Scalable Task Planning via Large Language Models and Structured World Representations
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910823656456192 |
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| author | Pérez-Dattari, Rodrigo Li, Zhaoting Babuška, Robert Kober, Jens Della Santina, Cosimo |
| author_facet | Pérez-Dattari, Rodrigo Li, Zhaoting Babuška, Robert Kober, Jens Della Santina, Cosimo |
| contents | Planning methods struggle with computational intractability in solving task-level problems in large-scale environments. This work explores leveraging the commonsense knowledge encoded in LLMs to empower planning techniques to deal with these complex scenarios. We achieve this by efficiently using LLMs to prune irrelevant components from the planning problem's state space, substantially simplifying its complexity. We demonstrate the efficacy of this system through extensive experiments within a household simulation environment, alongside real-world validation using a 7-DoF manipulator (video https://youtu.be/6ro2UOtOQS4). |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2409_04775 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Scalable Task Planning via Large Language Models and Structured World Representations Pérez-Dattari, Rodrigo Li, Zhaoting Babuška, Robert Kober, Jens Della Santina, Cosimo Robotics Artificial Intelligence Planning methods struggle with computational intractability in solving task-level problems in large-scale environments. This work explores leveraging the commonsense knowledge encoded in LLMs to empower planning techniques to deal with these complex scenarios. We achieve this by efficiently using LLMs to prune irrelevant components from the planning problem's state space, substantially simplifying its complexity. We demonstrate the efficacy of this system through extensive experiments within a household simulation environment, alongside real-world validation using a 7-DoF manipulator (video https://youtu.be/6ro2UOtOQS4). |
| title | Scalable Task Planning via Large Language Models and Structured World Representations |
| topic | Robotics Artificial Intelligence |
| url | https://arxiv.org/abs/2409.04775 |