<img src="https://robohub.org/wp-content/uploads/2018/04/bed_making_gif.jpg "  /><br>
In this episode, Audrow Nash speaks with Michael Laskey, PhD student at UC Berkeley, about a method for robust imitation learning, called DART. Laskey discusses how DART relates to previous imitation learning methods, how this approach has been used for folding bed sheets, and on the importance of robotics leveraging theory in other disciplines.

In this episode, Audrow Nash speaks with Michael Laskey, PhD student at UC Berkeley, about a method for robust imitation learning, called DART. Laskey discusses how DART relates to previous imitation learning methods, how this approach has been used for folding bed sheets, and on the importance of robotics leveraging theory in other disciplines.

<br>
In this episode, Audrow Nash speaks with Michael Laskey, PhD student at UC Berkeley, about a method for robust imitation learning, called DART. Laskey&nbsp;discusses how DART relates to previous imitation learning methods, how this approach has been used for folding bed sheets, and on the importance of robotics leveraging theory in other disciplines.

ep.258: DART: Noise injection for robust imitation learning, with  Michael Laskey

News and views on current and future trends in robot technology and artificial intelligence.

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ep.258: DART: Noise injection for robust imitation learning, with Michael Laskey

ep.258: DART: Noise injection for robust imitation learning, with Michael Laskey