Assessment of an ant-inspired algorithm for path planning

Abstract

The demand for path planners for a variety of applications has significantly increased over the past decade. The correct choice of a distance metric will be of utmost importance for an efficient path planner. The underlying connectivity of the roadmaps produced by the planner are determined by the metrics. A study was conducted in this chapter for the proper choice of planner metrics. Five metrics from the literature were chosen and implemented in a gain-based ant colony optimization (GACO) algorithm. Results are analyzed against parameters, such as time taken, length of the path, and turn characteristics. Finally, the GACO with the chosen metric was implemented using different satellite images from the International Society for Photogrammetry and Remote Sensing and compared against existing algorithms with respect to performance.