{"690754":{"#nid":"690754","#data":{"type":"news","title":"New Wearable Reroutes Lost Sensation, Restores Stability","body":[{"value":"\u003Cp\u003EMisjudge a curb or miss a step on the stairs, and there is a split second of panic as your foot doesn\u2019t land when you expect it to. That brief loss of pressure can be enough to throw off your balance entirely.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EFor most, that heart-pounding uncertainty ends the moment the foot finds solid ground. But for many individuals living with conditions like stroke or spinal cord injury (SCI), that sense of disconnect is a permanent reality.\u003C\/p\u003E\u003Cp\u003E\u201cThese conditions of course have a huge effect on our ability to move around and be independent \u2014 but the other side of it is the sensory feedback that we lose,\u201d says \u003Ca href=\u0022https:\/\/people.research.gatech.edu\/matthew-t-flavin\u0022\u003EMatthew Flavin\u003C\/a\u003E, an assistant professor in the \u003Ca href=\u0022https:\/\/ece.gatech.edu\/\u0022\u003ESchool of Electrical and Computer Engineering\u003C\/a\u003E. Most rehabilitation treatments primarily focus on restoring movement, but \u201ceven if you have motor control, if you can\u2019t feel when your foot\u0027s touching the ground it can be really hard for you to move around safely.\u201d\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EIn a new study published in \u003Ca href=\u0022https:\/\/www.pnas.org\/doi\/10.1073\/pnas.2536577123\u0022\u003E\u003Cem\u003EProceedings of the National Academy of Sciences\u003C\/em\u003E\u003C\/a\u003E, Flavin and an interdisciplinary team of researchers introduce a way to bridge this gap: a wearable \u201csensory substitution\u201d system that translates foot pressure into high-tech patterns of heat and vibration they can feel elsewhere.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe system uses high-resolution pressure-sensing insoles designed by the team, which are placed inside a user\u0027s shoes to record how their weight shifts in real-time. This data is streamed via Bluetooth to a flexible, skin-conformable array of haptic receivers worn on the forearms, a part of the body that often retains sensation in SCI. The receivers give quick pressure feedback through vibration, while also alerting the user to longer-term pressure \u201chotspots\u201d through heat.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cOne of the limitations of a lot of approaches in haptics is that you\u0027re having to map a missing sense onto a completely different sense,\u201d says Flavin. \u201cWe\u2019re keeping the type of information that we\u0027re missing, which is the distribution of pressure, and we\u0027re just basically putting it on a different part of their body.\u201d\u003C\/p\u003E\u003Cp\u003ERerouting the lost sensation was key to making the device intuitive to learn. Participants were able to correctly identify the \u201cfeel\u201d of the ground through their arms with high accuracy within a mere two-hour session. When tested with a small group of participants with stroke or SCI, the wearable significantly improved standing balance and led to steadier walking.\u003C\/p\u003E\u003Cp\u003E\u201cWhat\u2019s encouraging about these early results is that participants appeared to use the feedback in ways that supported balance and walking,\u201d says \u003Ca href=\u0022https:\/\/www.mccormick.northwestern.edu\/research-faculty\/directory\/profiles\/rogers-john.html\u0022\u003EJohn Rogers\u003C\/a\u003E, a materials science and engineering professor at Northwestern University who collaborated on this study. \u201cOur study suggests that providing pressure information through another part of the body could be a practical path for helping people compensate for lost sensation.\u201d\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EWhile vibration provides immediate feedback for walking and balance, the team views the thermal feedback as a tool for long-term health. Heat is a slower, low-frequency signal that could alert patients to pressure hotspots, potentially preventing diabetic foot ulcers or pressure injuries for those who are bedridden or use wheelchairs.\u003C\/p\u003E\u003Cp\u003EThe small, lightweight system is completely untethered, making it suitable for use during daily activities in and outside the clinic. It\u2019s also highly adaptable to different injury types, which is ideal for conditions as variable as stroke, SCI, and diabetic neuropathy. Placement of the haptic receivers can be adjusted based on where a patient has the most sensation, and the sensitivity of the insoles can be tailored to each patient.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EAs a member of several of Georgia Tech\u2019s \u003Ca href=\u0022https:\/\/research.gatech.edu\/interdisciplinary-research-institutes\u0022\u003EInterdisciplinary Research Institutes\u003C\/a\u003E \u2014 the \u003Ca href=\u0022https:\/\/neuro.gatech.edu\/\u0022\u003EInstitute for Neuroscience, Neurotechnology, and Society\u003C\/a\u003E, the \u003Ca href=\u0022https:\/\/research.gatech.edu\/robotics\u0022\u003EInstitute for Robotics and Intelligent Machines\u003C\/a\u003E, and the \u003Ca href=\u0022https:\/\/bioresearch.gatech.edu\/\u0022\u003EParker H. Petit Institute for Bioengineering and Biosciences\u003C\/a\u003E \u2014 Flavin credits the project\u2019s success to an interdisciplinary effort and deep engagement with clinicians and patients.\u003C\/p\u003E\u003Cp\u003E\u201cThis reinforces the importance of really engaging with your stakeholders very early on,\u201d says Flavin. \u201cIf you\u0027re not continually refining that concept with those stakeholders, you quickly find that they might be looking for something that your device isn\u0027t delivering.