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Extracting an accurate and complete map of the world is among the most difficult tasks in mobile robotics. In this regard, enabling the mobile robot to learn the map of the world and choose the optimum destination to continue the autonomous scanning of the environment, is the topic of this research. For this purpose, the Rao-Blackwellized particle filter for occupancy grid maps is used to determine the pose of the robot and create the map of the world. Furthermore, a two layered architecture is used for motion planning, considering the path planning and obstacle avoidance. The fundamental of exploration problem is determining the optimum goal among the other potential goals. The main objective of this research is to gain the ability of selecting the goal without human intervention and creating the map of the world autonomously. Hence in this work, the frontier-based exploration strategy is applied to the robot for the purpose of selecting the optimum goal. For practical implementation of the exploration problem, Robot Operating System(ROS) framework is used as the software platform of the robot. Moreover, the area of the fifth floor of the mechanical engineering department of the Isfahan university of technology is chosen as the unknown environment to test the robot. As a result, the frontier-based approach turned to be an effective algorithm for exploring the large and cluttered environments.

  • Mr. Majid Fattahian, MSc in Mechanical Engineerig, Isfahan University of Technology
  • Dr. Mehdi Keshmiri, Professor, Robotics, Isfahan University of Technology
  • Dr. Hossein Karimpour, Assistant Professor, Robotics and control, University of Isfahan




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