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Using AI to Help Robots Plan Tasks and Handle Unexpected Situations

Paper Authors:

Yan Ding,

Xiaohan Zhang,

Saeid Amiri,

Nieqing Cao,

Hao Yang,

Andy Kaminski,

Chad Esselink,

Shiqi Zhang

Bullets

Key Details

Proposes COWP, a framework integrating classical planning and LLMs for open-world task planning

Enables robots to handle unforeseen situations by augmenting action knowledge with common sense

Evaluated on a dataset of 1,085 real-world situations across 12 tasks

Outperformed baselines on task completion rate and situation handling

Demonstrated on a mobile manipulator performing delivery tasks

AI generated summary

Using AI to Help Robots Plan Tasks and Handle Unexpected Situations

This paper proposes a framework to enable robots to generate plans for long-horizon tasks and adapt when unexpected situations arise during execution. It integrates classical AI planning with large language models to leverage both structured action knowledge and flexible commonsense reasoning.

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