BEGIN:VCALENDAR VERSION:2.0 PRODID:-//128.220.36.25//NONSGML kigkonsult.se iCalcreator 2.26.9// CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Laboratory for Computational Sensing + Robotics X-WR-CALDESC: X-FROM-URL:https://lcsr.jhu.edu X-WR-TIMEZONE:America/New_York BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:STANDARD DTSTART:20231105T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RDATE:20241103T020000 TZNAME:EST END:STANDARD BEGIN:DAYLIGHT DTSTART:20240310T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RDATE:20250309T020000 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:ai1ec-13536@lcsr.jhu.edu DTSTAMP:20240328T075650Z CATEGORIES: CONTACT:Ashley Moriarty\; amoriar2@jhu.edu DESCRIPTION:Link for Live Seminar\nLink for Recorded seminars – 2022/2023 s chool year\n \nUlas Berk Karli and Shiye (Sally) Cao “What if it is wrong: effects of power dynamics and trust repair strategy on trust and complian ce in HRI.”\nAbstract: Robotic systems designed to work alongside people a re susceptible to technical and unexpected errors. Prior work has investig ated a variety of strategies aimed at repairing people’s trust in the robo t after its erroneous operations. In this work\, we explore the effect of post-error trust repair strategies (promise and explanation) on people’s t rust in the robot under varying power dynamics (supervisor and subordinate robot). Our results show that\, regardless of the power dynamics\, promis e is more effective at repairing user trust than explanation. Moreover\, p eople found a supervisor robot with verbal trust repair to be more trustwo rthy than a subordinate robot with verbal trust repair. Our results furthe r reveal that people are prone to complying with the supervisor robot even if it is wrong. We discuss the ethical concerns in the use of supervisor robot and potential interventions to prevent improper compliance in users for more productive human-robot collaboration.\n \nBio: Ulas Berk Karli is a MSE student in Robotics LCSR\, Johns Hopkins University. He received th e Bachelor of Science degree in Mechanical Engineering and Double Majored in Computer Engineering from Koc University\, Istanbul in 2021. His resear ch interests are Human-Robot Collaboration and Robot Learning for HRI.\nSh iye Cao is a first-year Ph.D. student in the Department of Computer Scienc e\, co-advised by Dr. Chien-Ming Huang and Dr. Anqi Liu. She received the Bachelor of Science degree in Computer Science with a second major in App lied Mathematics and Statistics from Johns Hopkins University in 2021\, an d the Masters of Science in Engineering in Computer Science from Johns Hop kins University in 2022. Her work focuses on user trust and reliance in hu man-machine collaborative tasks.\n \n \nEugene Lin “Robophysical modeling of spider vibration sensing of prey on orb webs”\nAbstract: Orb-weaving sp iders are functionally blind and detect prey-generated web vibrations thro ugh vibration sensors at their leg joints to locate and identify prey caug ht in their (near) planar webs. Previous studies focused on how spiders us e web geometry\, silk properties\, and web pre-tension to modulate vibrati on sensing. Spiders can also dynamically adjust their posture while sensin g prey\, which may be a form of active sensing (Hung\, Corver\, Gordus\, 2 022\, APS March Meeting). However\, whether this is true and how it works is poorly understood\, due to difficulty of measuring the dynamics of the entire prey-web-spider interaction system all at once. Here\, we developed a robophysical model of the system to test this hypothesis of active sens ing and discover its principles. Our model consists of a vibrating prey ro bot and a spider robot that can adjust its posture\, with torsional spring s at leg joints and accelerometers to measure joint vibration. Both robots are attached to a physical web made of cords with qualitatively similar p roperties to real spider web threads. Load cells measure web pre-tension a nd a high-speed camera system measure web vibrations and robot movement. P reliminary results showed vibration attenuation through the web from the p rey robot. We are currently studying the complex effects of spider robot’s dynamic posture change on vibration propagation across the web and leg jo ints\, by systematically varying the parameters of prey robot vibration\, spider robot leg posture\, and web pre-tension.\n \nBio: Eugene Lin is a t hird year PhD student in Dr. Chen Li’s lab (Terradynamics lab). His work f ocuses on understanding environmental sensing on suspended\, sparse terrai n. He received a B.S. in Mechanical Engineering at the University of Calif ornia\, San Diego. He recently presented this work at the annual SICB conf erence and will present it again at the annual March APS conference.\n \n \nAishwarya Pantula “Pick a Side: Untethered Gel Crawlers That Can Break S ymmetry”\nAbstract: The development of untethered soft crawling robots pro grammed to respond to environmental stimuli and precisely maneuverable acr oss size scales has been paramount to the fields of soft robotics\, drug d elivery\, and autonomous smart devices. Of particular relevance are revers ible thermoresponsive hydrogels\, which swell and shrink in the temperatur e range of (30- 60 °C) for operating such untethered soft robots in human physiological and ambient conditions. While crawling has been demonstrated by thermoresponsive hydrogels\, they need surface modifications in the fo rm of rachets\, asymmetric patterning\, or constraints to achieve unidirec tional motion.