{"689051":{"#nid":"689051","#data":{"type":"news","title":"Smarter, Faster, and More Human: A Leap Toward General-Purpose Robots","body":[{"value":"\u003Cp\u003ERobots are increasingly learning new skills by watching people. From folding laundry to handling food, many real-world, humanlike tasks are too nuanced to be efficiently programmed step by step.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EWith imitation learning, humans demonstrate a task and robots learn to copy what they see through cameras and sensors. While at the leading edge of robotics research, this approach is limited by a major constraint: Robots can only work as fast as the people who taught them.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ENow, Georgia Tech researchers have \u003Ca href=\u0022https:\/\/arxiv.org\/abs\/2506.11948\u0022\u003Ecreated a tool\u003C\/a\u003E that smashes that speed barrier. The system allows robots to execute complex tasks significantly faster than human demonstrations while maintaining precision, control, and safety.\u003C\/p\u003E\u003Cp\u003EThe team addresses a central challenge in modern robotics: how to combine the flexibility of learning from humans with the speed and reliability required for real-world deployment. The technology could lead to wider adoption of imitation learning in industrial and household applications and even enable robots to execute humanlike tasks better than ever before.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cThe thing we\u2019re trying to create \u2014 and I would argue industry is also trying to create \u2014 is a general-purpose robot that can do any task that human hands can do,\u201d said \u003Ca href=\u0022https:\/\/people.research.gatech.edu\/node\/18047\u0022\u003EShreyas Kousik\u003C\/a\u003E, assistant professor in the George W. Woodruff School of Mechanical Engineering and a co-lead author on the study. \u201cTo make that work outside the lab, speed really matters.\u201d\u003C\/p\u003E\u003Cp\u003EThe new tool, \u003Ca href=\u0022https:\/\/nadunranawaka1.github.io\/sail-policy\/\u0022\u003ESAIL\u003C\/a\u003E (Speed Adaptation for Imitation Learning), was born out of a cross-campus, interdisciplinary collaboration that brought together expertise in mechanical engineering, robotics systems, and machine learning. The research team includes Kousik; \u003Ca href=\u0022https:\/\/research.gatech.edu\/people\/benjamin-joffe\u0022\u003EBenjamin Joffe\u003C\/a\u003E, senior research scientist at the Georgia Tech Research Institute; and \u003Ca href=\u0022https:\/\/people.research.gatech.edu\/node\/17511\u0022\u003EDanfei Xu\u003C\/a\u003E, assistant professor in the School of Interactive Computing, along with graduate students and researchers from multiple labs.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003ESpeed Without Sacrifice\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003ETeaching robots to work faster than the speed of human demonstrations is challenging. Robots can behave differently at higher speeds, and small changes in the environment can cause errors.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cThe challenge is that a robot is limited to the data it was trained on, and any changes in the environment can cause it to fail,\u201d Kousik said.\u003C\/p\u003E\u003Cp\u003ESAIL addresses this challenge through a modular approach, with separate components working together to accelerate beyond the training data. The system keeps motions smooth at high speed, tracks movements accurately, adjusts speed dynamically based on task complexity, and schedules actions to account for hardware delays. This combination allows robots to move quickly while staying stable, coordinated, and precise.\u003C\/p\u003E\u003Cp\u003E\u201cOne of the gaps we saw was that our academic robotics systems could do impressive things, but they weren\u2019t fast or robust enough for practical use,\u201d Joffe said. \u201cWe wanted to study that gap carefully and design a system that addressed it end to end.\u201d\u003C\/p\u003E\u003Cp\u003EHe added, \u201cThe goal is not just to make robots faster, but to make them smart enough to know when speed helps and when it could cause mistakes.\u201d\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe team evaluated SAIL\u2019s performance across 12 tasks, both in simulation and on two physical robot platforms. Tasks included stacking cups, folding cloth, plating fruit, packing food items, and wiping a whiteboard. In most cases, SAIL-enabled robots completed tasks three to four times faster than standard imitation-learning systems without losing accuracy.\u003C\/p\u003E\u003Cp\u003EOne exception was the whiteboard-wiping task, where maintaining contact made high-speed execution difficult.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u201cUnderstanding where speed helps and where it hurts is critical,\u201d Kousik said. \u201cSometimes slowing down is the right decision.\u201d\u003C\/p\u003E\u003Cp\u003EWhile SAIL does not make robots universally adaptable on its own, it represents an important step toward robotic systems that can learn from humans without being constrained by human pace.\u003C\/p\u003E\u003Cp\u003EBy showing how learned robotic behaviors can be accelerated safely and systematically, SAIL brings imitation learning closer to real-world use \u2014 where speed, precision, and reliability all matter.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ECitation: Ranawaka Arachchige, et. al. \u201cSAIL: Faster-than-Demonstration Execution of Imitation Learning Policies,\u201d Conference on Robot Learning (CoRL), 2025.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDOI: \u003Ca href=\u0022https:\/\/doi.org\/10.48550\/arXiv.2506.11948\u0022\u003Ehttps:\/\/doi.org\/10.48550\/arXiv.2506.11948\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003EFunding: The authors would like to acknowledge the State of Georgia and the Agricultural Technology Research Program at Georgia Tech for supporting the work described in this paper.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ENew AI system lets robots work faster than their human teachers without sacrificing accuracy.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"New AI system lets robots work faster than their human teachers without sacrificing accuracy."}],"uid":"36123","created_gmt":"2026-03-19 15:38:45","changed_gmt":"2026-04-02 17:45:33","author":"Catherine Barzler","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-03-19T00:00:00-04:00","iso_date":"2026-03-19T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679690":{"id":"679690","type":"image","title":"robot-med.png","body":"\u003Cp\u003EPancake-flipping robots could be just around the corner thanks to a new robot learning system from Georgia Tech. (Credit: Adobe Stock)\u003C\/p\u003E","created":"1773934781","gmt_created":"2026-03-19 15:39:41","changed":"1773937931","gmt_changed":"2026-03-19 16:32:11","alt":"A white humanoid robot holds a blue pan while standing in a kitchen with a green backsplash","file":{"fid":"263881","name":"robot-med.png","image_path":"\/sites\/default\/files\/2026\/03\/19\/robot-med.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/03\/19\/robot-med.png","mime":"image\/png","size":2989840,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/03\/19\/robot-med.png?itok=2EUbFZa1"}},"679687":{"id":"679687","type":"video","title":" SAIL System Brings Us Closer to General-Purpose Robots","body":null,"created":"1773933476","gmt_created":"2026-03-19 15:17:56","changed":"1773933476","gmt_changed":"2026-03-19 15:17:56","video":{"youtube_id":"c1MbisHP75w","video_url":"https:\/\/youtu.be\/c1MbisHP75w"}}},"media_ids":["679690","679687"],"groups":[{"id":"1188","name":"Research Horizons"}],"categories":[],"keywords":[{"id":"187915","name":"go-researchnews"}],"core_research_areas":[{"id":"193655","name":"Artificial Intelligence at Georgia Tech"},{"id":"193653","name":"Georgia Tech Research Institute"},{"id":"193652","name":"Matter and Systems"},{"id":"39521","name":"Robotics"}],"news_room_topics":[{"id":"71881","name":"Science and Technology"}],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003ECatherine Barzler, Senior Research Writer\/Editor\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022mailto:catherine.barzler@gatech.edu\u0022\u003Ecatherine.barzler@gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":["catherine.barzler@gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}