\u201d\u003C\/p\u003E\u003Cp\u003EWith new funding from the National Science Foundation (NSF), the team is now working to make the technology even smaller and more reconfigurable, moving closer to a standard wearable for daily clinical use.\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EDOI: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/doi.org\/10.1073\/pnas.2536577123\u0022\u003E\u003Cem\u003Ehttps:\/\/doi.org\/10.1073\/pnas.2536577123\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EResearchers have developed a wireless wearable that translates foot pressure into heat and vibration, helping individuals with sensory impairments regain balance and mobility.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Researchers have developed a wireless wearable that translates foot pressure into heat and vibration, helping individuals with sensory impairments regain balance and mobility."}],"uid":"35575","created_gmt":"2026-06-15 20:56:13","changed_gmt":"2026-06-16 12:16:33","author":"adavidson38","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-06-15T00:00:00-04:00","iso_date":"2026-06-15T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"680466":{"id":"680466","type":"image","title":"Flavin-Device-Under-Microscope.png","body":"\u003Cdiv\u003EThe system converts pressure underfoot into vibration and heat felt elsewhere on the body, helping people with sensory loss regain awareness of their footing and improve balance.\u003C\/div\u003E","created":"1781557523","gmt_created":"2026-06-15 21:05:23","changed":"1781557523","gmt_changed":"2026-06-15 21:05:23","alt":"Close-up of hands positioning a flexible haptic device with embedded electronics under a microscope, highlighting the small components and patterned array used to deliver sensory feedback.","file":{"fid":"264732","name":"Flavin-Device-Under-Microscope.png","image_path":"\/sites\/default\/files\/2026\/06\/15\/Flavin-Device-Under-Microscope.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/06\/15\/Flavin-Device-Under-Microscope.png","mime":"image\/png","size":10816942,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/06\/15\/Flavin-Device-Under-Microscope.png?itok=7OCs2RGM"}},"680467":{"id":"680467","type":"image","title":"Flavin-Device-Portrait.png","body":"\u003Cdiv\u003EMatthew Flavin, assistant professor in electrical engineering and lead author of the study, holds the flexible haptic device.\u003C\/div\u003E","created":"1781557731","gmt_created":"2026-06-15 21:08:51","changed":"1781557731","gmt_changed":"2026-06-15 21:08:51","alt":"A researcher stands in a laboratory holding a flexible, transparent wearable device embedded with small electronic nodes, with microscopes and lab equipment visible in the background.","file":{"fid":"264733","name":"Flavin-Device-Portrait.png","image_path":"\/sites\/default\/files\/2026\/06\/15\/Flavin-Device-Portrait.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/06\/15\/Flavin-Device-Portrait.png","mime":"image\/png","size":12093054,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/06\/15\/Flavin-Device-Portrait.png?itok=7qCineau"}},"680468":{"id":"680468","type":"image","title":"Flavin-Device-Schematic.png","body":"\u003Cdiv\u003EPressure-sensing insoles in the shoes transmit real-time data to flexible haptic arrays worn on the forearms, where patterns of vibration and heat recreate a sense of foot-ground contact through sensory substitution.\u003C\/div\u003E","created":"1781571167","gmt_created":"2026-06-16 00:52:47","changed":"1781571167","gmt_changed":"2026-06-16 00:52:47","alt":"Schematic diagram of a wearable sensory substitution system showing pressure-sensing insoles placed inside shoes, flexible haptic arrays worn on both forearms, and a smartphone interface. Close-up views highlight the insole sensor layout and a dense grid of small actuators on the forearm device that deliver vibration and heat.","file":{"fid":"264734","name":"Flavin-Device-Schematic.png","image_path":"\/sites\/default\/files\/2026\/06\/15\/Flavin-Device-Schematic.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/06\/15\/Flavin-Device-Schematic.png","mime":"image\/png","size":2450907,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/06\/15\/Flavin-Device-Schematic.png?itok=U8hkGUYv"}}},"media_ids":["680466","680467","680468"],"related_links":[{"url":"https:\/\/neuro.gatech.edu\/new-wearable-device-monitors-skin-health-real-time","title":"New Wearable Device Monitors Skin Health in Real Time"},{"url":"https:\/\/neuro.gatech.edu\/confronting-roadblocks-medical-technology-innovation","title":"Confronting the Roadblocks in Medical Technology Innovation"},{"url":"https:\/\/neuro.gatech.edu\/head-toe-georgia-tech-researchers-treat-entire-human-body-through-neuroscience-research","title":"Head to Toe: Georgia Tech Researchers Treat the Entire Human Body Through Neuroscience Research"}],"groups":[{"id":"66220","name":"Neuro"},{"id":"1292","name":"Parker H. Petit Institute for Bioengineering and Bioscience (IBB)"},{"id":"1188","name":"Research Horizons"}],"categories":[{"id":"138","name":"Biotechnology, Health, Bioengineering, Genetics"},{"id":"146","name":"Life Sciences and Biology"},{"id":"135","name":"Research"},{"id":"152","name":"Robotics"}],"keywords":[{"id":"187915","name":"go-researchnews"},{"id":"172970","name":"go-neuro"}],"core_research_areas":[{"id":"39441","name":"Bioengineering and Bioscience"},{"id":"193656","name":"Neuro Next Initiative"},{"id":"39521","name":"Robotics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EWriter and Media Contact:\u003C\/strong\u003E\u003Cbr\u003E\u003Ca href=\u0022mailto:audra.davidson@research.gatech.edu\u0022\u003EAudra Davidson\u003C\/a\u003E\u003Cbr\u003EResearch Communications Program Manager\u003Cbr\u003EInstitute for Neuroscience, Neurotechnology, and Society (INNS)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EPhotos:\u003C\/strong\u003E\u003Cbr\u003EMaxwell Guberman\u003C\/p\u003E","format":"limited_html"}],"email":["audra.davidson@research.gatech.edu"],"slides":[],"orientation":[],"userdata":""}},"690589":{"#nid":"690589","#data":{"type":"news","title":"Ph.D. Student Gets the Assist as Bike Robot Performs First Front Flip","body":[{"value":"\u003Cp\u003EA bicycle robot from the Robotics and AI Institute (RAI) in Cambridge, Mass., has become the first to perform an unassisted acrobatic front flip.