Paper Info
Title
Bent fingers' angle calculation using supervised ANN to control electro-mechanical robotic hand
Abstract
The shape of human hand is such that it can perform many tedious tasks easily. It can reach narrow places and can perform difficult operations. It can bend its fingers at different angles to pick or hold different objects and apply force via fingers or palm area. It is very helpful in many difficult applications. However, there is risk of injury to the human hand, or even life in dangerous operations. It is not advisable to gamble of human body parts for applications like land mine removal. Hence, there is a need of a robotic hand which can perform the same operation as a human hand does in real time. This paper discusses a vision-based technique of controlling a robotic hand which has human hand like joints in fingers. The user has to show a gesture to the system with bare hand without any limitation on hand direction and the robotic hand would mimic that gesture. The positions of human hand fingers were calculated using supervised Artificial Neural Network. The preprocessing made the whole algorithm faster by cropping the region of interest from input image frame. The gesture was extracted from the input image and fingertips, centre of palm were detected. The animated simulation of robotic hand is done in Blender(R) software.
Year
DOI
Venue
2013
10.1016/j.compeleceng.2012.07.012
Computers & Electrical Engineering
Keywords
DocType
Volume
different angle,supervised ann,bare hand,human hand,difficult application,human hand finger,robotic hand,electro-mechanical robotic hand,bent finger,angle calculation,hand direction,different object,human body part,difficult operation
Journal
39
Issue
ISSN
Citations 
2
0045-7906
4
PageRank 
References 
Authors
0.55
18
2
Name
Order
Citations
PageRank
Ankit Chaudhary119618.51
Jagdish Lal Raheja216414.88