SIMULATION OF ROBOT MOVEMENT IN 2-DIMENSIONAL SPACE USING FUZZY-PARTICLE SWARM OPTIMIZATION - Irianto Irianto; Tan Hauw-Sen (FMIPA Universitas Lampung, 2020)
Nowdays, the use of a group of autonomous robots are grown increasingly, especially for an application dealing with hazardous material and or dangerous situation. In this case, autonomous robot movement where there is no interference from a human on the execution process is very important. The concern is how this group of autonomous robots could arrive as fast as possible to the target location to perform the tasks given. If it includes the movement of groups of autonomous robots then particle swarm optimization (PSO) is one of a simple yet powerful method available. Fuzzy logic as a logic system has been proven can be combined with various numbers of applications or methods to get a more optimal result. One of them is the combination of fuzzy logic with PSO method. This paper implemented the fuzzy-PSO optimization method to simulate a group of robots movement to the target location using scratch programming. The fuzzy-PSO optimization results, then compared to the results of classic PSO optimization. It is found that the robots with fuzzy-PSO optimization movement arrived at the location target in average more than 40% faster compared to the robots with classic PSO optimization movement.