\u003C\/p\u003E\u003Cp\u003ERAI calls the bicycle robot an ultra-mobility vehicle (UMV). It can reach a height of 3 feet and can jump from the floor onto a platform.\u003C\/p\u003E\u003Cp\u003EThe contributions of a Georgia Tech Ph.D. student helped make these feats possible through a robot control policy he developed.\u003C\/p\u003E\u003Cp\u003EJeonghwan Kim, who is pursuing a Ph.D. in robotics under the advisement of Associate Professor Sehoon Ha, spent two semesters interning at RAI. His task was to design a policy to teach the UMV to land after a flip.\u003C\/p\u003E\u003Cp\u003EThe result was iterative motion imitation (IMI), a novel method that imitates flip trajectories generated from prior examples. Kim said the robot bases its flip on a demonstration, and human engineers reconstruct and refine the flip path through simulation to fill in the gaps.\u003C\/p\u003E\u003Cp\u003E\u201cTo guide the robot to flip, we started with an imperfect trajectory generated by a motor-based controller and then ran simulations,\u201d Kim said. \u201cIt\u2019s an unstable trajectory, but we use it as a guide to train a single policy that can track it as it lands and tries to balance itself.\u201d\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003ESticking the Landing\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003EKim interned under the supervision of Shamel Fahmi, a research scientist at the RAI Institute. RAI has been developing the UMV for nearly three years.\u003C\/p\u003E\u003Cp\u003E\u201cWe wanted to work on a different robot morphology that wasn\u2019t legs or legs with wheels,\u201d Fahmi said. \u201cThat\u2019s when we thought of working with bikes.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cWe want to merge the athleticism of (Boston Dynamics\u2019) Atlas with the mobility of a bike. We wanted a robot that can go anywhere, do parkour, and acrobatics.\u201d\u003C\/p\u003E\u003Cp\u003EFahmi said that before Kim arrived, the research team had trouble getting the UMV to land consistently without breaking or falling.\u003C\/p\u003E\u003Cp\u003EThe UMV has two joints \u2014 an upper and a lower. The upper joint contains the motors and pulls the lower joint along as it propels into the air. The problem is getting the lighter lower joint to absorb the impact of landing without being crushed by the heavier upper joint.\u003C\/p\u003E\u003Cp\u003E\u201cThat\u2019s what brings reinforcement learning into the equation,\u201d Fahmi said. \u201cWe teach the robot to minimize its impact on the ground to land gracefully.\u201d\u003C\/p\u003E\u003Cp\u003EFahmi said that Kim proved the imitation examples the robot learns from don\u2019t have to be perfect. The process takes some time, but all it needs is a rough idea to get started.\u003C\/p\u003E\u003Cp\u003E\u201cYou can have an imperfect sketch and then constantly refine it,\u201d Fahmi said. \u201cThe first time, it\u2019s not going to go well.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cWe don\u2019t care about torque or power limits as long as it does the motion. Then we\u2019ll have a slightly better reference, repeat it, and imitate it again. In every iteration, we can add more parameters.\u201d\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EUp Against the Clock\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003EKim said he felt the pressure of time constraints during his two semesters with RAI as he worked to achieve consistent, successful landings. Even though he had multiple UMVs to experiment with, they broke down dozens of times. Each time one broke, a hardware team at RAI had to repair it.\u003C\/p\u003E\u003Cp\u003E\u201cThere was a lot of pressure to not only get this working before my internship ended, but also knowing there are costs behind every failed attempt, and every time the robot breaks, it takes time to repair it,\u201d Kim said.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cIt took almost five months for it to land without breaking. Then we needed two more months for it to stay balanced after the landing. It requires a lot of engineering effort to achieve a robust control policy for a safe flip.\u201d\u003C\/p\u003E\u003Cp\u003EBy the time Kim left RAI, the IMI policy had achieved consistent, seamless landings.\u003C\/p\u003E\u003Cp\u003E\u201cThe jump right now is what we call the visitor demo,\u201d Fahmi said. \u201cIf there are guests coming over to see it, we want to show them something that is extremely impressive, but also, more importantly, extremely reliable. It never fails.\u003C\/p\u003E\u003Cp\u003E\u201cIt was only possible because of the huge effort we put into designing, maintaining, and continuously improving the robot.\u201d\u003C\/p\u003E\u003Cp\u003EKim authored a\u0026nbsp;\u003Ca href=\u0022https:\/\/imi-umv.github.io\/\u0022\u003Epaper\u003C\/a\u003E on his framework and will present it at this week\u2019s\u0026nbsp;\u003Ca href=\u0022https:\/\/2026.ieee-icra.org\/\u0022\u003EInternational Conference on Robotics and Automation\u003C\/a\u003E (ICRA) in Vienna.