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Bridging the Sim2real Gap in Robotics with Marius Memmel - #695

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

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Bridging Simulation and Reality in Robotics

This chapter explores the challenges of applying traditional robotics models in unpredictable real-world environments, emphasizing the significance of effective simulations for data collection. It introduces the Sim2Real concept, detailing how accurate simulations can minimize manual adjustments and optimize robotic learning for complex tasks. The discussion also highlights methods like domain randomization and the ACID framework to facilitate the transfer of knowledge from simulated to real-world applications.

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