Zing Forum

Reading

NAO Social Robot Project: Graduation Design Practice on Multimodal Human-Robot Interaction

This is an intelligent interaction system developed based on the SoftBank NAO humanoid robot platform, integrating computer vision, speech recognition, and the ChatGPT large language model. It realizes three core functions: face recognition, natural dialogue, and autonomous dancing, with behavior control implemented using a Finite State Machine (FSM) architecture.

NAO 机器人ChatGPT人机交互多模态有限状态机计算机视觉语音识别大语言模型情感计算机器人开发
Published 2026-05-19 09:42Recent activity 2026-05-19 09:53Estimated read 7 min
NAO Social Robot Project: Graduation Design Practice on Multimodal Human-Robot Interaction
1

Section 01

NAO Social Robot Project Introduction

This project is an intelligent interaction system developed based on the SoftBank NAO humanoid robot platform, integrating computer vision, speech recognition, and the ChatGPT large language model. It realizes three core functions: face recognition, natural dialogue, and autonomous dancing, with behavior control using a Finite State Machine (FSM) architecture. It is a graduation design practice on multimodal human-robot interaction.

2

Section 02

Project Background: Exploration of Socialization in Humanoid Robots

In the field of human-robot interaction, traditional rule-based or pre-scripted interaction methods are rigid and lack flexibility. With the maturity of large language models (LLMs), embedding AI dialogue capabilities into physical robots has become possible. NAO is a classic humanoid robot platform developed by SoftBank Robotics, equipped with rich sensors, flexible movement capabilities, and a mature development framework. As a graduation design, this project explores combining ChatGPT's intelligent dialogue capabilities with NAO's physical interaction capabilities to create a robot system with social attributes.

3

Section 03

System Architecture and Technical Methods

System Architecture

Adopting a Finite State Machine (FSM) architecture, three core behavior states are defined:

  • Idle State: Real-time face detection, user identity recognition, new user registration, voice command monitoring
  • Dialogue State: Speech-to-text conversion, ChatGPT response generation, speech synthesis output, context memory
  • Dance State: Music detection, dance choreography execution, smooth transition

Technology Stack

  • Core Platform: NAOqi SDK, Python, OpenCV
  • Perception & Interaction: Google Speech API/Offline Speech Recognition, Audio Processing, Face Detection & Recognition
  • Intelligent Core: OpenAI API, Finite State Machine Design Pattern

State Machine Design

Advantages: Clear state boundaries, simple transition logic, easy to debug and extend; Trigger events include voice commands (Hey NAO/Dance NAO, etc.), face recognition events, and audio detection.

4

Section 04

Function Implementation and Verification

System Workflow

  1. Start and enter the idle state
  2. Environment scanning (face detection, greeting/inviting registration)
  3. Monitor commands:
    • Hear "Hey NAO" → Dialogue state
    • Hear "Dance NAO" → Dance state
  4. Exit conditions: Saying "Goodbye" during dialogue / Saying "Stop NAO" during dance returns to idle state

Verification & Highlights

  • Video demonstration provided (link in README)
  • Technical highlights: Multimodal fusion (visual/auditory/language), LLM physicalization (ChatGPT empowers natural dialogue), preliminary exploration of emotion computing (dance expresses emotions)
5

Section 05

Team Collaboration and Division of Labor

Development team division:

  • Computer Vision Integration: Face detection, recognition, and user management modules
  • Robot Behavior Programming: NAOqi framework calls and action choreography
  • ChatGPT Dialogue System Design: OpenAI API integration and dialogue flow design
  • Audio Processing & State Control: Music detection and state machine implementation

Team members: David Shi, Ousama Alabdullah, Humaira Saddat

6

Section 06

Limitations and Improvement Directions

Limitations of the system and improvement suggestions:

  • Offline Capability: Relies on OpenAI API; dialogue function unavailable offline
  • Multilingual Support: Chinese-English switching is not intelligent enough
  • Dance Diversity: Only preset sequences; real-time choreography can be added
  • Emotion Recognition: Currently only able to express emotions, cannot recognize user emotions
7

Section 07

Summary and Insights

Summary

This project is an excellent graduation design work, demonstrating the combination of cutting-edge AI technology and a mature robot platform. It realizes the orderly coordination of three functions through the FSM architecture, providing a reference example for robot development and human-robot interaction learning.

Insights

  • State machines are an effective model for robot behavior management
  • LLMs transform robots from "executors" to "dialoguers"
  • Multimodality is the inevitable path to natural human-robot interaction