Pub Date : 2024-10-16DOI: 10.1126/scirobotics.adm7965
Hannes Gamper,Andreas Mueller,Mario Di Castro
A holistic robotic concept for inspection, maintenance, and emergency interventions for the Future Circular Collider is presented.
介绍了用于未来环形对撞机的检查、维护和紧急干预的整体机器人概念。
{"title":"High-tech guardians: Robotics at the heart of the Future Circular Collider.","authors":"Hannes Gamper,Andreas Mueller,Mario Di Castro","doi":"10.1126/scirobotics.adm7965","DOIUrl":"https://doi.org/10.1126/scirobotics.adm7965","url":null,"abstract":"A holistic robotic concept for inspection, maintenance, and emergency interventions for the Future Circular Collider is presented.","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"98 1","pages":"eadm7965"},"PeriodicalIF":25.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1126/scirobotics.adn6848
Jiří Ulrich, Martin Stefanec, Fatemeh Rekabi-Bana, Laurenz Alexander Fedotoff, Tomáš Rouček, Bilal Yağız Gündeğer, Mahmood Saadat, Jan Blaha, Jiří Janota, Daniel Nicolas Hofstadler, Kristina Žampachů, Erhan Ege Keyvan, Babür Erdem, Erol Şahin, Hande Alemdar, Ali Emre Turgut, Farshad Arvin, Thomas Schmickl, Tomáš Krajník
Digital and mechatronic methods, paired with artificial intelligence and machine learning, are transformative technologies in behavioral science and biology. The central element of the most important pollinator species—honey bees—is the colony’s queen. Because honey bee self-regulation is complex and studying queens in their natural colony context is difficult, the behavioral strategies of these organisms have not been widely studied. We created an autonomous robotic observation and behavioral analysis system aimed at continuous observation of the queen and her interactions with worker bees and comb cells, generating behavioral datasets of exceptional length and quality. Key behavioral metrics of the queen and her social embedding within the colony were gathered using our robotic system. Data were collected continuously for 24 hours a day over a period of 30 days, demonstrating our system’s capability to extract key behavioral metrics at microscopic, mesoscopic, and macroscopic system levels. Additionally, interactions among the queen, worker bees, and brood were observed and quantified. Long-term continuous observations performed by the robot yielded large amounts of high-definition video data that are beyond the observation capabilities of humans or stationary cameras. Our robotic system can enable a deeper understanding of the innermost mechanisms of honey bees’ swarm-intelligent self-regulation. Moreover, it offers the possibility to study other social insect colonies, biocoenoses, and ecosystems in an automated manner. Social insects are keystone species in all terrestrial ecosystems; thus, developing a better understanding of their behaviors will be invaluable for the protection and even the restoration of our fragile ecosystems globally.
{"title":"Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots","authors":"Jiří Ulrich, Martin Stefanec, Fatemeh Rekabi-Bana, Laurenz Alexander Fedotoff, Tomáš Rouček, Bilal Yağız Gündeğer, Mahmood Saadat, Jan Blaha, Jiří Janota, Daniel Nicolas Hofstadler, Kristina Žampachů, Erhan Ege Keyvan, Babür Erdem, Erol Şahin, Hande Alemdar, Ali Emre Turgut, Farshad Arvin, Thomas Schmickl, Tomáš Krajník","doi":"10.1126/scirobotics.adn6848","DOIUrl":"https://doi.org/10.1126/scirobotics.adn6848","url":null,"abstract":"Digital and mechatronic methods, paired with artificial intelligence and machine learning, are transformative technologies in behavioral science and biology. The central element of the most important pollinator species—honey bees—is the colony’s queen. Because honey bee self-regulation is complex and studying queens in their natural colony context is difficult, the behavioral strategies of these organisms have not been widely studied. We created an autonomous robotic observation and behavioral analysis system aimed at continuous observation of the queen and her interactions with worker bees and comb cells, generating behavioral datasets of exceptional length and quality. Key behavioral metrics of the queen and her social embedding within the colony were gathered using our robotic system. Data were collected continuously for 24 hours a day over a period of 30 days, demonstrating our system’s capability to extract key behavioral metrics at microscopic, mesoscopic, and macroscopic system levels. Additionally, interactions among the queen, worker bees, and brood were observed and quantified. Long-term continuous observations performed by the robot yielded large amounts of high-definition video data that are beyond the observation capabilities of humans or stationary cameras. Our robotic system can enable a deeper understanding of the innermost mechanisms of honey bees’ swarm-intelligent self-regulation. Moreover, it offers the possibility to study other social insect colonies, biocoenoses, and ecosystems in an automated manner. Social insects are keystone species in all terrestrial ecosystems; thus, developing a better understanding of their behaviors will be invaluable for the protection and even the restoration of our fragile ecosystems globally.","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"24 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1126/scirobotics.adm7689
