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.

1. Real Time Hand Movement Controlled Robotic
Arm for Risk Prevention
Shamman Noor
Jamal Ahmed Shohan
Mashrura Sharmin Waresi
Sultanul Areffin Rhythm
Mohammad Asif Ahmed
Asir Intisar Khan
Shaikh Anowarul Fattah
Celia Shahnaz

2. Motivation
Increasing Demand For
Real-time Human
Control Without Human
Deployment in
Numerous Industries
Applications
•Space Missions
•Precise Remote Control For Sensitive
Industrial and Research Instruments
•Virtual Human Handling of Toxic and
Radioactive Materials
•Authorization of Control

3. Image frame of
webcam image
RGB to gray scale
conversion
Binary image
conversion
Image filtering and
smoothing
Measuring angles
created by points
using geometric
equations
Sending array of
angles over
Bluetooth
communication to
drive servo motors
Flow Diagram

4. Prototype Robot
Arm
1. Base Platform
2. Lower Arm
3. Upper Arm
4. Grip
Base Platform
Lower Arm
Upper Arm
Grip

5. Degrees of
Freedom
1. Movement of Lower Arm
2. Movement of Upper Arm
3. Rotation of Base Platform
4. Movement of Grip
Base Platform
Grip
Lower Arm
Upper Arm

6. Image Processing Flow Diagram – Lower and Upper Arm
Image acquired from
webcam
A webcam at the top of the
hand is used to acquire this
image
Gray-scale Conversion
The image is then converted
to gray scale image
Extraction of Green
Colored areas
The gray scale image is
subtracted from the green
layer of the RGB image
Binary Image
Conversion
Resulting image is
converted to a binary image
Original Image with
Green colored areas
shown
The original image is shown
with the green areas
extracted for the user

7. Image Processing Flow Diagram – Base Platform and Grip
Image acquired from
webcam
A webcam at the side of the
hand is used to acquire this
image
Gray-scale Conversion
The image is then converted
to gray scale image
Extraction of Green
Colored areas
The gray scale image is
subtracted from the green
layer of the RGB image
Binary Image
Conversion
Resulting image is
converted to a binary image
Original Image with
Green colored areas
shown
The original image is shown
with the green areas
extracted for the user

8. How angle is transferred from Hand to Robot Arm

9. X
Y
How angle is transferred from Hand to Robot Arm

10. X
Y
Height
Base
How angle is transferred from Hand to Robot Arm

11. X
Y
Height
Base
How angle is transferred from Hand to Robot Arm

12. X
Y
Height
Base
How angle is transferred from Hand to Robot Arm

13. Results – Rotation of the Base Platform

14. Results – Rotation of the Lower Arm

15. Results – Rotation of the Upper Arm

16. Results – Movement of the Grip

17. Future Implementations
3. Movement along
XY Plane
2. Movement Along
Z - Axis
1. Two Robot Arms

18. Thank you for your attention