In-Context Robot Learning with VLM Agents

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