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.

翻译：尽管大型语言模型（LLMs）在代码生成方面展现出卓越能力，但在处理复杂任务时仍面临挑战。机器人开发作为高度复杂的领域，本质上需要人类参与任务分配与团队协作。为优化机器人开发流程，我们提出一种受真实机器人开发者启发的创新性自动化协作框架。该框架部署多个LLMs扮演差异化角色——分析师、程序员与测试员。分析师深入剖析用户需求，使程序员能生成精准代码；测试员则根据用户反馈微调参数以适配实际机器人应用。每个LLM在开发过程中承担多样化的关键任务，明确的协作规则模拟了真实世界中LLM之间的团队协作。分析师、程序员与测试员形成紧密团队，统筹策略制定、代码编写与参数调整。通过该框架，无需专业知识储备，仅凭借非专家参与即可实现复杂机器人开发。