Browsing by Author "Abed, Mohamed Amine"

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    Development and implementation of an even and uneven environment navigation strategy
    (2016) Belkalem, Jugurtha; Abed, Mohamed Amine; Belaidi, Hadjira (Supervisor)
    Industrial robotics is evolving quickly around the world, a great interest is shown for these machines.The robot’s age is close, new citizens will join our society. However, for these machines to operate complex algorithms are needed and required to handle various situations. An important capability for mobile robots is navigation, reaching a destination without colliding the obstacles, this problem is referred as Path Planning. Path planning is required for an autonomous mobile robot to find an optimal trajectory to the destination, a human controller is not needed anymore. A new approach has been proposed in this work, built upon the internet of objects ; computers are focused on path computation and robots on the execution, information is exchanged through the network (wireless local area network). The results outperform by far the classical implementations where robots were making every decision. Scalability is also achieved easily using the proposed topology, multiple robots can be controlled without impacting on the implementation. In this project, intelligent and robust software has been written to automate every task, a simple input of the map will trigger the whole process, the computer will compute an optimal trajectory then sends it to the robot for execution through the wireless medium(WIFI). The path is preplanned and can be saved for further exploitation. The robot is also able to detect a change in the environment and report it to the computer to get a new path.
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    IoT Path Planning Approach for Mobile Robots
    (IEEE, 2018) Belaidi, Hadjira; Jugurtha, Belkalem; Abed, Mohamed Amine; Bentarzi, Hamid
    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.