Sign Language-Controlled Robot: A Simple and Time-Efficient Approach to Human-Machine Interaction

Machine learning has played an important role in sign language recognition over the past decade. However, many existing systems are complex, require extensive computational power, and lack precision in real-time use.This project aims to develop a simple and time-efficient sign language-controlled robot that interprets static American Sign Language (ASL) gestures to perform movement-based tasks. Built with a Raspberry Pi, the robot will communicate with a nearby laptop to detect and classify signs in real time. Building on prior research, this project will use innovative computer vision techniques for static sign recognition. It will focus on improving static sign detection accuracy while minimizing latency, enhancing overall system responsiveness.The study highlights the potential of sign language for human-machine interaction, with broader applications in accessibility and inclusion.