Automatic Robotic Development through Collaborative Framework by Large
Language Models
- URL: http://arxiv.org/abs/2402.03699v2
- Date: Fri, 16 Feb 2024 12:46:03 GMT
- Title: Automatic Robotic Development through Collaborative Framework by Large
Language Models
- Authors: Zhirong Luan and Yujun Lai, Rundong Huang, Xiaruiqi Lan, Liangjun
Chen, Badong Chen
- Abstract summary: We propose an innovative automated collaboration framework inspired by real-world robot developers.
This framework employs multiple LLMs in distinct roles analysts, programmers, and testers.
Analysts delve deep into user requirements, enabling programmers to produce precise code, while testers fine-tune the parameters.
- Score: 13.957351735394683
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Despite the remarkable code generation abilities of large language models
LLMs, they still face challenges in complex task handling. Robot development, a
highly intricate field, inherently demands human involvement in task allocation
and collaborative teamwork . To enhance robot development, we propose an
innovative automated collaboration framework inspired by real-world robot
developers. This framework employs multiple LLMs in distinct roles analysts,
programmers, and testers. Analysts delve deep into user requirements, enabling
programmers to produce precise code, while testers fine-tune the parameters
based on user feedback for practical robot application. Each LLM tackles
diverse, critical tasks within the development process. Clear collaboration
rules emulate real world teamwork among LLMs. Analysts, programmers, and
testers form a cohesive team overseeing strategy, code, and parameter
adjustments . Through this framework, we achieve complex robot development
without requiring specialized knowledge, relying solely on non experts
participation.
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