\u003C\/p\u003E\u003Cp\u003EFor more information about the UMV project, please visit the\u0026nbsp;\u003Ca href=\u0022https:\/\/rai-inst.com\/resources\/blog\/designing-wheeled-robotic-systems\/\u0022\u003ERAI blog\u003C\/a\u003E or watch their\u0026nbsp;\u003Ca href=\u0022https:\/\/www.youtube.com\/watch?v=cjaZUFMZWOY\u0026amp;t=95s\u0022\u003Evideo\u003C\/a\u003E on YouTube.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EA bicycle robot from the Robotics and AI Institute (RAI) in Cambridge, Mass., has become the first to perform an unassisted acrobatic front flip.\u003C\/p\u003E\u003Cp\u003EJeonghwan Kim, who is pursuing a Ph.D. in robotics under the advisement of Associate Professor Sehoon Ha, spent two semesters interning at RAI. His task was to design a policy to teach the UMV to land after a flip.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"A Georgia Tech Ph.D. student\u0027s robot control policy helped the Robotics and AI Institute develop the first bike robot capable of an unassisted front flip."}],"uid":"36530","created_gmt":"2026-06-02 13:06:16","changed_gmt":"2026-06-02 13:11:56","author":"Nathan Deen","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-06-02T00:00:00-04:00","iso_date":"2026-06-02T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"680398":{"id":"680398","type":"image","title":"DSC07117-2048x1365.jpg-copy.jpg","body":"\u003Cp\u003EPhoto courtesy of the Robotics and AI Institute\u003C\/p\u003E","created":"1780405593","gmt_created":"2026-06-02 13:06:33","changed":"1780405662","gmt_changed":"2026-06-02 13:07:42","alt":"Bike robot","file":{"fid":"264654","name":"DSC07117-2048x1365.jpg-copy.jpg","image_path":"\/sites\/default\/files\/2026\/06\/02\/DSC07117-2048x1365.jpg-copy.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/06\/02\/DSC07117-2048x1365.jpg-copy.jpg","mime":"image\/jpeg","size":131530,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/06\/02\/DSC07117-2048x1365.jpg-copy.jpg?itok=12RGh4JN"}}},"media_ids":["680398"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1188","name":"Research Horizons"},{"id":"50876","name":"School of Interactive Computing"}],"categories":[{"id":"152","name":"Robotics"}],"keywords":[{"id":"188776","name":"go-research"},{"id":"187915","name":"go-researchnews"},{"id":"9153","name":"Research Horizons"},{"id":"187991","name":"go-robotics"},{"id":"184632","name":"mobile robotics"}],"core_research_areas":[{"id":"39521","name":"Robotics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"690553":{"#nid":"690553","#data":{"type":"news","title":"New App Allows Anyone to Operate a Robot From Their Phone","body":[{"value":"\u003Cp\u003ESomeone with no computing experience may soon be able to remotely control a robot from anywhere on the planet using a smartphone, thanks to new technology developed by Georgia Tech.\u003C\/p\u003E\u003Cp\u003EThe new technology is also set to revolutionize the scale of policy training data collection, which is essential to advancing robotic capabilities and meeting growing production demand.\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/cobalt-teleop.github.io\/\u0022\u003ECOBALT\u003C\/a\u003E is a mobile app that turns smartphones into controllers for robot arms. With a secure Wi-Fi connection to a server, users can move their phones in any direction, and the robot arm will mirror the motion \u2014 from anywhere in the world.\u003C\/p\u003E\u003Cp\u003EAyush Agarwal, a Ph.D. student in Georgia Tech\u2019s School of Interactive Computing who leads a research team developing COBALT, said it works like the games people play on smartphones. Users can press a button to have the arm grasp an object, move it, and release it with another button.\u003C\/p\u003E\u003Cp\u003EAgarwal conducted several user studies with participants in nine countries who remotely operated robot arms inside Georgia Tech\u2019s\u0026nbsp;\u003Ca href=\u0022https:\/\/www.pair.toronto.edu\/\u0022\u003EPeople, AI \u0026amp; Robotics (PAIR) Lab\u003C\/a\u003E. The lab is directed by Assistant Professor Animesh Garg, who advises Agarwal.\u003C\/p\u003E\u003Cp\u003E\u201cWe built an entire distribution system for remote teleoperation scaled to where we had people from Indonesia, India, and Pakistan operating for us,\u201d Agarwal said. \u201cThey were novice operators who had never done it before. By collecting data from these new users, we showed that we can train policies to automate certain tasks.\u201d\u003C\/p\u003E\u003Cp\u003EGarg envisions a world where data collection for policy training is done through crowdsourcing. He began working toward this goal 10 years ago as a postdoc at Stanford University, when he developed\u0026nbsp;\u003Ca href=\u0022https:\/\/roboturk.stanford.edu\/\u0022\u003ERoboTurk\u003C\/a\u003E, an earlier version of COBALT.\u003C\/p\u003E\u003Cp\u003E\u201cThere is a large-scale data collection requirement for mass robot production to be possible, and it will not be solved purely through simulation,\u201d Garg said.\u003C\/p\u003E\u003Cp\u003E\u201cOur idea was, what if we could get almost every person on the planet to be a passive source for data collection? There are almost five billion people who have smartphones and know how to use them.\u201d\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EEducation and Economy Impact\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003EAnother major implication of COBALT could be expanded access to CS and robotics education.\u003C\/p\u003E\u003Cp\u003EStudents can learn to operate a robot remotely in any classroom. In fact, Garg and his lab recently hosted students from Midtown High School in Atlanta to demonstrate COBALT and let them control robot arms from a phone.\u003C\/p\u003E\u003Cp\u003EGarg also sees the possibility of a \u201cgig economy\u201d in which people pay remote operators to control assistive robots in their homes and complete household chores for them.