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Designs of Human–robot Interaction Using Depth Sensor-based Hand Gesture Communication for Smart Material-handling Robot Operations by Ing-Jr Ding; Jun-Lin Su is a Engineering article available to read on EtoBox.

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With rapid developments in biometric recognition, a great deal of attention is being paid to robots which interact smartly with humans and communicate certain types of biometrical information. Such human–machine interaction (HMI), also well-known as human–robot interaction (HRI), will, in the future, prove an important development when it comes to automotive manufacturing applications. Currently, hand gesture recognition-based HRI designs are being practically used in various areas of automotive manufacturing, assembly lines, supply chains, and collaborative inspection. However, very few studies are focused on material-handling robot interactions combined with hand gesture communication of the operator. The current work develops a depth sensor-based dynamic hand gesture recognition scheme for continuous-time operations with material-handling robots. The proposed approach properly employs the Kinect depth sensor to extract features of Hu moment invariants from depth data, through which feature-based template match hand gesture recognition is developed. In order to construct continuous-time robot operations using dynamic hand gestures with concatenations of a series of hand gesture a

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Author

Ing-Jr Ding; Jun-Lin Su

Publisher

SAGE Publications

Published

2022

Language

EN

Field

Engineering (Physical Sciences)