only the amount of rotation of each of these parts was evaluated. In that case, the tightening of parts 7-1, 7-2, 8, 12, and 13 can be achieved even by human hand itself (without using the tools) whereas part 11 is hard to handle due to its small size.4 No clear picture of the electric screwdriver can be extracted from either the video recorded by the competition committee or [Citation28], but a clear one is given in [Citation29].5 In [Citation22], a cylindrical part with a diameter which is equal to or greater than its length is treated as a non-cylindrical part.Additional informationFundingThis work is based on results obtained from a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO)[P17004] and was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number JP21K03978.Notes on contributorsHiroki DobashiHiroki Dobashi received the BS, MS, and PhD degrees in mechanical engineering from Kyoto University in 2007, 2009, and 2012, respectively. From 2012 to 2013, he was a contract assistant at School of Science and Technology, Kwansei Gakuin University. From 2013 to 2017, he was an assistant professor in the Department of Robotics, Faculty of Science an","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134973946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of attentive listening robot on pleasure and arousal change in psychiatric daycare","authors":"Keiko Ochi, Koji Inoue, Divesh Lala, Tatsuya Kawahara, Hirokazu Kumazaki","doi":"10.1080/01691864.2023.2257264","DOIUrl":"https://doi.org/10.1080/01691864.2023.2257264","url":null,"abstract":"AbstractIn this paper, we investigate the usefulness of an attentive-listening robot in psychiatric daycare, an outpatient treatment program for the rehabilitation of psychiatric disorders. The robot was developed based on counseling techniques, such as repeating words that the user has said. It can also generate backchannels as a listening behavior during user utterance. Conversation experiments have been conducted to evaluate whether the robot can provide effective activities in this setting. The robot attentively listened to 18 daycare attendees talking about their recent memorable events for up to 3 min. The results showed that the conversation increased self-rated arousal. The impressions of the robot showed that talking with the robot was more conversable than with strangers and more useful as a talking partner than a friend. The subjects also had a positive impression about whether they would keep the robot in their homes. A linear regression analysis indicates that the frequency of the robot's assessment responses and backchannels positively affect pleasure improvement. The findings may pave the way for utilizing this kind of robots that people can talk to easily without hesitation or excessive consideration.Keywords: Communicative robotattentive listeningmental healthpsychiatric daycarespeech analysis AcknowledgmentsWe thank Dr. Yosuke Maeda and Ms. Sawa Maeda for their supervision of the experiments. We also thank Ms. Yumi Onishi, Ms. Reina Ōki and Mr. Hiroshi Notsu for the support to their experiments and insightful discussions based on their knowledge and experience in psychiatric daycare.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis study was supported by JSPS KAKENHI (19H05691) and JST Moonshot R&D Grant Number JPMJMS2011.Notes on contributorsKeiko OchiKeiko Ochi received PhD in Graduate School of Information Science and Technology, University of Tokyo, Japan. Currently, her research interests include assistive technology and speech signal processing.Koji InoueKoji Inoue received his MS and PhD degrees in informatics in 2015 and 2018 from Kyoto University, Japan. He is currently an assistant professor at Graduate School of Informatics, Kyoto University, and was a research fellow of the Japan Society for the Promotion of Science (JSPS) from 2015 to 2018. His research interests include spoken dialogue systems, speech signal processing, multimodal interaction, and conversational robots. He is a member of IEEE and ACM.Divesh LalaDivesh Lala received PhD in Graduate School of Informatics in 2015, from Kyoto University, Kyoto, Japan. Currently, he is a researcher in Graduate School of Informatics, Kyoto University. His research interests include human–robot interaction and multimodal signal processing.Tatsuya KawaharaTatsuya Kawahara received BE in 1987, ME in 1989, and PhD in 1995, all in information science, from Kyoto University, Kyoto, Japan. From 1995 to 1996, he","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135591936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}