Acceptance over Ignorance - How to Embrace Uncertainty in Robotic Manipulation
Paul G. Allen School via YouTube
Learn Backend Development Part-Time, Online
Learn AI, Data Science & Business — Earn Certificates That Get You Hired
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Explore a thought-provoking lecture on embracing uncertainty in robotic manipulation presented by Stanford University's Jeannette Bohg at the Winter 2020 Robotics Colloquium. Delve into three innovative approaches that tackle the challenges of uncertainty in robotics: scaffolding robot learning through optimal fixture placement, object-centric task and motion planning, and model-predictive control for deformable object manipulation. Gain insights into why human manipulation skills are difficult to replicate in robots and how accepting inherent uncertainty can lead to more robust robotic systems. Learn about Bohg's distinguished career and her contributions to the field of autonomous robotic manipulation and grasping.
Syllabus
Winter 2020 Robotics Colloquium: Jeannette Bohg (Stanford University)
Taught by
Paul G. Allen School