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IJSTR >> Volume 9 - Issue 3, March 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Development Of Autonomous Robot For Tunnel Mapping Using Raspberry-Pi Processor

[Full Text]

 

AUTHOR(S)

P.Velrajkumar, P.Ramesh, C.Senthilpari, T.Bhuvaneswari, V.Chitra

 

KEYWORDS

Autonomous Robot, Tunnel Mapping, Raspberry-Pi, Ubuntu, Wifi Module, QT Creator, Camera.

 

ABSTRACT

An autonomous robot plays an important role in the future of rescue operation in unknown environments. In this research a robot is capable of moving in tunnel and able to do operation in the tunnel. The robot is controlled wirelessly via Wifi communication using wifi router. The robot itself is equipped with a mini computer that is a Raspberry-Pi processor. The Raspberry-Pi is the brain for the robot as it gives out command on the movement of the robot and the data from the USB camera is collected and then transmitted to the computer. The robot is capable to go up 75 to 110 meters on Wifi signal. Once the connection is lost the robot will stop by itself. The robot is equipped with two batteries that last long and does run for more than 30 – 45 minutes. The robot is controlled via a computer that is programmed to run Ubuntu operating system. From the comfort of sitting in front of the computer the robot can be controlled from a distance and the live is then stream on the computer.

 

REFERENCES

[1] Stefano Carpin, “Fast and Accurate Map Merging for Multi-Robot Systems”, Autonomous Robot, 25 (3), pp. 305 – 316, 2008.
[2] Durrant-Whyte.H, Bailey.T, “Simultaneous Localization and Mapping: Part I”, IEEE Robotics and Automation Magazine, 13 (2), pp. 99 – 110, 2006.
[3] Guolai Jiang, Lei Yin, Shaokun Jin, Chaoran Tian, Xinbo Ma, Yongsheng Ou, “A Simultaneous Localization and Mapping (SLAM) Framework for 2.5D Map Building based on Low-Cost LiDAR and Vision Fusion”, Applied Sciences, 9, pp. 1 – 17, 2019.
[4] Hsieh.M.Y.A, Kumar.V, Taylor.C.J, “Construting Radio Signal Strength Maps with Multiple Robots”, IEEE International Conference on Robotics and Automation, 2004.
[5] Dieter Fox, Wolfram Burgard, Hannes Kruppa, Sebastian Thrun, “A Probabilistic Approach to Collaborative Multi-Robot Localization”, Autonomous Robot, 8, pp. 325 – 344, 2000.
[6] Hahnel.D, Schulz.D, Burgard.W, “Map Building with Mobile Robots in Populated Environments”, IEEE International Conference on Intelligent Robots and Sytems, 2002.
[7] Velrajkumar.P, Senthilpari.C, Ramesh.P, Ramanamurthy.G, Kodandapani.D, “Development of Smart Number Writing Robotic Arm using Stochastic Gradient Decent Algorithm”, International Journal of Innovative Technology and Exploring Engineering, 8 (10), pp. 542 – 547, 2019.
[8] Larsen.M.B, “High Performance Doppler-Inertial Navigation-Experimental Results”, IEEE Conference on OCEANS, 2000.
[9] Leonard.J.J, Durrant-Whyte.H.F, “Mobile Robot Localization by Tracking Geometric Beacons”, IEEE Transactions on Robotics and Autoimation, 7 (3), pp. 376 – 382.
[10] Lima.P.U, Santos.P, Oliveira.R, Atmad.A, Santos.J, “Cooperative Localization based on Visually Shared Objects”, Lecture Notes in Computer Science, Springer, 6556, 2011.
[11] Neira.J, Tardos.J.D, “Data Association in Stochastic Mapping using the Joint Compatibility Test”, IEEE Transactions on Robotic and Automation, 17 (6), pp. 890 – 897, 2001.
[12] Amer.S.I, Eskander.M.N, Aziza M.Zaki, “Positioning and Motion Control for Mobile Robot”, International Journal of Emerging Technology and Advanced Engineering, 2 (11), pp. 498 – 504, 2012.