Title: "An Enhanced Object Detection Approach for Robot-Hand Implementation"
Authors:
Ngo Thanh Nhan – 18521175 – KTMT2018 – Main Author.
Truong Tai Thuan – 18521472 – KTMT2018 – Co-author.
Supervisor: MS. Doan Duy.
Abstract:
Recently, robot-hand has drawn many attention in the field of automated control and applied in different fields of industry, life, and science. Developing an automatic robot-hand with high accuracy and low cost to support people with hand disability is the interest of this paper. To this end, we introduced an enhanced image classification approach to classify targeted objects and build our own 3D Printed Robot-Hand. We are then training the robot-hand with images of typical objects and applying the output result of detecting to control the grabbing and holding processes of the robot-hand. The accuracy of object detection achieves about 91 % and the holding process is almost successful for the detected objects, which indicates the application potential of this approach
In this paper, our goal was to deploy a low-cost robot hand capable of automatically gripping objects. This means the robot hand could grasp objects with appropriate force and direction corresponding to the shape of the object. This project can greatly enhance the daily activities of people with disabilities and can be used for intelligent robots. We believe this topic will have high practical applications in the future.
We express our gratitude to Mr. Doan Duy and the Computer Engineering Faculty for their guidance and support during our research and the publication of this international scientific paper.
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Hai Bang - Media Collaborator, University of Information Technology
Translation: Nhat Hien