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MSc Thesis Defense Announcement by Padma Priya Kondepudi:"Robot Path Planning with IGA-MMAS and MMASIGA "

Friday, November 22, 2019 - 14:30 to 16:30



The School of Computer Science at the University of Windsor is pleased to present …


MSc Thesis Defense by: Padma Priya Kondepudi

Date:  Friday, November 22, 2019
Time:  2:30pm – 4:30pm
Location: 3105, Lambton Tower
Path Planning of mobile robots is one of the essential tasks in robotic research
and studies with intelligent technologies. It helps in determining the path
from a source to the destination. It has extended its roots from classic approaches
to further improvements over time, such as evolutionary approaches. Ant Colony
Optimization (ACO) and Genetic algorithm are well known evolutionary approaches
in effective path planning. This research work focuses on the Max-Min Ant Sys-
tem (MMAS) derived from the ACO evolutionary approach of Ant System (AS) and
Improved Genetic Algorithm (IGA) which is efficient over the classical Genetic Al-
gorithm. In-order to study robot path planning two methods are combined in this
research work combining MMAS and IGA as two-hybrid methods of MMAS-IGA and
IGA-MMAS . The results of the two-hybrid methods will be deriving the near optimal
solution, demonstrated in the experimental study of this work. Grid maps are used
for simulating the robot path planning environment which is modeled using the grid
method. Genetic operators of IGA are combined with MMAS for the enhancement
of the overall result of the methods IGA-MMAS and MMAS-IGA. The effectiveness
of the two methods will be determined in the simulation modeled using MATLAB
environment. The experimental results of these hybrid methods are done in a static
environment, and the performance of MMAS-IGA and IGA-MMAS is compared to
the path planning method GA-ACO.

Thesis Committee:

Internal Reader: Dr. Yung H. Tsin
External Reader: Dr. Esam-Abdel Raheem
Advisor: Dr. Dan Wu
Chair: Dr. Dima Alhadidi


 MSc Thesis Defense Announcement


5113 Lamton Tower, 401 Sunset Av., Windsor ON, N9B 3P4, (519) 253-3000 Ext. 3716