Advertisement

Development of Guided Autonomous Navigation for Indoor Material Handling Applications

  • Aparna Geetha JayaprakashEmail author
  • Sandeep Bairampalli
  • Vijay Desai
  • Ravichandra Bhat
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 16)

Abstract

In recent past emphasis on material handling requirements in industry has gone up considerably and in particular several researchers have attempted to improve the indoor material handling. In this paper an autonomous navigation system is implemented on a trolley for applications intending to move the trolley along a predefined path without human operator assistance. The trolley operates in two modes: Learning mode and Autonomous mode. In the learning mode the operator has to manually move the trolley along a path, it has to follow autonomously when the autonomous mode is activated.

Keywords

Autonomous navigation Ultrasonic sensor Gyroscope Heading angle Kalman filter Wheel encoder 

References

  1. 1.
    Ayub, S., Bahraminisaab, A., Honary, B.: A sensor fusion method for smart phone orientation estimation (2012)Google Scholar
  2. 2.
    Piedrahita, G.A., Guayacundo, D.M.: Evaluation of accelerometer as inertial navigation system for mobile robots. IEEE, October 2007Google Scholar
  3. 3.
    Borenstein, J.: Heuristics-enhanced Odometry for indoor tracking of segways. IEEEGoogle Scholar
  4. 4.
    Redhyka, G.G., Setiawan, D., Soetraprawata, D.: Embedded sensor fusion and moving-average filter for inertial measurement unit (IMU) on the microcontroller-based stabilized platform. In: International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT) (2015)Google Scholar
  5. 5.
    Makni, A., Fourati, H., Kibangou, A.Y.: Adaptive Kalman filter for MEMS-IMU based attitude estimation under external acceleration and parsimonious use of gyroscope. In: Control Conference (ECC) (2014)Google Scholar
  6. 6.
    Kinmlioglu, S.: Fusion of sensor signals for navigation on an unmanned ground vehicle prototype. In: 22nd Signal processing and Communications Applications Conference (SIU) (2014)Google Scholar
  7. 7.
    Park, S., Hashimoto, S.: Autonomous mobile robot navigation using passive RFID in indoor environment. IEEE Trans. Ind. Electron. 56(7), 2366–2373 (2009)CrossRefGoogle Scholar
  8. 8.
    Raghavan, V., Jamshidi, M.: Sensor fusion based autonomous mobile robot navigation. IEEE (2007)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Aparna Geetha Jayaprakash
    • 1
    Email author
  • Sandeep Bairampalli
    • 1
  • Vijay Desai
    • 2
  • Ravichandra Bhat
    • 1
  1. 1.RBEI/ETP3Robert Bosch Engineering and Business Solutions Pvt. Ltd.BangaloreIndia
  2. 2.Mechanical Engineering DepartmentNational Institute of Technology Karnataka (NITK)MangaloreIndia

Personalised recommendations