Robots are becoming increasingly common in our daily lives, from automated vacuum cleaners to drones delivering packages.
As technology advances, they are starting to do tasks that were once limited to humans, such as picking a cherry from a tree.
It is an extremely challenging task for robots due to perception errors, sensor noise, and the dynamic nature of the problem.
CherryBot is a system designed to address this challenge by pre-training in an approximate simulation and then fine-tuning with model-free RL in the real world.
It is generic enough to handle dynamic environments and objects of different sizes, shapes, and textures without requiring specific hardware.
It uses an assembled robot arm and chopsticks, and after only 30 minutes of interaction in the real world, it can demonstrate superhuman reactiveness on dynamic, high-precision tasks.
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