IoT Path Planning Approach for Mobile Robots

Abstract

Path planning is an essential task for any autonomous mobile robot to extract an optimal free path from a given initial position to a defined target. In this work, new approach built upon the internet of things (IoT) has been proposed; microprocessor based devices are used on path generation and robot platforms focus on path following. Hence, two different algorithms, Bug0 and Potential Field, are merged to create a hybrid approach using fixed cell decomposition for the environment and a map of this environment is created. Data are exchanged via the wireless LAN (local area network). The obtained results surpass the traditional implementations where robots were making every decision. Moreover, the proposed topology accomplishes scalability easily. Therefore, this work consists of the development and the implementation of intellectual and robust software to automate the robot tasks. A map, built basing on data acquired from a camera, will activate the whole process; then, a computer (or any microprocessor device) will treat these data and generate an optimal trajectory and send it to the robot platform via the wireless medium to enable it to navigate from any given initial point to any target. The robot is also able to detect a change in the environment and report it to the computer to get a new path.