Stochastic approach for modeling soft fingers with creep behavior

IF 1.4 4区 计算机科学 Q4 ROBOTICS
Sumitaka Honji, Hikaru Arita, Kenji Tahara
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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.
具有蠕变行为的软手指随机建模方法
摘要软体机器人因其柔软性而具有较高的适应性和安全性,因此在人类社会中得到了广泛的应用。然而,考虑到软机器人作为人类的替代劳动力,其灵巧行为的可控性是不够的。基于模型的控制方法是实现灵巧行为的有效方法。为了建立一个合适的控制模型,必须解决基于特定属性的问题,例如蠕变行为和可变运动。本文建立了具有粘弹性关节的软手指的集总参数化模型。参数以分布形式表示,这使得模型能够考虑到运动的可变性。在此基础上,对参数分布进行了随机分析。模型结果与实验结果一致,该模型能够研究与机器人可变性相关的各种参数的影响。关键词:集总参数化模型分布粘弹性参数随机变量变换敏感性分析致谢感谢资金来源。此外,我们要感谢人权专员办事处实验室成员进行了有益的讨论。披露声明作者未报告潜在的利益冲突。本研究由日本科学促进会(JSPS)科学研究资助基金(A) No. 20H00610资助。sumitaka Honji于2019年和2021年分别获得日本九州大学工程学院机械工程系学士和硕士学位。他现在是九州大学的博士生。他的兴趣包括软机器人系统的建模和控制。Hikaru Arita,分别于2012年、2014年和2019年在日本电子通信大学(University of Electro-Communications)获得工学学士、硕士和博士学位。他曾在多家机构任职,包括2014年至2016年在日本京都的欧姆龙公司(OMRON Corporation)工作,以及2019年至2022年在立命馆大学(Ritsumeikan University)担任助理教授。他目前是日本九州大学工程学院机械工程系助理教授。他目前的研究兴趣包括接近传感器,基于传感器的控制,肌肉骨骼机器人,机械手,操作和软机器人。田原健二获得机械学士学位。Eng。1998年获得信息学硕士学位。科学。和系统。2000年获得机器人博士学位,2003年获得机器人博士学位,均毕业于日本立命馆大学。2003年至2007年,他加入RIKEN仿生控制研究中心,担任研究科学家。2007年加入九州大学任终身副教授,2011年任日本九州大学工学院机械工程系副教授。自2020年起任该系正教授。他目前的研究方向包括多指机械手的力学、设计和控制、软机器人技术(包括聚合人工肌肉驱动器)、力控制、两足机器人、人体运动分析和实现。
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来源期刊
Advanced Robotics
Advanced Robotics 工程技术-机器人学
CiteScore
4.10
自引率
20.00%
发文量
102
审稿时长
5.3 months
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.
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