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In the recent decade, robotic exploration is emerging as a vast research platform as it prolongs to be a challenging task, especially in unknown dynamic environments. Exploration plays a vital role in collecting data from the areas inaccessible to the human. The operation of manual exploration systems in complex environments is cumbersome due to ineffective noise filtering, poor visibility and shuffling of map characteristics. In order to overcome such drawbacks, our approach focuses on the development of autonomous robotic exploration by designing a robust SLAM-based system, incorporating tri-layered mapping technique for automatic map generation and a new geometrical boundary-based path-planning technique to improve the mobility of the robot during navigation. The proposed path-planning algorithm yields better trajectory planning and obstacle avoidance using the pose, odometry and orientation parameters of the robot. The performance of the developed robot is evaluated through real-time experimentation, and it is evident from the results that, the proposed approach is preferable for autonomous exploration applications.

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The world has shrunk as the internet grew large. The best example are maps, navigation etc. People can see their own location from the internet and help to navigate to places, streets, cities etc. But still it has a limitation that maps cannot navigate through an enclosed environment as the environment will be represented as blocks in maps. In such cases when a stranger gets into the environment, to reach a particular point in it, it will be difficult for navigating independently. Also in that situation the stranger has to ask for information from the people in the region which will be leading to a trial and error scenario. So in order to provide the navigating information to the user directly, without using the concept of internet, Automatic Navigation System for a Specific Locality is proposed where the Wi-Fi streamers will be streaming the information to the people in checkpoints to navigate them to the destination points.