Bridging the Sim2real Gap in Robotics with Marius Memmel - #695
2024-07-30 · 57 min · episode 695 · 13 entities
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→ appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
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Bridging the Sim2real Gap in Robotics with Marius Memmel - #695
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Bridging the Sim2real Gap in Robotics with Marius Memmel - #695
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Feed author/publisher: Sam Charrington
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Feed author/publisher: Sam Charrington
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appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Bridging the Sim2real Gap in Robotics with Marius Memmel - #695
Episode description as stored
Today, we're joined by Marius Memmel, a PhD student at the University of Washington, to discuss his research on sim-to-real transfer approaches for developing autonomous robotic agents in unstructured environments. Our conversation focuses on his recent ASID and URDFormer papers. We explore the complexities presented by real-world settings like a cluttered kitchen, data acquisition challenges for training robust models, the importance of simulation, and the challenge of bridging the sim2real gap in robotics. Marius introduces ASID, a framework designed to enable robots to autonomously generate and refine simulation models to improve sim-to-real transfer. We discuss the role of Fisher information as a metric for trajectory sensitivity to physical parameters and the importance of exploration and exploitation phases in robot learning. Additionally, we cover URDFormer, a transformer-based model that generates URDF documents for scene and object reconstruction to create realistic simulation environments.
The complete show notes for this episode can be found at https://twimlai.com/go/695.