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Talk Through It: End User Directed Manipulation Learning
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2026-02-17 10:33:12
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Talk Through It Talk Through It: End User Directed Manipulation Learning Carl Winge, Adam Imdieke, Bahaa Aldeeb, Dongyeop Kang, Karthik Desingh University of Minnesota Published in IEEE Robotics and Automation Letters IEEE ArXiv Video Code Talk Through It is a robot learning framework that enables end users to teach robots skills and tasks with natural language instructions. Abstract Training generalist robot agents is an immensely difficult feat due to the requirement to perform a huge range of tasks in many different environments. We propose selectively training robots based on end-user preferences instead. Given a factory model that lets an end user instruct a robot to perform lower-level actions (e.g. ‘Move left’), we show that end users can collect demonstrations using language to train their home model for higher-level tasks specific to their needs ...
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