T. Thang Vo-Doan, Victor V. Titov, Michael J. M. Harrap, Stephan Lochner, Andrew D. Straw
Insects have important roles globally in ecology, economy, and health, yet our understanding of their behavior remains limited. Bees, for example, use vision and a tiny brain to find flowers and return home, but understanding how they perform these impressive tasks has been hampered by limitations in recording technology. Here, we present Fast Lock-On (FLO) tracking. This method moves an image sensor to remain focused on a retroreflective marker affixed to an insect. Using paraxial infrared illumination, simple image processing can localize the sensor location of the insect in a few milliseconds. When coupled with a feedback system to steer a high-magnification optical system to remain focused on the insect, a high–spatiotemporal resolution trajectory can be gathered over a large region. As the basis for several robotic systems, we show that FLO is a versatile idea that can be used in combination with other components. We demonstrate that the optical path can be split and used for recording high-speed video. Furthermore, by flying an FLO system on a quadcopter drone, we track a flying honey bee and anticipate tracking insects in the wild over kilometer scales. Such systems have the capability to provide higher-resolution information about insects behaving in natural environments and as such will be helpful in revealing the biomechanical and neuroethological mechanisms used by insects in natural settings.
{"title":"High-resolution outdoor videography of insects using Fast Lock-On tracking","authors":"T. Thang Vo-Doan, Victor V. Titov, Michael J. M. Harrap, Stephan Lochner, Andrew D. Straw","doi":"10.1126/scirobotics.adm7689","DOIUrl":"https://doi.org/10.1126/scirobotics.adm7689","url":null,"abstract":"Insects have important roles globally in ecology, economy, and health, yet our understanding of their behavior remains limited. Bees, for example, use vision and a tiny brain to find flowers and return home, but understanding how they perform these impressive tasks has been hampered by limitations in recording technology. Here, we present Fast Lock-On (FLO) tracking. This method moves an image sensor to remain focused on a retroreflective marker affixed to an insect. Using paraxial infrared illumination, simple image processing can localize the sensor location of the insect in a few milliseconds. When coupled with a feedback system to steer a high-magnification optical system to remain focused on the insect, a high–spatiotemporal resolution trajectory can be gathered over a large region. As the basis for several robotic systems, we show that FLO is a versatile idea that can be used in combination with other components. We demonstrate that the optical path can be split and used for recording high-speed video. Furthermore, by flying an FLO system on a quadcopter drone, we track a flying honey bee and anticipate tracking insects in the wild over kilometer scales. Such systems have the capability to provide higher-resolution information about insects behaving in natural environments and as such will be helpful in revealing the biomechanical and neuroethological mechanisms used by insects in natural settings.","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"4 1","pages":""},"PeriodicalIF":25.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-25DOI: 10.1126/scirobotics.adr9299
Maheera Bawa, Ritu Raman
Innovations in control mechanisms for muscle-powered robots are advancing the sophistication of biohybrid machines.
肌肉驱动机器人控制机制的创新正在推动生物混合机器的发展。
{"title":"Taking control: Steering the future of biohybrid robots","authors":"Maheera Bawa, Ritu Raman","doi":"10.1126/scirobotics.adr9299","DOIUrl":"10.1126/scirobotics.adr9299","url":null,"abstract":"<div >Innovations in control mechanisms for muscle-powered robots are advancing the sophistication of biohybrid machines.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 94","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-25DOI: 10.1126/scirobotics.ads4127
Nicole W. Xu
A butterfly-like robot swims using an electronic device to stimulate human-derived motor neurons and cardiac muscle cells.
