Core Concepts
PhysicsAssistant integrates LLM and YOLOv8 for real-time physics lab assistance.
Abstract
Introduction
Challenges in K-12 physics education.
Importance of interactive robots in education.
Robot System
PhysicsAssistant overview.
User study with 8th-grade students.
LLM Capabilities
LLM limitations in visual data processing.
Integration of YOLOv8 for visual understanding.
System Architecture
Speech-to-text encoding.
Image processing with YOLOv8.
Prompt designing for LLM.
Response Generation
LLM-generated responses.
Response validation for accuracy.
Efficiency
Comparison of response times with GPT-4.
Experimental Analysis
Setup and evaluation criteria.
Expert ratings on knowledge dimensions.
Results
Performance comparison between PhysicsAssistant and GPT-4.
Efficiency in response time.
Discussion
System's strengths and areas for improvement.
Conclusion
Potential of PhysicsAssistant in educational robotics.
Stats
"PhysicsAssistant provides prompt responses with comparable quality to GPT-4."
"Response time of PhysicsAssistant is significantly faster than GPT-4."