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SUMMARY:Spring 2022 GRASP SFI: Youngwoon Lee\, University of Southern California\, “Scaling Robot Learning with Skills: Towards Furniture Assembly and Beyond”
DESCRIPTION:Despite the recent progress in robot learning\, robotics research and benchmarks today are typically confined to simple short-horizon tasks. However\, tasks in our daily lives are much more complicated — consisting of multiple sub-tasks and requiring high dexterity skills — and the typical “learning from scratch” scheme is hardly scale to such complex long-horizon tasks. \nIn this talk\, I propose to extend the range of tasks that robots can learn by acquiring a useful skillset and efficiently harnessing these skills. As a first step\, I will introduce a novel benchmark for complex long-horizon manipulation tasks\, IKEA furniture assembly environment. Then\, I will present skill chaining approaches that enable sequential skill composition to perform long-horizon tasks. Finally\, I will talk about how to learn a long-horizon task efficiently using skills and skill priors extracted from diverse data.
URL:https://seasevents.nmsdev7.com/event/spring-2022-grasp-sfi-youngwoon-lee-university-of-southern-california-scaling-robot-learning-with-skills-towards-furniture-assembly-and-beyond/
LOCATION:Levine 512
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
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