一个类似蝴蝶的机器人利用电子设备刺激源自人类的运动神经元和心肌细胞游泳。
{"title":"Float like a butterfly, swim like a biohybrid neuromuscular robot","authors":"Nicole W. Xu","doi":"10.1126/scirobotics.ads4127","DOIUrl":"10.1126/scirobotics.ads4127","url":null,"abstract":"<div >A butterfly-like robot swims using an electronic device to stimulate human-derived motor neurons and cardiac muscle cells.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 94","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Machine learning, robots, and abuse of power","authors":"Robin R. Murphy","doi":"10.1126/scirobotics.ads6559","DOIUrl":"10.1126/scirobotics.ads6559","url":null,"abstract":"<div >The novel <i>Annie Bot</i> by Sierra Greer is a machine learning take on the domestic noir genre.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 94","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-25DOI: 10.1126/scirobotics.ado0051
Hiroyuki Tetsuka, Samuele Gobbi, Takaaki Hatanaka, Lorenzo Pirrami, Su Ryon Shin
Biological motions of native muscle tissues rely on the nervous system to interface movement with the surrounding environment. The neural innervation of muscles, crucial for regulating movement, is the fundamental infrastructure for swiftly responding to changes in body tissue requirements. This study introduces a bioelectronic neuromuscular robot integrated with the motor nervous system through electrical synapses to evoke cardiac muscle activities and steer robotic motion. Serving as an artificial brain and wirelessly regulating selective neural activation to initiate robot fin motion, a wireless frequency multiplexing bioelectronic device is used to control the robot. Frequency multiplexing bioelectronics enables the control of the robot locomotion speed and direction by modulating the flapping of the robot fins through the wireless motor innervation of cardiac muscles. The robots demonstrated an average locomotion speed of ~0.52 ± 0.22 millimeters per second, fin-flapping frequency up to 2.0 hertz, and turning locomotion path curvature of ~0.11 ± 0.04 radians per millimeter. These systems will contribute to the expansion of biohybrid machines into the brain-to-motor frontier for developing autonomous biohybrid systems capable of advanced adaptive motor control and learning.
{"title":"Wirelessly steerable bioelectronic neuromuscular robots adapting neurocardiac junctions","authors":"Hiroyuki Tetsuka, Samuele Gobbi, Takaaki Hatanaka, Lorenzo Pirrami, Su Ryon Shin","doi":"10.1126/scirobotics.ado0051","DOIUrl":"10.1126/scirobotics.ado0051","url":null,"abstract":"<div >Biological motions of native muscle tissues rely on the nervous system to interface movement with the surrounding environment. The neural innervation of muscles, crucial for regulating movement, is the fundamental infrastructure for swiftly responding to changes in body tissue requirements. This study introduces a bioelectronic neuromuscular robot integrated with the motor nervous system through electrical synapses to evoke cardiac muscle activities and steer robotic motion. Serving as an artificial brain and wirelessly regulating selective neural activation to initiate robot fin motion, a wireless frequency multiplexing bioelectronic device is used to control the robot. Frequency multiplexing bioelectronics enables the control of the robot locomotion speed and direction by modulating the flapping of the robot fins through the wireless motor innervation of cardiac muscles. The robots demonstrated an average locomotion speed of ~0.52 ± 0.22 millimeters per second, fin-flapping frequency up to 2.0 hertz, and turning locomotion path curvature of ~0.11 ± 0.04 radians per millimeter. These systems will contribute to the expansion of biohybrid machines into the brain-to-motor frontier for developing autonomous biohybrid systems capable of advanced adaptive motor control and learning.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 94","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.science.org/doi/reader/10.1126/scirobotics.ado0051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-25DOI: 10.1126/scirobotics.ado4553
James Davies, Mai Thanh Thai, Bibhu Sharma, Trung Thien Hoang, Chi Cong Nguyen, Phuoc Thien Phan, Thao Nhu Anne Marie Vuong, Adrienne Ji, Kefan Zhu, Emanuele Nicotra, Yi-Chin Toh, Michael Stevens, Christopher Hayward, Hoang-Phuong Phan, Nigel Hamilton Lovell, Thanh Nho Do
The heart’s intricate myocardial architecture has been called the Gordian knot of anatomy, an impossible tangle of intricate muscle fibers. This complexity dictates equally complex cardiac motions that are difficult to mimic in physical systems. If these motions could be generated by a robotic system, then cardiac device testing, cardiovascular disease studies, and surgical procedure training could reduce their reliance on animal models, saving time, costs, and lives. This work introduces a bioinspired soft robotic left ventricle simulator capable of reproducing the minutiae of cardiac motion while providing physiological pressures. This device uses thin-filament artificial muscles to mimic the multilayered myocardial architecture. To demonstrate the device’s ability to follow the cardiac motions observed in the literature, we used canine myocardial strain data as input signals that were subsequently applied to each artificial myocardial layer. The device’s ability to reproduce physiological volume and pressure under healthy and heart failure conditions, as well as effective simulation of a cardiac support device, were experimentally demonstrated in a left-sided mock circulation loop. This work also has the potential to deliver faithful simulated cardiac motion for preclinical device and surgical procedure testing, with the potential to simulate patient-specific myocardial architecture and motion.
