{"title":"Stochastic approach for modeling soft fingers with creep behavior","authors":"Sumitaka Honji, Hikaru Arita, Kenji Tahara","doi":"10.1080/01691864.2023.2279600","DOIUrl":null,"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 2020, he has served as a Full Professor in the same department. His current research interests include mechanics, design, and control of multi-fingered robotic hands, soft robotics including polymeric artificial muscle actuators, force control, bipedal robots, and analysis and realization of human body movements.","PeriodicalId":7261,"journal":{"name":"Advanced Robotics","volume":"30 14","pages":"0"},"PeriodicalIF":1.4000,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/01691864.2023.2279600","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
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 2020, he has served as a Full Professor in the same department. His current research interests include mechanics, design, and control of multi-fingered robotic hands, soft robotics including polymeric artificial muscle actuators, force control, bipedal robots, and analysis and realization of human body movements.
期刊介绍:
Advanced Robotics (AR) is the international journal of the Robotics Society of Japan and has a history of more than twenty years. It is an interdisciplinary journal which integrates publication of all aspects of research on robotics science and technology. Advanced Robotics publishes original research papers and survey papers from all over the world. Issues contain papers on analysis, theory, design, development, implementation and use of robots and robot technology. The journal covers both fundamental robotics and robotics related to applied fields such as service robotics, field robotics, medical robotics, rescue robotics, space robotics, underwater robotics, agriculture robotics, industrial robotics, and robots in emerging fields. It also covers aspects of social and managerial analysis and policy regarding robots.
Advanced Robotics (AR) is an international, ranked, peer-reviewed journal which publishes original research contributions to scientific knowledge.
All manuscript submissions are subject to initial appraisal by the Editor, and, if found suitable for further consideration, to peer review by independent, anonymous expert referees.