The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of MATHEMATICS AND COMPUTERS IN SIMULATION
Transactions ID Number: 19-674
Full Name: Norlida Buniyamin
Position: Associate Professor
Age: ON
Sex: Female
Address: Fac. of Electrical Engineering, University Teknologi Mara, Shah Alam, Selangor
Country: MALAYSIA
Tel: 60193579877
Tel prefix: 60355436082
Fax: 60355435077
E-mail address: nbuniyamin@salam.uitm.edu.my
Other E-mails: norlida_buniyamin@yahoo.com
Title of the Paper: Robot global path planning overview and a variation of ant colony system algorithm
Authors as they appear in the Paper: Norlida Buniyamin, Nohaidda Sariff, Wan Ahmad Jailani Wan Ngah, Zainuddin Mohamad
Email addresses of all the authors: nbuniyamin@salam.uitm.edu.my,zainuddin@salam.uitm.edu.my,norhaiddasariff@yahoo.com,jai3232@yahoo.co.uk
Number of paper pages: 8
Abstract: This paper presents the results of a research that aims to develop an algorithm to solve robot path planning (RPP) problems in static environments. The problem is to find a global optimal path that satisfies the optimization criteria of shortest path with minimum computation time. A description of a variation of Ant Colony System (ACS) algorithm utilized for Robot Path Planning (RPP) purposes is presented. A representation of heuristic and visibility equation of state transition rules is proposed to sustain the function of Ant Colony System (ACS) for solving RPP problem of finding the optimal path. This algorithm was applied within a global static map that consists of feasible free space nodes. The performance of the algorithm in terms of computation time and number of iteration required to obtain an optimal path were evaluated by using a simulation approach. Subsequently, its performance was compared to the performance of Genetic Algorithm (GA) a well known and e!
stablished RPP algorithm. The results obtained indicate that the developed algorithm performed much better than the GA. In addition, an overview of robot path planning (PP) algorithms in global static environment is also offered.
Keywords: Path Planning, Ant Colony System, Algorithm, Global Environment, Autonomous Robot.
EXTENSION of the file: .pdf
Special (Invited) Session: Ant Colony System for Robot Path Planning in Global Static Environment
Organizer of the Session: 635-272
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