<![CDATA[Planning the path is one of the most important things in the world of robotics, especially autonomous robots, to be able to move the autonomous robot requires a path that will guide the movement, or steps to be taken next, can also be spelled out as the determination of the point of coordinates to be addressed so that the robot can move to destination by taking the nearest lane and guiding the robot not to take unnecessary steps. This research uses adaptive A-star algorithm as the shortest path finding algorithm, the algorithm used is the development of A-star algorithm so that it can perform path search gradually and done repeatedly to determine every step that must be taken robot in the future and this algorithm belongs to a simple algorithm in a family heuristic algorithm. The test environment is built using Netlogo 5.3.1 Application, an agent-based application developed by Uri Wilensky at the center for Connected Learning and Compute-based Modeling at Northwestern University. The results of the tests have shown that the adaptive A-star algorithm can perform the optimal shortest path search and not trapped in the optimal local conditions with a standard deviation of 0.422%.]]>
Copyrights © 2017