\u003C\/p\u003E\u003Cp\u003E\u201cIt could be Uber for robots,\u201d he said. \u201cPeople who want to log onto the platform can do so at their convenience and for as long as they want.\u201d\u003C\/p\u003E\u003Cp\u003ECompanies with robot-dependent labor tasks could also use the platform to enable human oversight.\u003C\/p\u003E\u003Cp\u003E\u201cIf I deploy a robot in a factory that achieves high autonomy for most tasks, but there are still times it needs help, a human could operate the robot from anywhere in the world,\u201d Garg said.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EBuilding a Network\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003EAgarwal\u2019s studies showed that people prefer to interact with and control a robot using a smartphone rather than virtual reality (VR) headsets, controllers, keyboards, mice, or other devices.\u003C\/p\u003E\u003Cp\u003E\u201cThe phone is a more intuitive interface and can provide data quality that\u2019s on par with other commonly used devices,\u201d he said.\u003C\/p\u003E\u003Cp\u003EAgarwal also said there is minimal latency in the video feed sent back to operators on the other side of the world. That\u2019s because the amount of data being processed is small.\u003C\/p\u003E\u003Cp\u003EThe data is carried over Web Real-Time Communication (WebRTC), the same technology used by many streaming services and web conferencing platforms such as Zoom and Google Meet.\u003C\/p\u003E\u003Cp\u003E\u201cThere\u2019s a connection from your phone to the teleoperation server, which is connected to the robots,\u201d Agarwal said.\u003C\/p\u003E\u003Cp\u003E\u201cThen there\u2019s another connection from the teleoperation server back to the user, which allows for a video stream. We need low latency on both because you don\u2019t want the user to move their phone and wait 10 seconds to see the visual feed.\u201d\u003C\/p\u003E\u003Cp\u003EAgarwal is the co-lead author of a paper on COBALT that is being presented at the\u0026nbsp;\u003Ca href=\u0022https:\/\/2026.ieee-icra.org\/\u0022\u003EIEEE International Conference on Robotics and Automation\u003C\/a\u003E this week in Vienna. He said the paper stands out because it has moved from theory to the implementation of an entire distribution network.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cThe real novelty of our paper is the systems that we build around it to actually support the scaling of remote operation and data collection at a global level,\u201d he said.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EWith a secure Wi-Fi connection to a server, users can move their phones in any direction, and the robot arm will mirror the motion \u2014 from anywhere in the world.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"A new mobile app turns smartphones into controllers for robot arms. "}],"uid":"36530","created_gmt":"2026-05-29 16:37:15","changed_gmt":"2026-05-29 16:43:09","author":"Nathan Deen","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-05-29T00:00:00-04:00","iso_date":"2026-05-29T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"680381":{"id":"680381","type":"image","title":"Animesh-Garg-lab_86A8356.jpg","body":null,"created":"1780072785","gmt_created":"2026-05-29 16:39:45","changed":"1780072785","gmt_changed":"2026-05-29 16:39:45","alt":"Three men use their phones to control a robot arm","file":{"fid":"264637","name":"Animesh-Garg-lab_86A8356.jpg","image_path":"\/sites\/default\/files\/2026\/05\/29\/Animesh-Garg-lab_86A8356.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/05\/29\/Animesh-Garg-lab_86A8356.jpg","mime":"image\/jpeg","size":186525,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/05\/29\/Animesh-Garg-lab_86A8356.jpg?itok=8WOofrjN"}}},"media_ids":["680381"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1188","name":"Research Horizons"},{"id":"50876","name":"School of Interactive Computing"}],"categories":[{"id":"152","name":"Robotics"}],"keywords":[{"id":"188776","name":"go-research"},{"id":"187915","name":"go-researchnews"},{"id":"9153","name":"Research Horizons"},{"id":"168927","name":"smartphones"},{"id":"44461","name":"robot arm"},{"id":"93131","name":"ICRA"}],"core_research_areas":[{"id":"39521","name":"Robotics"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"688391":{"#nid":"688391","#data":{"type":"news","title":"Robot Pollinator Could Produce More, Better Crops for Indoor Farms","body":[{"value":"\u003Cp\u003EA new robot could solve one of the biggest challenges facing indoor farmers: manual pollination.\u003C\/p\u003E\u003Cp\u003EIndoor farms, also known as vertical farms, are popular among agricultural researchers and are expanding across the agricultural industry. Some benefits they have over outdoor farms include:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EYear-round production of food crops\u003C\/li\u003E\u003Cli\u003ELess water and land requirements\u003C\/li\u003E\u003Cli\u003ENot needing pesticides\u003C\/li\u003E\u003Cli\u003EReducing carbon emissions from shipping\u003C\/li\u003E\u003Cli\u003EReducing food waste\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EAdditionally,\u0026nbsp;\u003Ca href=\u0022https:\/\/www.agritecture.com\/blog\/2021\/7\/20\/5-ways-vertical-farming-is-improving-nutrition\u0022\u003E\u003Cstrong\u003Esome studies\u003C\/strong\u003E\u003C\/a\u003E indicate that indoor farms produce more nutritious food for urban communities.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EHowever, these farms are often inaccessible to birds, bees, and other natural pollinators, leaving the pollination process to humans. The tedious process must be completed by hand for each flower to ensure the indoor crop flourishes.