RANGED SUBGROUP PARTICLE SWARM OPTIMIZATION FOR LOCALIZING MULTIPLE ODOR SOURCES
| Autor: | Petrus Mursanto, K. Sekiyama, Benyamin Kusumoputro, Andreas Febrian, Wisnu Jatmiko, Abdul Muis, Toshio Fukuda, W. Pambuko |
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| Rok vydání: | 2017 |
| Předmět: |
Chemical concentration
Mathematical optimization lcsh:T Computer science Ode Particle swarm optimization Modified Particle Swarm Optimization Real Life Scenario Multiple Odor Sources Localization lcsh:Technology Wind speed Subgroup Odor Control and Systems Engineering lcsh:Technology (General) Parallel Search lcsh:T1-995 Robot Open dynamics engine Open Dynamic Engine Electrical and Electronic Engineering Parallel search |
| Zdroj: | Scopus-Elsevier International Journal on Smart Sensing and Intelligent Systems, Vol 3, Iss 3 (2010) |
| Popis: | A new algorithm based on Modified Particle Swarm Optimization (MPSO) that follows is a local gradient of a chemical concentration within a plume and follows the direction of the wind velocity is investigated. Moreover, the niche or parallel search characteristic is adopted on MPSO to solve the multi-peak and multi-source problem. When using parallel MPSO, subgroup of robot is introduced then each subgroup can locate the odor source. Unfortunately, there is a possibility that more that one subgroup locates one odor sources. This is inefficient because other subgroups locate other source, then we proposed a ranged subgroup method for coping for that problem, then the searching performance will increase. Finally ODE (Open Dynamics Engine) library is used for physical modeling of the robot like friction, balancing moment and others so that the simulation adequate to accurately address the real life scenario. |
| Databáze: | OpenAIRE |
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