Human-System Interaction Interface Utilizing 3D Gesture Recognition Techniques based on Wearable Technology

Abstract

Working with robots has the risk of safety and security of human interaction that limits the robots fine motion within a factory floor. Thus, it requires the improving human system interaction interface in a robotic assembly line. Gesture recognition can be used as an assistive tool to reduce the interaction complexities associated during human intervention with robots and machines. The aim of this research is to recognize 3D gesture using wearable devices in order to improve human-robot/machine collaboration through better interaction interface. The derived systems consist of Data Classification, Recognition, and interaction. The novel system proposed improves human-machine interaction interface and reduces the system complexity through improving the interaction system leading to better working environment. The recognition of gestures helps to improve the interaction between humans and robots and helps in performing different robotic tasks. The method proposed in this research proves better performance compared to the currently existing gesture recognition methods. The data for gesture recognition is taken using different wearable devices, pressure and motion sensors. Reducing the interaction complexity will help to provide better working environment and gives assurance to worker about their security and safety with better working environment