<p>Software plays a crucial role in robot control systems, and its efficient, flexible development is essential for production. Such software must be customized to specific production processes, requiring developers with specialized expertise in these areas—the high development threshold results in reduced efficiency and increased costs. Recently, significant progress has been made in automated problem-solving through societies of agents based on large language models (LLMs). To automate software development for industrial robot control systems, this paper introduces an Industrial Robot Control Software Auto-Development (IRCSAD) framework with multi-agent collaboration, and a Low-code Industrial Software Platform (LISP) for validating IRCSAD-developed software. IRCSAD automates software development and iterative optimization of prompts through the collaboration of multiple LLM-based agents. This work also proposes a software testing methodology for robot control systems based on reliability assessment. An experimental study that develops software for the robot control system for assembly, sorting, and inspection tasks is implemented. The results show that collaboration with LISP enhances IRCSAD's ability to solve complex problems in the development process, saves development costs, and improves development efficiency.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Collaborative LLM agents for flexible software development of intelligent industrial robot control systems

  • Kezhou Chen,
  • Tao Wang,
  • Mingzhe Ni,
  • Lianglun Cheng,
  • Zhuowei Wang,
  • Chong Chen

摘要

Software plays a crucial role in robot control systems, and its efficient, flexible development is essential for production. Such software must be customized to specific production processes, requiring developers with specialized expertise in these areas—the high development threshold results in reduced efficiency and increased costs. Recently, significant progress has been made in automated problem-solving through societies of agents based on large language models (LLMs). To automate software development for industrial robot control systems, this paper introduces an Industrial Robot Control Software Auto-Development (IRCSAD) framework with multi-agent collaboration, and a Low-code Industrial Software Platform (LISP) for validating IRCSAD-developed software. IRCSAD automates software development and iterative optimization of prompts through the collaboration of multiple LLM-based agents. This work also proposes a software testing methodology for robot control systems based on reliability assessment. An experimental study that develops software for the robot control system for assembly, sorting, and inspection tasks is implemented. The results show that collaboration with LISP enhances IRCSAD's ability to solve complex problems in the development process, saves development costs, and improves development efficiency.