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Executing point-to-point augmented path is one of the most challenging tasks for any mobile robot navigation. The challenge is much higher when it is in GPS (Global positioning system) denied indoor environment. This thesis presents the analysis of various intelligent approaches including applicable heuristic graph theoretic and bio-inspired techniques for achieving optimal point-to-point navigation. usage of LiDAR and RGB-D sensor data as source input has been preferred, ensuring total workspace coverage and minimization of action performed by the robot in carrying out realistic applications...