\nHere we demonstrate and validate a new mechanism for untet hered\, unidirectional crawling for multisegmented gel crawlers built from an active thermoresponsive poly (N-isopropyl acrylamide) (pNIPAM) and pas sive polyacrylamide (pAAM) on flat unpatterned surfaces. By connecting bil ayers of different geometries and thicknesses using a centrally suspended gel linker\, we create a morphological gradient along the fore-aft axis\, which leads to an asymmetry in the contact forces during the swelling and deswelling of our crawler. We thoroughly explain our mechanism using exper iments and finite element simulations and\, using experiments\, demonstrat e that we can tune the generated asymmetry and\, in turn\, increase the di splacement of the crawler by varying linker stiffness\, morphology\, and t he number of bilayer segments. We believe this mechanism can be widely app lied across fields of study to create the next generation of autonomous sh ape-changing and smart locomotors.\nBio: Aishwarya is a 4th year Ph.D. can didate in the lab of Dr. David Gracias at Johns Hopkins University\, USA. Her research focuses on exploring smart materials like stimuli-responsive hydrogels\, combining them with novel patterning methods like 3D/4D printi ng\, imprint molding\, lithography\, etc.\, and using different mechanical design strategies to create untethered biomimetic actuators and locomotor s across size scales for soft robotics and biomedical devices.\n \n \nMaia Stiber “On using social signals to enable flexible error-aware HRI.”\nAbs tract: Prior error management techniques often do not possess the versatil ity to appropriately address robot errors across tasks and scenarios. Thei r fundamental framework involves explicit\, manual error management and im plicit domain-specific information driven error management\, tailoring the ir response for specific interaction contexts. We present a framework for approaching error-aware systems by adding implicit social signals as anoth er information channel to create more flexibility in application. To suppo rt this notion\, we introduce a novel dataset (composed of three data coll ections) with a focus on understanding natural facial action unit (AU) res ponses to robot errors during physical-based human-robot interactions—vary ing across task\, error\, people\, and scenario. Analysis of the dataset r eveals that\, through the lens of error detection\, using AUs as input int o error management affords flexibility to the system and has the potential to improve error detection response rate. In addition\, we provide an exa mple real-time interactive robot error management system using the error-a ware framework.\n \nBio: Maia Stiber is a 4th year Ph.D. candidate in the Department of Computer Science\, co-advised by Dr. Chien-Ming Huang and Dr . Russell Taylor. She received a B.S. in Computer Science from Caltech in 2019 and a M.S.E. in Computer Science from Johns Hopkins University in 202 1. Her work focuses on leveraging natural human responses to robot errors in an effort to develop flexible error management techniques in support of effective human-robot interaction.\n \nVictor Antony “Co-designing with o lder adults\, for older adults: robots to promote physical activity.”\nAbs tract: Lack of physical activity has severe negative health consequences f or older adults and limits their ability to live independently. Robots hav e been proposed to help engage older adults in physical activity (PA)\, al beit with limited success. There is a lack of robust understanding of olde r adults’ needs and wants from robots designed to engage them in PA. In th is paper\, we report on the findings of a co-design process where older ad ults\, physical therapy experts\, and engineers designed robots to promote PA in older adults. We found a variety of motivators for and barriers aga inst PA in older adults\; we\, then\, conceptualized a broad spectrum of p ossible robotic support and found that robots can play various roles to he lp older adults engage in PA. This exploratory study elucidated several ov erarching themes and emphasized the need for personalization and adaptabil ity. This work highlights key design features that researchers and enginee rs should consider when developing robots to engage older adults in PA\, a nd underscores the importance of involving various stakeholders in the des ign and development of assistive robots.\n \nBio: Victor Antony is a secon d-year Ph.D. student in the Department of Computer Science\, advised by Dr . Chien-Ming Huang. He received the Bachelor of Science degree in Computer Science from the University of Rochester in 2021. His work focuses on Soc ial Robots for well-being.\n DTSTART;TZID=America/New_York:20230301T120000 DTEND;TZID=America/New_York:20230301T130000 LOCATION:Hackerman B17 SEQUENCE:0 SUMMARY:LCSR Seminar: Student Seminars URL:https://lcsr.jhu.edu/events/lcsr-seminar-student/ X-COST-TYPE:free X-ALT-DESC;FMTTYPE=text/html:\\n\\n
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Ulas Berk Karli and Shiye (Sally) Cao “What if it is wrong : effects of power dynamics and trust repair strategy on trust and complia nce in HRI.”
