Review and Analysis of Different Methodologies Used in Mobile Robot Navigation

Robot navigation is a fundamental problem in robotics. Navigation associated to mobile robot is the problem of finding a feasible path form one configuration to another by avoiding the obstacles along its path. Various approaches have been developed to cope with this problem and still researchers are keen to develop the new techniques which would make the process smoother and faster. Selection of the suitable method depends on the application and the working environment as not even a single approach guarantees for the optimal result in any kind of workspace. Therefore the choice of approach has become a demanding task. Combination of different approaches also used in order to make the local as well as global navigation system more effective. This paper provides an overview on different methodologies used for the successful navigation of mobile robot in last few decades. The paper focuses on the reactive navigation techniques based on as Neural Network, Fuzzy Logic, Neuro-Fuzzy, Fuzzy-Neuro, Genetic Algorithm, and biologically inspired techniques like Ant Colony Optimization (ACO) algorithm, Particle Swarm Optimization (PSO) Algorithm, and Bacteria Foraging Optimization Algorithm (BFOA) and Bees Algorithm (BA).