Gesture Control

Gesture control aims to create intuitive human-robot interfaces by translating human movements into robot commands, eliminating the need for cumbersome controllers. Current research focuses on developing robust and efficient algorithms, often employing deep learning models like convolutional neural networks, to accurately recognize a range of hand and body gestures in real-time, even for complex 3D robot control. This field is significant because it promises more natural and engaging interactions with robots across diverse applications, from industrial automation to assistive technologies, improving both task efficiency and user experience. Ergonomic considerations, such as reducing user fatigue through passive support systems, are also gaining importance.