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Max-Min Ant System Algorithm for Dynamic Grid Environment

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  • Thu, 03/01/2018 - 2:30pm - 4:00pm




Max-Min Ant System Algorithm for Dynamic Grid Environment.

MSc Thesis Proposal by:

Satya Shree Sankini

Date:  Thursday, March  1st, 2018
Time:  2:30pm – 4:00 pm
Location: 3105, Lambton Tower

Abstract: Path planning is an essential task for the robot to navigate and control its motion. It is said to be an NP complete problem which is difficult to solve, especially in a dynamic environment. The optimal path needs to be rerouted each time a new obstacle appears in front of the robot in the dynamic environment.

This research focuses on the MAX-MIN Ant System Algorithm(MMAS) which is an Ant Colony Algorithm derived from Ant System and is different from it. The effectiveness of this algorithm is illustrated by the means of experimental study. Using a greedier search than the Ant System algorithm is one of the specific characteristics of the MMAS, which will be studied in the research.  The robot environment model is represented by a grid which has obstacles whose positions change in each map that is used. Local search routines will be added that take the solution generated by the ants to their local optimum before the pheromone update and this would enhance the solutions obtained by the previous researchers.

To implement the idea of the research, the experiments will be performed in MATLAB development environment where a simulation program will be designed, and the algorithm will be implemented in different maps with obstacles.

Thesis Committee:
Internal Reader: Dr. Imran Ahmad
External Reader: Dr. Chunhong Chen
Advisor: Dr. Dan Wu

 



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