{"title":"Soft robotic artificial left ventricle simulator capable of reproducing myocardial biomechanics","authors":"James Davies, Mai Thanh Thai, Bibhu Sharma, Trung Thien Hoang, Chi Cong Nguyen, Phuoc Thien Phan, Thao Nhu Anne Marie Vuong, Adrienne Ji, Kefan Zhu, Emanuele Nicotra, Yi-Chin Toh, Michael Stevens, Christopher Hayward, Hoang-Phuong Phan, Nigel Hamilton Lovell, Thanh Nho Do","doi":"10.1126/scirobotics.ado4553","DOIUrl":"10.1126/scirobotics.ado4553","url":null,"abstract":"<div >The heart’s intricate myocardial architecture has been called the Gordian knot of anatomy, an impossible tangle of intricate muscle fibers. This complexity dictates equally complex cardiac motions that are difficult to mimic in physical systems. If these motions could be generated by a robotic system, then cardiac device testing, cardiovascular disease studies, and surgical procedure training could reduce their reliance on animal models, saving time, costs, and lives. This work introduces a bioinspired soft robotic left ventricle simulator capable of reproducing the minutiae of cardiac motion while providing physiological pressures. This device uses thin-filament artificial muscles to mimic the multilayered myocardial architecture. To demonstrate the device’s ability to follow the cardiac motions observed in the literature, we used canine myocardial strain data as input signals that were subsequently applied to each artificial myocardial layer. The device’s ability to reproduce physiological volume and pressure under healthy and heart failure conditions, as well as effective simulation of a cardiac support device, were experimentally demonstrated in a left-sided mock circulation loop. This work also has the potential to deliver faithful simulated cardiac motion for preclinical device and surgical procedure testing, with the potential to simulate patient-specific myocardial architecture and motion.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 94","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.1126/scirobotics.adr8282
Nikhil V. Divekar, Gray C. Thomas, Avani R. Yerva, Hannah B. Frame, Robert D. Gregg
The quadriceps are particularly susceptible to fatigue during repetitive lifting, lowering, and carrying (LLC), affecting worker performance, posture, and ultimately lower-back injury risk. Although robotic exoskeletons have been developed and optimized for specific use cases like lifting-lowering, their controllers lack the versatility or customizability to target critical muscles across many fatiguing tasks. Here, we present a task-adaptive knee exoskeleton controller that automatically modulates virtual springs, dampers, and gravity and inertia compensation to assist squatting, level walking, and ramp and stairs ascent/descent. Unlike end-to-end neural networks, the controller is composed of predictable, bounded components with interpretable parameters that are amenable to data-driven optimization for biomimetic assistance and subsequent application-specific tuning, for example, maximizing quadriceps assistance over multiterrain LLC. When deployed on a backdrivable knee exoskeleton, the assistance torques holistically reduced quadriceps effort across multiterrain LLC tasks (significantly except for level walking) in 10 human users without user-specific calibration. The exoskeleton also significantly improved fatigue-induced deficits in time-based performance and posture during repetitive lifting-lowering. Last, the system facilitated seamless task transitions and garnered a high effectiveness rating postfatigue over a multiterrain circuit. These findings indicate that this versatile control framework can target critical muscles across multiple tasks, specifically mitigating quadriceps fatigue and its deleterious effects.
