Hand Gesture Control Robo Car using Machine Learning

This project presents a gesture-controlled robotic car aimed at improving human-robot interaction by utilizing intuitive control methods. The system achieves a gesture recognition accuracy of up to 90% even with slightest change in lightening and up to a certain distance of 5 feet, enabling reliable real-time interpretation of hand movements. Unlike existing systems, this implementation integrates a robotic arm, extending the car's functionality for practical tasks such as object manipulation. Leveraging advanced image processing techniques and a machine learning model, the project translates user gestures into motion commands with minimal latency. Wireless communication, facilitated by a Bluetooth module, ensures seamless control, allowing users to operate the robotic car both indoors and outdoors. This project aims to use gestures to control the robotic technology and incorporates what is needed in the industry of human-robot interaction and development of their applications.