Sensor-based robot motion planning - A tabu search approach

The attractive research theme for many roboticists has been the planning robot motions. The class of motion planners dealing with is known as online, sensor-based, local, a posteriori, real-time, and reactive motion planners. There are classic motion-planning approaches for planning and optimizing robot motions and one is generally known as metaheuristics. Aside from genetic algorithms (GAs) and simulated annealing (SA), another well-known metaheuristic technique is tabu search (TS) method. It is a powerful algorithmic approach that has been remodeled and integrated in a single algorithm to craft a motion planner capable of solving varieties of exploration and goal-finding problems. The online and sensor-based nature of the presented model, can be applied to dynamic environments, as well.