We integrate perception and task planning under belief-space planning to enable strategic information gathering in open-world environments, where vision-language foundation models are used to estimate the state and its uncertainty.
We enable a robot to rapidly and autonomously specialize parameterized skills by planning to practice them. The robot decides what skills to practice and how to practice them. The robot is left alone for hours, repeatedly practicing and improving.