\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/research.gatech.edu\/people\/ai-ping-hu\u0022\u003E\u003Cstrong\u003EAi-Ping Hu\u003C\/strong\u003E\u003C\/a\u003E, a principal research engineer at the Georgia Tech Research Institute (GTRI), has spent years exploring methods to efficiently pollinate flowering plants and food crops in indoor farms to find a way to efficiently pollinate flower plants and food crops in indoor farms.\u003C\/p\u003E\u003Cp\u003EHu,\u0026nbsp;\u003Ca href=\u0022https:\/\/research.gatech.edu\/people\/shreyas-kousik\u0022\u003E\u003Cstrong\u003EAssistant Professor Shreyas Kousik of the George W. Woodruff School of Mechanical Engineering\u003C\/strong\u003E\u003C\/a\u003E, and a rotating group of student interns have developed a robot prototype that may be up to the task.\u003C\/p\u003E\u003Cp\u003EThe robot can efficiently pollinate plants that have both male and female reproductive parts. These plants only require pollen to be transferred from one part to the other rather than externally from another flower.\u003C\/p\u003E\u003Cp\u003ENatural pollinators perform this task outdoors, but Hu said indoor farmers often use a paintbrush or electric tootbrush to ensure these flowers are pollinated.\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EKnowing the Pose\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003EAn early challenge the research team addressed was teaching the robot to identify the \u201cpose\u201d of each flower. Pose refers to a flower\u2019s orientation, shape, and symmetry. Knowing these details ensures precise delivery of the pollen to maximize reproductive success.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cIt\u2019s crucial to know exactly which way the flowers are facing,\u201d Hu said.\u003C\/p\u003E\u003Cp\u003E\u201cYou want to approach the flower from the front because that\u2019s where all the biological structures are. Knowing the pose tells you where the stem is. Our device grasps the stem and shakes it to dislodge the pollen.\u003C\/p\u003E\u003Cp\u003E\u201cEvery flower is going to have its own pose, and you need to know what that is within at least 10 degrees.\u201d\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EComputer Vision Breakthrough\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003E\u003Cstrong\u003EHarsh Muriki\u003C\/strong\u003E is a robotics master\u2019s student at Georgia Tech\u2019s School of Interactive Computing, who used computer vision to solve the pose problem while interning for Hu and GTRI.\u003C\/p\u003E\u003Cp\u003EMuriki attached a camera to a FarmBot to capture images of strawberry plants from dozens of angles in a small garden in front of Georgia Tech\u2019s Food Processing Technology Building. The\u0026nbsp;\u003Ca href=\u0022https:\/\/farm.bot\/?srsltid=AfmBOoqh1Z8vSs3WflZisgw5DsOUSo8shD4VtY0Y8_VmVpVyt0Iwalxo\u0022\u003E\u003Cstrong\u003EFarmBot\u003C\/strong\u003E\u003C\/a\u003E is an XYZ-axis robot that waters and sprays pesticides on outdoor gardens, though it is not capable of pollination.\u003C\/p\u003E\u003Cp\u003E\u201cWe reconstruct the images of the flower into a 3D model and use a technique that converts the 3D model into multiple 2D images with depth information,\u201d Muriki said. \u201cThis enables us to send them to object detectors.\u201d\u003C\/p\u003E\u003Cp\u003EMuriki said he used a real-time object detection system called YOLO (You Only Look Once) to classify objects. YOLO is known for identifying and classifying objects in a single pass.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EVed Sengupta\u003C\/strong\u003E, a computer engineering major who interned with Muriki, fine-tuned the algorithms that converted 3D images into 2D.\u003C\/p\u003E\u003Cp\u003E\u201cThis was a crucial part of making robot pollination possible,\u201d Sengupta said. \u201cThere is a big gap between 3D and 2D image processing.\u003C\/p\u003E\u003Cp\u003E\u201cThere\u2019s not a lot of data on the internet for 3D object detection, but there\u2019s a ton for 2D. We were able to get great results from the converted images, and I think any sector of technology can take advantage of that.\u201d\u003C\/p\u003E\u003Cp\u003ESengupta, Muriki, and Hu co-authored a paper about their work that was accepted to the 2025 International Conference on Robotics and Automation (ICRA) in Atlanta.\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EMeasuring Success\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003EThe pollination robot, built in Kousik\u2019s Safe Robotics Lab, is now in the prototype phase.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EHu said the robot can do more than pollinate. It can also analyze each flower to determine how well it was pollinated and whether the chances for reproduction are high.\u003C\/p\u003E\u003Cp\u003E\u201cIt has an additional capability of microscopic inspection,\u201d Hu said. \u201cIt\u2019s the first device we know of that provides visual feedback on how well a flower was pollinated.\u201d\u003C\/p\u003E\u003Cp\u003EFor more information about the robot, visit the\u0026nbsp;\u003Ca href=\u0022https:\/\/saferoboticslab.me.gatech.edu\/research\/towards-robotic-pollination\/\u0022\u003E\u003Cstrong\u003ESafe Robotics Lab project page\u003C\/strong\u003E\u003C\/a\u003E.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EManual pollination is one of the biggest challenges for indoor farmers. These farms are often inaccessible to birds, bees, and other natural pollinators, leaving the pollination process to humans. The tedious process must be completed by hand for each flower to ensure the indoor crop flourishes.\u003C\/p\u003E\u003Cp\u003EA Georgia Tech research led by Ai-Ping Hu and Shreyas Kousik team is working to solve that. A robot they\u0027ve developed can efficiently pollinate plants that have both male and female reproductive parts. These plants only require pollen to be transferred from one part to the other rather than externally from another flower.