RoboKnight is a low-cost, modular robotic chess coach designed to promote interactive, fun, and personalized chess learning for players of all skill levels. The system blends robotic manipulation, computer vision, and advanced chess engine logic—wrapped in a user-friendly educational web dashboard—to offer real-time coaching and analysis.
This organization hosts the core repositories powering the RoboKnight ecosystem:
RoboKnight is composed of four interconnected modules:
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Arduino-Controlled Robotic Arm Controls a 4-DOF robotic arm to perform physical piece movements. Repository:
arduino-code -
Computer Vision Module Uses YOLO-based detection and FEN encoding to detect the board and moves in real time. Repository:
computer-vision -
Teacher Dashboard – Backend Handles user management, move tracking, and chess engine integration for personalized tutoring. Repository:
TeacherDashboard-Backend -
Teacher Dashboard – Frontend A clean web-based interface to visualize moves, game statistics, and player progress. Repository:
TeacherDashboard-Frontend
Unlike traditional robotic chess systems, RoboKnight emphasizes teaching over just playing:
- Real-time gameplay feedback via a web dashboard
- Skill-adaptive move suggestions
- Game mode selection and difficulty control
- Designed for classroom deployment: portable, affordable, and scalable
- Vision-guided move detection with real-world chessboards (no special pieces)
- Modular and scalable Raspberry Pi–Arduino architecture
- Web-based performance analytics
- Low power consumption (battery or AC-DC)
- Designed for students, schools, and robotics/AI enthusiasts
- Early Prototype Video: Watch here
Developed by students at INSAT Tunisia, with support from the IEEE INSAT Student Branch and the IEEE SMC Tunisia Chapter.
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