ChatBuilder: LLM-assisted Modular Robot Creation

Modular robotic structures simplify robot design and manufacturing by using standardized modules, enhancing flexibility and adaptability. However, the need for manual input in design and assembly limit their potential. Current methods to automate this process still require significant human effort and technical expertise. This paper introduces a novel approach that employs Large Language Models (LLMs) as intelligent agents to automate the creation of modular robotic structures. We decompose the modular robot creation task and develop two agents based on LLM to plan and assemble the modular robots from text prompts. By inputting a textual description, users can generate robot designs that are validated in both simulated and real-world environments. This method reduces the need for manual intervention and lowers the technical barrier to creating complex robotic systems.

Authors

• Xin Chen
• Xifeng Gao
• Lifeng Zhu
• Aiguo Song
• Zherong Pan

Keywords

• Energy consumption
• Generative AI
• Large language models
• Robot control
• Manuals
• Intelligent agents
• Robots
• Intelligent robots
• Assembly
• Modular Robots
• Multi-agent
• Robotic System
• Intelligence Agencies
• Textual Descriptions
• Modular Structure
• Real-world Environments
• Robot Design
• Standard Module
• Robot Structure
• Design Process
• Specific Tasks
• Number Of Results
• 3D Printing
• Graphical User Interface
• Task Design
• Design Requirements
• Design Space
• Robotic Arm
• Mobile Robot
• Modular Design
• Modular Components
• Input Text
• End-effector
• Design Capabilities
• Range Of Requirements