Call for Papers 2024 |
Feb 2024 - Volume 15, Issue 1
Deadline: 15 Jan 2024
Publication: 20 Feb 2024
Apr 2024 - Volume 15, Issue 2
Deadline: 15 Mar 2024
Publication: 20 Apr 2024
More
|
|
|
ABSTRACT
Title |
: |
CONTROL OF AN AUTONOMOUS VEHICLE WITH OBSTACLES IDENTIFICATION AND COLLISION AVOIDANCE USING MULTI VIEW CONVOLUTIONAL NEURAL NETWORK |
Authors |
: |
M.Karthikeyan, S.Sathiamoorthy |
Keywords |
: |
Autonomous Vehicle, Neural Networks, CNN, Machine Learning and Deep Learning, WMFA |
Issue Date |
: |
Jan-Feb 2021 |
Abstract |
: |
Artificial Intelligence (AI) is inevitable in this era for automation requirements in all large scale industries like Automotive, Aerospace, Railways, Industrial automation, and Renewable energy industries. Among the AI techniques, deep learning algorithm with artificial neural network (ANN) receives greater attention on estimation and control requirements. In this paper, control of autonomous passenger vehicle using deep multi view convolutional neural network (CNN) for the identification of obstacles with 3 dimensional (3D) images of the same using Winograd Minimal filter algorithm (WMFA) has been presented. Authors also have clearly articulated the accuracy level difference between Machine learning (ML) algorithm, basic CNN algorithm and the proposed CNN algorithm in this paper for obstacle identification, collision avoidance and steering control. Most importantly, training of neural networks with multi view topology using Matlab/Simulink coding has been presented with the results. Real-time 3D images have been captured and compared with the stored and trained data. Output of trained CNNs have been captured and the results have been compared and discussed in this paper. |
Page(s) |
: |
178-192 |
ISSN |
: |
0976-5166 |
Source |
: |
Vol. 12, No.1 |
PDF |
: |
Download |
DOI |
: |
10.21817/indjcse/2021/v12i1/211201209 |
|