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"A research team that expands GTRI, the College of Engineering, and the College of Computing have developed a robot capable of pollinating flowers in indoor farms."}],"uid":"36530","created_gmt":"2026-02-19 18:58:12","changed_gmt":"2026-03-20 12:54:01","author":"Nathan Deen","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-02-19T00:00:00-05:00","iso_date":"2026-02-19T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679370":{"id":"679370","type":"image","title":"Harsh-Muriki_86A0006.jpg","body":null,"created":"1771527500","gmt_created":"2026-02-19 18:58:20","changed":"1771527500","gmt_changed":"2026-02-19 18:58:20","alt":"Harsh Muriki","file":{"fid":"263520","name":"Harsh-Muriki_86A0006.jpg","image_path":"\/sites\/default\/files\/2026\/02\/19\/Harsh-Muriki_86A0006.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/02\/19\/Harsh-Muriki_86A0006.jpg","mime":"image\/jpeg","size":140654,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/02\/19\/Harsh-Muriki_86A0006.jpg?itok=rd0rv1Yt"}}},"media_ids":["679370"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1188","name":"Research Horizons"},{"id":"50876","name":"School of Interactive Computing"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"153","name":"Computer Science\/Information Technology and Security"},{"id":"145","name":"Engineering"},{"id":"135","name":"Research"},{"id":"152","name":"Robotics"}],"keywords":[{"id":"9153","name":"Research Horizons"},{"id":"187991","name":"go-robotics"},{"id":"192863","name":"go-ai"},{"id":"11506","name":"computer vision"},{"id":"180840","name":"computer vision systems"},{"id":"669","name":"agriculture"},{"id":"194392","name":"AI in Agriculture"},{"id":"170254","name":"urban gardening"},{"id":"94111","name":"farming"},{"id":"14913","name":"urban farming"},{"id":"23911","name":"bees"},{"id":"6660","name":"flowers"},{"id":"187915","name":"go-researchnews"}],"core_research_areas":[{"id":"193655","name":"Artificial Intelligence at Georgia Tech"},{"id":"193653","name":"Georgia Tech Research Institute"},{"id":"39521","name":"Robotics"}],"news_room_topics":[{"id":"71911","name":"Earth and Environment"}],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:ndeen6@gatech.edu\u0022\u003ENathan Deen\u003C\/a\u003E\u003Cbr\u003ECollege of Computing\u003Cbr\u003EGeorgia Tech\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"688893":{"#nid":"688893","#data":{"type":"news","title":"Sheepdogs Reveal a Better Way to Guide Robot Swarms","body":[{"value":"\u003Cp\u003ESheepdogs, bred to control large groups of sheep in open fields, have demonstrated their skills in competitions dating back to the 1870s.\u003C\/p\u003E\u003Cp\u003EIn these contests, a handler directs a trained dog with whistle signals to guide a small group of sheep across a field and sometimes split the flock cleanly into two groups. But sheep do not always cooperate.\u003C\/p\u003E\u003Cp\u003EResearchers at the Georgia Institute of Technology studied how handler\u2013dog teams manage these unpredictable flocks in sheepdog trials and found principles that extend beyond livestock herding.\u003C\/p\u003E\u003Cp\u003EIn a \u003Ca href=\u0022https:\/\/www.science.org\/doi\/10.1126\/sciadv.adx6791\u0022\u003E\u003Cstrong\u003Estudy\u003C\/strong\u003E\u003C\/a\u003E published in \u003Cem\u003EScience Advances\u0026nbsp;\u003C\/em\u003Eas the cover feature, the researchers applied those insights to computer simulations showing how similar strategies could improve the control of robot swarms, autonomous vehicles, AI agents, and other networked systems where many machines must coordinate their actions despite uncertain conditions.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EGroup Movement Dynamics\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u201cBirds, bugs, fish, sheep, and many other organisms move in groups because it benefits individuals, including protection from predators,\u201d said \u003Ca href=\u0022https:\/\/bhamla.gatech.edu\/\u0022\u003E\u003Cstrong\u003ESaad Bhamla\u003C\/strong\u003E\u003C\/a\u003E, an associate professor in Georgia Tech\u2019s School of Chemical and Biomolecular Engineering. \u201cThe puzzle is that the \u2018group\u2019 is not a single organism. It is built from many individuals, each making local, imperfect decisions.\u201d\u003C\/p\u003E\u003Cp\u003EWhen a predator threatens a herd of sheep, individuals near the edge often move toward the center to reduce their own risk, Bhamla explained. \u201cThis is \u2018selfish herd\u2019 behavior,\u201d he said. \u201cShepherds exploit that instinct using trained dogs.\u201d\u003C\/p\u003E\u003Cp\u003EFrom examining hours of contest footage, the researchers found that controlling small groups of sheep can be harder than managing large ones. A larger group, with more sheep protected in the center, may behave more coherently than a small group as the animals constantly shift between two instincts: \u201cfollow the group\u201d and \u201cflee the dog.\u201d\u003C\/p\u003E\u003Cp\u003E\u201cThat switching behavior makes the group unpredictable,\u201d said Tuhin Chakrabortty, a former postdoctoral researcher in the Bhamla Lab who co-led the study.\u003C\/p\u003E\u003Cp\u003ELooking closely at how dogs and their handlers guide small groups, the researchers found that unpredictability in the flock\u2019s behavior does not always make control harder. \u201cUnder the right conditions, that \u2018noisy\u2019 behavior might actually be a benefit,\u201d Bhamla said.