Decision Probability based Immune Plasma Algorithm for Path Planning Problem of Unmanned Aerial Vehicles

The increasing operational capabilities of modern unmanned aerial vehicles and their military counterparts focused researchers' attentions for solving complex problems to do with them optimally. In this study, Immune Plasma algorithm (IP al-gorithm or IPA) that is a recent intelligent optimization technique was modified by integrating newly designed plasma transfer schema and treatment continuation procedure and then decision probability based IPA (decIPA) was introduced for solving path planning problem of the mentioned aerial vehicles. In order to investigate how the improvements made on the fundamental operations of IPA change the qualities of the discovered paths, a set of experiments and comparative studies were carried out. The comparative studies between decIPA and other path planners allowed to state that decIPA is capable of planning more robust and safe paths especially for the test cases with high number of segmentation points.