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.

通过创新的自动协作框架，借鉴实际机器人开发者的经验，利用多个大型语言模型在分析、编程和测试等不同角色中合作，深入挖掘用户需求、生成精确代码，并根据用户反馈调整参数以实现复杂的机器人开发任务，无需专业知识，仅依靠非专家参与。