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Data-Driven Fine Manipulation: Pushing Boundaries in Robotic Precision

Offered By: Montreal Robotics via YouTube

Tags

Robotics Courses Reinforcement Learning Courses Self-supervised Learning Courses Imitation Learning Courses

Course Description

Overview

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Explore cutting-edge advancements in robotic fine manipulation through this insightful 58-minute conference talk by Liyiming Ke, a PhD candidate at the University of Washington. Delve into innovative data-driven solutions for tasks such as precise grasping, cutting, and assisted feeding, applicable in fields ranging from surgery to disaster recovery. Learn how Ke's research leverages imitation and reinforcement learning to enable even low-cost hardware to perform intricate manipulations with superhuman responsiveness. Discover the unique chopstick-wielding robot testbed developed to push the boundaries of manipulator capabilities. Gain valuable insights into the integration of theoretical understanding with practical robotic system applications, and witness how just 30 minutes of real-world data training resulted in nearly 100% success in grasping tiny moving balls mid-air. Access accompanying videos to visualize these groundbreaking achievements in robotic precision.

Syllabus

Liyiming Ke: Data-Driven Fine Manipulation: Pushing Boundaries in Robotic Precision


Taught by

Montreal Robotics

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