Meta-heuristic techniques for path planning: recent trends and advancements

Path planning is a propitious research domain with extensive application areas. It is the procedure to construct a collision-free path from specified source to destination point. Earlier, classical techniques were widely implemented to solve path planning problems. Classical techniques are very easy to implement but they are time-consuming and are not effective in case of uncertainties. But meta-heuristic techniques have the ability even to perform in an approximate and uncertain environment. This makes the use of meta-heuristic techniques in a more focused manner for the optimal path planning research. This paper presents the Overview, recent trends and advancement from year 2001 to 2017 in the field of optimal path planning using meta-heuristic techniques. During the study, different meta-heuristic algorithms are analysed and classified into three categories: swarm-based meta-heuristic techniques, other than swarm-based techniques and combinational meta-heuristic techniques. In addition, basic understanding and applicability of specific algorithms for path planning are also discussed along with its strengths and downsides.