\nAbstract: Robotic systems designed to work a longside people are susceptible to technical and unexpected errors. Prior work has investigated a variety of strategies aimed at repairing people’s trust in the robot after its erroneous operations. In this work\, we explo re the effect of post-error trust repair strategies (promise and explanati on) on people’s trust in the robot under varying power dynamics (superviso r and subordinate robot). Our results show that\, regardless of the power dynamics\, promise is more effective at repairing user trust than explanat ion. Moreover\, people found a supervisor robot with verbal trust repair t o be more trustworthy than a subordinate robot with verbal trust repair. O ur results further reveal that people are prone to complying with the supe rvisor robot even if it is wrong. We discuss the ethical concerns in the u se of supervisor robot and potential interventions to prevent improper com pliance in users for more productive human-robot collaboration.
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Bio: Ulas Berk Karli is a MSE student in Robotics LCSR\, Johns Hop kins University. He received the Bachelor of Science degree in Mechanical Engineering and Double Majored in Computer Engineering from Koc University \, Istanbul in 2021. His research interests are Human-Robot Collaboration and Robot Learning for HRI.
\nShiye Cao is a first-year Ph.D. studen t in the Department of Computer Science\, co-advised by Dr. Chien-Ming Hua ng and Dr. Anqi Liu. She received the Bachelor of Science degree in Comput er Science with a second major in Applied Mathematics and Statistics from Johns Hopkins University in 2021\, and the Masters of Science in Engineer ing in Computer Science from Johns Hopkins University in 2022. Her work fo cuses on user trust and reliance in human-machine collaborative tasks.
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Eugene Lin “Robophysical modeling of spider vibration sensing of prey on orb webs ”
\nAbstract: Orb-weaving spiders are functionally blind an d detect prey-generated web vibrations through vibration sensors at their leg joints to locate and identify prey caught in their (near) planar webs. Previous studies focused on how spiders use web geometry\, silk propertie s\, and web pre-tension to modulate vibration sensing. Spiders can also dy namically adjust their posture while sensing prey\, which may be a form of active sensing (Hung\, Corver\, Gordus\, 2022\, APS March Meeting). Howev er\, whether this is true and how it works is poorly understood\, due to d ifficulty of measuring the dynamics of the entire prey-web-spider interact ion system all at once. Here\, we developed a robophysical model of the sy stem to test this hypothesis of active sensing and discover its principles . Our model consists of a vibrating prey robot and a spider robot that can adjust its posture\, with torsional springs at leg joints and acceleromet ers to measure joint vibration. Both robots are attached to a physical web made of cords with qualitatively similar properties to real spider web th reads. Load cells measure web pre-tension and a high-speed camera system m easure web vibrations and robot movement. Preliminary results showed vibra tion attenuation through the web from the prey robot. We are currently stu dying the complex effects of spider robot’s dynamic posture change on vibr ation propagation across the web and leg joints\, by systematically varyin g the parameters of prey robot vibration\, spider robot leg posture\, and web pre-tension.
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Bio: Eugene Lin is a third year PhD stu dent in Dr. Chen Li’s lab (Terradynamics lab). His work focuses on underst anding environmental sensing on suspended\, sparse terrain. He received a B.S. in Mechanical Engineering at the University of California\, San Diego . He recently presented this work at the annual SICB conference and will p resent it again at the annual March APS conference.
