Moving Robot Path Planning Algorithm Analysis on Dynamic Environment Based Difference Method Update on Ant Colony Algorithm

Abstract

The algorithms is one of important thing at mobile robot path planning. It's commonly used to solve a problem in path planning, especially when the environtment is so complexity, where the object can be move dynamically (target or obstacle). The path's must be collision-free (safe path), the shortest-path, and the time required by the robot to reached distination (best time). The ACO (ant colony optimization) is one of algorithm can be used to get a shortest-path in path planning algorithm, ACO have renewal processes (pheromone updating) to optimize result (search process), and it's used in this research for searching process. The pattern of target movement in this research with liniers and sinusoidals motion pattern and simulation use Netlogo 5.3.1 simulator software can be done, an agent-based free application developed by Uri Wilensky at the Center for Connected Learning and Computed-based Modeling at Northwestern University. In this research using two different renewal process (4 grids and 8 grids) for upgrading process araound the best patch, where is the 8 grids is more suitable for use at complex environtments with large number of obstacles especially in terms of time required algorithm to finding a shortest path.