Real time hand movement controlled robotic arm for risk prevention

Abstract

In this paper, we propose an “Artificial Human Hand Model” which can precisely follow the real movements of human hand by means of image processing thereby avoiding sensor noise and damage and providing more adjustable response. Webcams are used to capture the hand images followed by Morphological image processing to extract information from human hand movement. The five degrees of freedom implemented in the proposed method are rotation of base, arm like motions, elbow like motions, grip motions, and rotation of grip. The robot hand is controlled successfully using human hand movement, where the system can pick up, manipulate and move objects from one place to other with precision. The user can control the hand entirely based on his/her intentions to accomplish the required task. Our proposed real-time method of implementing human hand movement also ensures instantaneous control and performance. Distant control of the robotic hand not only ensures complete safety to human, but also allows flexibility in controlling distant objects. Overall, our proposed system can guarantee safety, flexibility and accuracy in performing sensitive tasks in day-to-day life thus offering suitability for risk prevention.