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Aishwarya Pantula “Pick a Side: Untethered Gel Crawlers That Can Break Symmetry”
\nAb stract: The development of untethered soft crawling robots programmed to r espond to environmental stimuli and precisely maneuverable across size sca les has been paramount to the fields of soft robotics\, drug delivery\, an d autonomous smart devices. Of particular relevance are reversible thermor esponsive hydrogels\, which swell and shrink in the temperature range of ( 30- 60 °C) for operating such untethered soft robots in human physiologica l and ambient conditions. While crawling has been demonstrated by thermore sponsive hydrogels\, they need surface modifications in the form of rachet s\, asymmetric patterning\, or constraints to achieve unidirectional motio n.
\nHere we demonstrate and validate a new mechanism for untethered \, unidirectional crawling for multisegmented gel crawlers built from an a ctive thermoresponsive poly (N-isopropyl acrylamide) (pNIPAM) and passive polyacrylamide (pAAM) on flat unpatterned surfaces. By connecting bilayers of different geometries and thicknesses using a centrally suspended gel l inker\, we create a morphological gradient along the fore-aft axis\, which leads to an asymmetry in the contact forces during the swelling and deswe lling of our crawler. We thoroughly explain our mechanism using experiment s and finite element simulations and\, using experiments\, demonstrate tha t we can tune the generated asymmetry and\, in turn\, increase the displac ement of the crawler by varying linker stiffness\, morphology\, and the nu mber of bilayer segments. We believe this mechanism can be widely applied across fields of study to create the next generation of autonomous shape-c hanging and smart locomotors.
\nBio: Aishwarya is a 4th year Ph.D. c andidate in the lab of Dr. David Gracias at Johns Hopkins University\, USA . Her research focuses on exploring smart materials like stimuli-responsiv e hydrogels\, combining them with novel patterning methods like 3D/4D prin ting\, imprint molding\, lithography\, etc.\, and using different mechanic al design strategies to create untethered biomimetic actuators and locomot ors across size scales for soft robotics and biomedical devices.
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Maia Stiber “On using social signals to enable flexible error-aware HRI.”
\nAbstract: Prior error manageme nt techniques often do not possess the versatility to appropriately addres s robot errors across tasks and scenarios. Their fundamental framework inv olves explicit\, manual error management and implicit domain-specific info rmation driven error management\, tailoring their response for specific in teraction contexts. We present a framework for approaching error-aware sys tems by adding implicit social signals as another information channel to c reate more flexibility in application. To support this notion\, we introdu ce a novel dataset (composed of three data collections) with a focus on un derstanding natural facial action unit (AU) responses to robot errors duri ng physical-based human-robot interactions—varying across task\, error\, p eople\, and scenario. Analysis of the dataset reveals that\, through the l ens of error detection\, using AUs as input into error management affords flexibility to the system and has the potential to improve error detection response rate. In addition\, we provide an example real-time interactive robot error management system using the error-aware framework.
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Bio: Maia Stiber is a 4th year Ph.D. candidate in the Department of Computer Science\, co-advised by Dr. Chien-Ming Huang and Dr. Russell Tay lor. She received a B.S. in Computer Science from Caltech in 2019 and a M. S.E. in Computer Science from Johns Hopkins University in 2021. Her work f ocuses on leveraging natural human responses to robot errors in an effort to develop flexible error management techniques in support of effective hu man-robot interaction.
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Victor A ntony “Co-designing with older adults\, for older adults: robots to promot e physical activity.”
\nAbstract: Lack of physical activity has severe negative health consequences for older adults and limits their ability to live independently. Robots have been proposed to help engage o lder adults in physical activity (PA)\, albeit with limited success. There is a lack of robust understanding of older adults’ needs and wants from r obots designed to engage them in PA. In this paper\, we report on the find ings of a co-design process where older adults\, physical therapy experts\ , and engineers designed robots to promote PA in older adults. We found a variety of motivators for and barriers against PA in older adults\; we\, t hen\, conceptualized a broad spectrum of possible robotic support and foun d that robots can play various roles to help older adults engage in PA. Th is exploratory study elucidated several overarching themes and emphasized the need for personalization and adaptability. This work highlights key de sign features that researchers and engineers should consider when developi ng robots to engage older adults in PA\, and underscores the importance of involving various stakeholders in the design and development of assistive robots.
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Bio: Victor Antony is a second-year Ph.D. stude nt in the Department of Computer Science\, advised by Dr. Chien-Ming Huang . He received the Bachelor of Science degree in Computer Science from the University of Rochester in 2021. His work focuses on Social Robots for wel l-being.
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