Robots Learning In Realistic Digital Worlds
Robots can now learn to pick, stack, and organize things inside digital rooms, practicing safely and faster, without needing real-world training every time.
Robots may soon learn like people, by practicing in digital worlds rather than physical spaces. Unlike chatbots, such as ChatGPT or Claude, which improve by processing large amounts of text, robots face a different challenge, requiring movement through spaces, handling objects, and completing tasks.
Collecting motion data from real robots is slow, costly, and hard to reproduce, while virtual training often looks unrealistic. Researchers at MIT and the Toyota Research Institute have developed steerable scene generation to address this problem.
Virtual training often looks unrealistic, with objects floating or intersecting.
Without accurate environments, robots cannot learn safely or effectively.
Author's summary: Robots learn in digital worlds.