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@article{175123,
        author = {S Narendraa Nath and K Jagadish and V Vethagreeswar},
        title = {Moblie Robot Navigation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {1768-1773},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175123},
        abstract = {Navigation and obstacle avoidance are core challenges in mobile robotics, which have been addressed by numerous researchers over the past two decades. The primary goal of navigation is to identify an optimal or suboptimal path from the starting point to the destination. Traditionally, mobile robot navigation is approached using either deterministic or nondeterministic algorithms. In recent years, a hybrid approach combining both types of algorithms, referred to as [1] Evolutionary algorithms, has been employed to tackle navigation problems. A general classification of the deterministic, nondeterministic (stochastic), and evolutionary algorithms applied to mobile robot navigation has been proposed by various researchers.
Mobile robot navigation can be broadly categorized into global and local navigation. In global navigation, the robot requires prior knowledge of the environment. [2] Several methods have been developed for global navigation, including Voronoi graphs, Artificial Potential Fields, Dijkstra's algorithm, Visibility graphs, Grid-based methods, and Cell decomposition techniques, among others. On the other hand, local navigation allows the robot to autonomously determine and control its movement and orientation using sensors like ultrasonic range finders, infrared sensors, and cameras. Methods such as fuzzy logic, neural networks, neuro- fuzzy systems, genetic algorithms, particle swarm optimization, ant colony optimization, and simulated annealing have been successfully applied to address local navigation challenges.
[3] The mobile robot navigation system is a valuable tool for tasks such as transporting objects from one location to another or navigating through different areas. Its simplicity and effectiveness are enhanced by the ability to control the robot via Bluetooth through an Android application on a smartphone.},
        keywords = {Mobile Robot Navigation, Deterministic Algorithms, Nondeterministic Algorithms, Evolutionary Algorithms, Global Navigation, Local Navigation, Voronoi Graphs, Artificial Potential Fields, Dijkstra's Algorithm, Visibility Graphs, Grid-based Methods.},
        month = {April},
        }