Researchers are pursuing in-context robot learning with vision-language model (VLM) agents to let robots adapt to unfamiliar environments, according to a report on the work. The approach aims to address the limitation that no finite collection of demonstrations can cover every task and situation a robot will encounter, making learning from context at deployment essential for generalization.
Enabling robots to adapt to unfamiliar environments as readily as humans remains a moonshot goal of embodied AI. No finite collection of demonstrations can cover every task and situation a robot will encounter, making the ability to learn from context at deployment essential for generalization. Such
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