The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS
Transactions ID Number: 52-512
Full Name: Ferdian Jovan
Position: Researcher
Age: ON
Sex: Male
Address: Cibinong Street, No. 789 RT 03/07, 16916
Country: INDONESIA
Tel: 081399921098
Tel prefix: +62
Fax:
E-mail address: ferdian.jovan@gmail.com
Other E-mails: ferdian.jovan@ui.edu, feroy_88@yahoo.co.id
Title of the Paper: modified pso algorithm for single and multiple odor sources localization problems: progress and challenge
Authors as they appear in the Paper: Jatmiko W, Jovan F, Dhiemas R.Y.S Alvissalim M. Sakti, Fanany M Ivan, Febrian A, T. Fukuda, K. Sekiyama
Email addresses of all the authors: wisnuj@cs.ui.ac.id, ferdian.jovan@gmail.com, syr_zameihd@yahoo.co.id, alvissalim@yahoo.com.au, shuyuie@gmail.com
Number of paper pages: 18
Abstract: Odor sensing technology in robotic research introduce two research field namely odor recognition and odor source localization. Odor source localization research also include the odor recognition ability with localization method. This paper shows some experiment had been done to localize odor source using single agent and multiple agents. Experiment shows that single agent can't be used in dynamic environment, hence also can't be used in real life application. This paper promotes an algorithm known as Particle Swarm Optimization (PSO) to solved this problems. The experiment conducted using PSO shows that PSO able to localize the odor source in the same condition where single agent failed. However, PSO still need to be modified before it can be use widely. This paper shows modification that has been proposed by the authors to enhance it's ability. The research also has been push to solve multiple odor sources using parallel localization. To verify proposed method, so!
ftware simulator was used. Results from these experiment show that Modified PSO is able to localize all four odor sources in dynamic environment in 651.900 seconds within 7 x 7 meters search area. The modification being applied in this research not limited by searching technic but also creating two types of robot.
Keywords: Particle Swarm Optimization, PSO, Modified PSO, Odor Source Localization, Al-Fath, Multiple Odor Sources Localization, Multiple Robots, Dynamic Environment, Parallel Localization
EXTENSION of the file: .pdf
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How Did you learn about congress: Inspection multiple odor sources with multiple mobile robots by modified pso algorithm
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