# Animesh Garg

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Teaching Bots Learn by Watching Human Behavior - Ep. 67

Robots following coded instructions to complete a task? Old school. Robots learning to do things by watching how humans do it? That’s the future. Earlier this year, Stanford’s Animesh Garg and Marynel Vázquez shared their research in a talk on “Generalizable Autonomy for Robotic Mobility and Manipu…

Antonin Raffin and Ashley Hill

Antonin Raffin is a researcher at the German Aerospace Center (DLR) in Munich, working in the Institute of Robotics and Mechatronics. His research is on using machine learning for controlling real robots (because simulation is not enough), with a particular interest for reinforcement learning.  Ash…

Episode 24: Way With Words; Armina Mussa, Artist & Creative Director of Saint Heron; Mind: Creativity in the City

This month, we kick off the new year with an exploration of language in our feature, "Way With Words". How do we preserve our most endangered languages? How does a dialect become a language? Do labels like "Womxn", "LGBTQIA", "people of color" and "Latinx" empower or hold people back? What happens …

SPIRE: Synergistic Planning, Imitation, and Reinforcement Learning for Long-Horizon Manipulation

[00:00] Introduction [00:20] Core limitations in robot manipulation: challenges with RL and IL [01:08] SPIRE's hybrid approach: combining task planning with learning methods [01:44] TAMP-gated learning: selective application of learned policies [02:20] Training innovations: warm-starting RL and…

Ep 95 | The Hard Part Is Not Training Robots. It Is Making Them Generalize (w/ Animesh Garg)

I talk with Animesh Garg,Assistant Professor at Georgia Tech and one of the leading voices in robot learning today: We talk about growing up in India, building his first autonomous vehicle on a $280 budget after being rejected from a CMU program, and how that failure pushed him toward Berkeley, Sta…

Ep#105: Beyond Imitation: Self-Improving Robot Policies via Off-Policy Q-Planning

Imitation learning, especially with interventions, has driven so much recent robotics progress. However, improving a policy via targeted interventions until it reaches a useful and deployable success rate is a time and labor intensive process. Instead, wouldn’t it be great if policies could improve…