With the advances of technology, mobile robots
are becoming increasingly popular. According to Karthiga
(2014) developed countries get the assistance of mobile robots
to rescue humans in disaster areas and this has been proven
as a productive method to eliminate human error. In such
instances robots are required to navigate in hostile
environments such as collapsing buildings or areas affected
fire. This paper presents implemented control architecture
for mobile robot target tracking and obstacle avoidance in a
dynamic hostile environment. Given the existing body of
research results in the field of obstacle avoidance and path
planning, which is reviewed in this context, particular
attention is paid to integrate computer vision based sensing
mechanisms to robust fuzzy logic based navigation control
method. A rule-based fuzzy controller with reactive
behaviour was implemented and tested on a RP5 mobile
robot platform. Depth and colour information for both
navigation and target tracking are to be captured using a
Asus Xtion PRO sensor. This traversability data is used to
infer, in real time, the navigational path based on the Fuzzy
Rule-Base algorithm. The effectiveness of the proposed
approach was verified through several experiments, which
demonstrates the feasibility of a fuzzy target tracker as well
as the extensible obstacle and hostile region avoidance system.
Tharindu Fernando : is currently a final year student following a
BSc computer science special degree program in Faculty of
science, University of Peradeniya Sir Lanka. His research interests
include, Artificial intelligence, Machine Learning, Computer vison
and human computer interaction.
Harshala Gammulle : Asst Prof, Dept of E & TC, Sinhgad Academy of Engg,
Pune, India
Durgaprasad K Kamat : is currently an undergraduate student
following a BSc computer science special degree program in
Faculty of science, University of Peradeniya Sir Lanka. Her
research interest include, Digital forensics, Artificial intelligence
and image processing.
Chamila Walgampaya : earned his B.Sc. in Computer Engineering
with honours in November 2001 from the Faculty of Engineering,
University of Peradeniya, Sri Lanka. He earned his Ph.D. in August
2011 from the School of Engineering at the University of Louisville.
For his Ph.D., he worked on developing a novel click fraud
detection and prevention system for Internet advertising. His
disseration titled is "Click Fruad: how to spot it? how to stop it?" He
is currently a lecturer in the Department of Engineering
Mathematics, University of Peradeniya.
Fuzzy Logic Control
Mobile Robot Target
Tracking
Obstacle Avoidance Module
Hostile Region
Avoidance Module
This paper addresses the navigational challenges that arise
in settings where mobile robots move in an unstructured
environment. We have proposed a robust fuzzy logic
based navigation control algorithm and a novel framework
for the integration of computer vision based sensing
mechanism for mobile robots. The proposed work intends
to introduce robots into open, real world environments and
navigate them intelligently with minimal human
intervention. The study has addressed the two main issues
in robot path planning. Reliable reactive obstacle and
hostile region avoidance to guarantee safe operation, and
smooth path planning that allows to dynamically adapt
environment information with the motion of surrounding
persons and objects.
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