Paper Info
Title
Enabling A Freely Accessible Open Source Remotely Controlled Robotic Articulator With A Neuro-Inspired Control Algorithm
Abstract
Internet-enabled technologies for robotics education are gaining importance as online platforms facilitating and promoting skill training. Understanding the use and design of robotics is now introduced at university undergraduate levels, but in developing economies establishing usable hardware and software platforms face several challenges like cost, equipment etc. Remote labs help providing alternatives to some of the challenges. We developed an online laboratory for bioinspired robotics using a low-cost 6 degree-of-freedom robotic articulator with a neuro-inspired controller. Cerebellum-inspired neural network algorithm approximates forward and inverse kinematics for movement coordination. With over 210000 registered users, the remote lab has been perceived as an interactive online learning tool and a practice platform. Direct feedback from 60 students and 100 university teachers indicated that the remote laboratory motivated self-organized learning and was useful as teaching material to aid robotics skill education.
Year
DOI
Venue
2017
10.3991/ijoe.v13i01.6288
INTERNATIONAL JOURNAL OF ONLINE ENGINEERING
Keywords
Field
DocType
Remote labs, Robotic articulator, Neural Network, Open Source, ICT
USable,Inverse kinematics,Remote laboratory,Software,Information and Communications Technology,Artificial intelligence,Robotic paradigms,Engineering,Artificial neural network,Multimedia,Robotics,Embedded system
Journal
Volume
Issue
ISSN
13
1
1868-1646
Citations 
PageRank 
References 
1
0.37
0
Authors
6
Name
Order
Citations
PageRank
asha vijayan121.75
Chaitanya Nutakki222.08
Dhanush Kumar3124.01
Krishnashree Achuthan46824.70
Bipin Nair52614.21
Shyam Diwakar64418.20