Generative Task Network:New Paradigm for Autonomic Task Planning and Execution Based on LLM
Year: 2025
Type: article
Abstract: Owing to the development of generative artificial intelligence,the intelligent planning technology of unmanned systems is set to undergo a new transformation.This paper first analyzes the shortcomings of traditional intelligent task planning paradigms in terms of generalization,transferability and coherence.In response,it proposes a new paradigm for task planning and execution based on large language models,namely generative task network.This method enables unmanned systems to autonomously discover tasks,intelligently plan,and automatically execute them,forming a closed-loop from problem to solution.It also endows the task planning process of unmanned systems with the advantages of generalization and ease of transfer.This paper then introduces the concept of the generative task network,defines its key elements and models its process,and subsequently designs a ge-neral application architecture.Finally,an application analysis is conducted taking the aviation materials warehouse of N Airlines as the scenario,effectively enhancing the intelligence and automation levels of unmanned systems in warehouse management.
Author: HUANG Xueqin, ZHANG Sheng, ZHU Xianqiang, ZHANG Qianzhen, ZHU Cheng
Institution: National University of Defense Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7084121759
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