Classical and Heuristic Approaches for Mobile Robot Path Planning: A Survey

The most important research area in robotics is navigation algorithms. Robot path planning (RPP) the process of choosing best route for a mobile robot to take before it moves. Finding an ideal or nearly referred as “path optimization.” solution values that satisfy single number objectives, such shortest, smoothest, and safest path, goal. objective this study present overview strategies robots utilize three classical approaches, namely: roadmap approach (RM), cell decomposition (CD), artificial potential fields (APF), addition eleven heuristic including genetic algorithm (GA), ant colony optimization (ACO), bee (ABC), gray wolf (GWO), shuffled frog-leaping (SFLA), whale (WOA), bacterial foraging (BFO), firefly (FF) algorithm, cuckoo search (CS), bat (BA), which may be used various environmental situations. Multiple issues, dynamic goals, static environments, multiple robots, real-time simulation, kinematic analysis, hybrid algorithms, are addressed different set articles presented study. A discussion, well thorough tables charts, will at end work help readers understand what types developed use wide range ecological contexts. Therefore, work’s main contribution provides broad view planning, make easier scientists topic near future.