Public Phd Defense - Reinforcement Learning For Real-World Robots

Public PhD defense - Reinforcement Learning for Real-World Robots

Denis Steckelmacher

Provably Safe Learning-Based Robot Control (Alec Farid, PhD Defense)

Intelligent Robot Motion Lab

Learning Robot Control: From RL to Differential Simulation - (PhD Defense of Yunlong Song)

UZH Robotics and Perception Group

Real-World Humanoid Locomotion with Reinforcement Learning

Hybrid Robotics

Collective Robot Reinforcement Learning, Human Demonstration

PhD Thesis Defense: Michael Everett

AerospaceControlsLab

Deep Reinforcement Learning Based Robot Arm Manipulation – Real-world Experiment

Control Lab KAIST

RealAnt robot takes reinforcement learning to the real world

Aalto University

Setting up a Reinforcement Learning Task with a Real-World Robot

Real World Reinforcement Learning with the Thing

UTIAS STARS Laboratory

Real-World Human-Robot Collaborative Reinforcement Learning

Yu-Chi Lin: PhD Defense

Benchmarking Reinforcement Learning Algorithms on Real-World Robots

Collective Robot Reinforcement Learning, Training Phase

Deep Reinforcement Learning in the Real World -Sergey Levine

Institute for Advanced Study

Brian Bittner: PhD Defense

Lu Gan: PhD Defense

Virtual PhD Defense of Steven Jens Jorgensen

UT Human Centered Robotics Lab

Zheming Zhou: PhD Defense