{"title":"A versatile knee exoskeleton mitigates quadriceps fatigue in lifting, lowering, and carrying tasks","authors":"Nikhil V. Divekar, Gray C. Thomas, Avani R. Yerva, Hannah B. Frame, Robert D. Gregg","doi":"10.1126/scirobotics.adr8282","DOIUrl":"10.1126/scirobotics.adr8282","url":null,"abstract":"<div >The quadriceps are particularly susceptible to fatigue during repetitive lifting, lowering, and carrying (LLC), affecting worker performance, posture, and ultimately lower-back injury risk. Although robotic exoskeletons have been developed and optimized for specific use cases like lifting-lowering, their controllers lack the versatility or customizability to target critical muscles across many fatiguing tasks. Here, we present a task-adaptive knee exoskeleton controller that automatically modulates virtual springs, dampers, and gravity and inertia compensation to assist squatting, level walking, and ramp and stairs ascent/descent. Unlike end-to-end neural networks, the controller is composed of predictable, bounded components with interpretable parameters that are amenable to data-driven optimization for biomimetic assistance and subsequent application-specific tuning, for example, maximizing quadriceps assistance over multiterrain LLC. When deployed on a backdrivable knee exoskeleton, the assistance torques holistically reduced quadriceps effort across multiterrain LLC tasks (significantly except for level walking) in 10 human users without user-specific calibration. The exoskeleton also significantly improved fatigue-induced deficits in time-based performance and posture during repetitive lifting-lowering. Last, the system facilitated seamless task transitions and garnered a high effectiveness rating postfatigue over a multiterrain circuit. These findings indicate that this versatile control framework can target critical muscles across multiple tasks, specifically mitigating quadriceps fatigue and its deleterious effects.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 94","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-18DOI: 10.1126/scirobotics.adl3546
Zachary Yoder, Ellen H. Rumley, Ingemar Schmidt, Philipp Rothemund, Christoph Keplinger
Robots made from reconfigurable modular units feature versatility, cost efficiency, and improved sustainability compared with fixed designs. Reconfigurable modules driven by soft actuators provide adaptable actuation, safe interaction, and wide design freedom, but existing soft modules would benefit from high-speed and high-strain actuation, as well as driving methods well-suited to untethered operation. Here, we introduce a class of electrically actuated robotic modules that provide high-speed (a peak contractile strain rate of 4618% per second, 15.8-hertz bandwidth, and a peak specific power of 122 watts per kilogram), high-strain (49% contraction) actuation and that use magnets for reversible mechanical and electrical connections between neighboring modules, thereby serving as building blocks for rapidly reconfigurable and highly agile robotic systems. The actuation performance of each hexagonal electrohydraulic (HEXEL) module is enabled by a synergistic combination of soft and rigid components; a hexagonal exoskeleton of rigid plates amplifies the motion produced by soft electrohydraulic actuators and provides a mechanical structure and connection platform for reconfigurable robots composed of many modules. We characterize the actuation performance of individual HEXEL modules, present a model that captures their quasi-static force-stroke behavior, and demonstrate both a high-jumping and a fast pipe-crawling robot. Using embedded magnetic connections, we arranged multiple modules into reconfigurable robots with diverse functionality, including a high-stroke muscle, a multimodal active array, a table-top active platform, and a fast-rolling robot. We further leveraged the magnetic connections for hosting untethered, snap-on driving electronics, together highlighting the promise of HEXEL modules for creating rapidly reconfigurable high-speed robots.
{"title":"Hexagonal electrohydraulic modules for rapidly reconfigurable high-speed robots","authors":"Zachary Yoder, Ellen H. Rumley, Ingemar Schmidt, Philipp Rothemund, Christoph Keplinger","doi":"10.1126/scirobotics.adl3546","DOIUrl":"10.1126/scirobotics.adl3546","url":null,"abstract":"<div >Robots made from reconfigurable modular units feature versatility, cost efficiency, and improved sustainability compared with fixed designs. Reconfigurable modules driven by soft actuators provide adaptable actuation, safe interaction, and wide design freedom, but existing soft modules would benefit from high-speed and high-strain actuation, as well as driving methods well-suited to untethered operation. Here, we introduce a class of electrically actuated robotic modules that provide high-speed (a peak contractile strain rate of 4618% per second, 15.8-hertz bandwidth, and a peak specific power of 122 watts per kilogram), high-strain (49% contraction) actuation and that use magnets for reversible mechanical and electrical connections between neighboring modules, thereby serving as building blocks for rapidly reconfigurable and highly agile robotic systems. The actuation performance of each hexagonal electrohydraulic (HEXEL) module is enabled by a synergistic combination of soft and rigid components; a hexagonal exoskeleton of rigid plates amplifies the motion produced by soft electrohydraulic actuators and provides a mechanical structure and connection platform for reconfigurable robots composed of many modules. We characterize the actuation performance of individual HEXEL modules, present a model that captures their quasi-static force-stroke behavior, and demonstrate both a high-jumping and a fast pipe-crawling robot. Using embedded magnetic connections, we arranged multiple modules into reconfigurable robots with diverse functionality, including a high-stroke muscle, a multimodal active array, a table-top active platform, and a fast-rolling robot. We further leveraged the magnetic connections for hosting untethered, snap-on driving electronics, together highlighting the promise of HEXEL modules for creating rapidly reconfigurable high-speed robots.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"9 94","pages":""},"PeriodicalIF":26.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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