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESuccessful Sheep Herding\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESheepdog handlers categorize sheep by how strongly they respond to a dog\u2019s threatening pressure. Some very responsive sheep might panic under too much pressure, while others might ignore mild pressure and require stronger positioning by the dog.\u003C\/p\u003E\u003Cp\u003EThe researchers observed that successful control often followed a two-step pattern. First, the dog subtly influenced the sheep\u2019s orientation while the animals were mostly standing still. Once the flock was aligned in the desired direction, the dog increased pressure to trigger movement. The timing of those actions was critical, because alignment within a small group could disappear quickly as individuals switched between instincts.\u003C\/p\u003E\u003Cp\u003E\u201cIn our simulations, increasing pressure makes the flock reach the desired orientation faster, but how long the flock stays aligned is set mainly by noise,\u201d Chakrabortty said. \u201cIn essence, dogs can steer the direction, but they can\u2019t hold that decision indefinitely, so timing matters.\u201d\u003C\/p\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003EDeveloping Computer Models\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ETo understand the broader implications of that behavior, the team developed computer models that captured how sheep respond both to the dog and to one another. The models allowed the researchers to test different strategies for guiding groups whose members make independent decisions under uncertainty.\u003C\/p\u003E\u003Cp\u003EThey then applied those ideas to simulations of robotic swarms. Engineers often design such systems so that each robot blends signals from all nearby robots before deciding how to move. While that approach works well when signals are clear, it can break down when information is noisy or conflicting, Bhamla explained.\u003C\/p\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cp\u003ETo explain why that switching strategy can work under noisy conditions, the researchers used an analogy of a smoke-filled room where only one person can see the exit, and no one knows who that person is. If everyone polls everyone else and averages the guesses, the one correct signal can get diluted by many noisy ones.\u003C\/p\u003E\u003Cp\u003E\u201cThat\u2019s the counterintuitive part. When only one person has the right information, averaging can wash out the signal. But if you follow one person at a time, and keep switching who that is, the right information can spread through the crowd,\u201d Bhamla said.\u003C\/p\u003E\u003Cp\u003EBuilding on that idea, the researchers tested a strategy inspired by the switching behavior they observed in sheep. In the simulations, each robot paid attention to just one source at a time (either a guiding signal or a neighboring robot) and switched that source from one step to the next.\u003C\/p\u003E\u003Cp\u003EUnder noisy conditions, this switching strategy required less effort to keep the group moving along a desired path than either averaging-based strategies or fixed leader-follower strategies.\u003C\/p\u003E\u003Cp\u003EThe researchers call their approach the Indecisive Swarm Algorithm. The name reflects a counterintuitive insight: allowing influence to shift among individuals over time can make groups easier to guide when conditions are uncertain.\u003C\/p\u003E\u003Cp\u003E\u201cOur findings suggest that the same dynamics that make small animal groups unpredictable may also offer new ways to control complex engineered systems,\u201d Bhamla said.\u003C\/p\u003E\u003Cp\u003ECITATION: Tuhin Chakrabortty and Saad Bhamla, \u201c\u003Ca href=\u0022https:\/\/www.science.org\/doi\/10.1126\/sciadv.adx6791\u0022\u003E\u003Cstrong\u003EControlling noisy herds: Temporal network restructuring improves control of indecisive collectives\u003C\/strong\u003E\u003C\/a\u003E,\u201d \u003Cem\u003EScience Advances\u003C\/em\u003E, 2026\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EThis research was funded in part by Schmidt Sciences as part of a \u003C\/em\u003E\u003Ca href=\u0022https:\/\/news.gatech.edu\/news\/2025\/09\/16\/saad-bhamla-named-2025-schmidt-polymath\u0022\u003E\u003Cem\u003ESchmidt Polymath\u003C\/em\u003E\u003C\/a\u003E\u003Cem\u003E grant to Saad Bhamla.\u003C\/em\u003E\u003C\/p\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech researchers studying sheepdog trials found new principles for guiding unpredictable groups and used them to develop computer models that could improve coordination in robot swarms, autonomous vehicles, and other networked systems.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Tech researchers studying sheepdog trials found new principles for guiding unpredictable groups and used them to develop computer models that could improve coordination in robot swarms, autonomous vehicles, and other networked systems."}],"uid":"27271","created_gmt":"2026-03-11 19:59:46","changed_gmt":"2026-03-12 15:53:25","author":"Brad Dixon","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-03-11T00:00:00-04:00","iso_date":"2026-03-11T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679589":{"id":"679589","type":"video","title":"SMART Dogs herding sheep on a farm, looks like flock of bird pattern","body":"\u003Cp\u003ESMART Dogs herding sheep on a farm, looks like flock of bird pattern\u003C\/p\u003E","created":"1773260200","gmt_created":"2026-03-11 20:16:40","changed":"1773260200","gmt_changed":"2026-03-11 20:16:40","video":{"youtube_id":"_CjwqIX6C2I","video_url":"https:\/\/youtu.be\/_CjwqIX6C2I?si=bfsxIT77-iAJCm-2"}},"679590":{"id":"679590","type":"video","title":"A dog herding sheep in a sheepdog trial","body":"\u003Cp\u003E\u003Cem\u003EA dog herding sheep in a sheepdog 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