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Developing a Smart Navigator for Surveillance in Unmanned Zones

  • Pooja NagEmail author
  • Sumit Shinde
  • Kapil Sadani
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 11)

Abstract

The current work reports of an obstacle avoidance and object tracking algorithm integrated and tested on robot. The system is designed with high torque geared DC motors and it has a payload capacity of up to 3 kg. The robot is fully autonomous and it is designed to patrol high security/hazardous zones and dynamically report any suspicious activity which when observed initiates an alarm to the security for further action whiles it continues to track and report the suspect. This has a major advantage over conventional CCTV systems in terms of cost and memory requirements and would not require constant human supervision. The robot proposed hereof uses wheel-encoders, ICbased Gyroscope, IR Line Laser, and spy camera as the basic sensing elements. It also has a smart charging feature which makes it energy efficient.

Keywords

Object tracking Obstacle avoidance Surveillance 

References

  1. 1.
    Labonte, D., Michaud, F., Boissy, P., Corriveau, H., Cloutier, R., Roux, M.A.: A pilot study on teleoperated mobile robots in home environments. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4466–4471, October 2006Google Scholar
  2. 2.
    Birk, A., Kenn, H.: Roboguard, a teleoperated mobile security robot. In: Control Engineering Practice, vol. 10, no. 11, pp. 1259–1264. Elsevier (2002)Google Scholar
  3. 3.
    Lidoris, G., Rohrmuller, F., Wollherr, D., Buss, M.: The Autonomous City Explorer (ACE) project—mobile robot navigation in highly populated urban environments. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1416–1422, May 2009Google Scholar
  4. 4.
    Biswas, J., Veloso, M.: Wifi localization and navigation for autonomous indoor mobile robots. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 4379–4384, May 2010Google Scholar
  5. 5.
    Maier, D., Kleiner, A.: Improved GPS sensor model for mobile robots in urban terrain. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 4385–4390, May 2010Google Scholar
  6. 6.
    Lee, K., Chung, W., Yoo, K.: Kinematic parameter calibration of a carlike mobile robot to improve odometry accuracy. Mechatronics 20(5) (2010)Google Scholar
  7. 7.
    Ferri, G., Caselli, E., Mattoli, V., Mondini, A., Mazzolai, B., Dario, P.: SPIRAL: a novel biologically-inspired algorithm for gas/odor source localization in an indoor environment with no strong airflow. Robot. Auton. Syst. 57(4), 393–402 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of MechatronicsManipal Institute of Technology, Manipal UniversityManipalIndia
  2. 2.Department of Instrumentation and ControlManipal Institute of Technology, Manipal UniversityManipalIndia

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