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Automatic Control and Computer Sciences

, Volume 52, Issue 5, pp 382–391 | Cite as

Design of Sensor Data Fusion Algorithm for Mobile Robot Navigation Using ANFIS and Its Analysis Across the Membership Functions

  • S. AdarshEmail author
  • K. I. Ramachandran
Article
  • 31 Downloads

Abstract

Design and development of autonomous mobile robots attracts more attention in the era of autonomous navigation. There are various algorithms used in practice for solving research problems related to the robot model and its operating environment. This paper presents the design of data fusion algorithm using Adaptive Neuro Fuzzy Interface (ANFIS) for the navigation of mobile robots. Detailed analysis of various membership functions (MFs) provided in this paper helps to select the most appropriate MF for the design of similar navigation systems. The combined use of fuzzy and neural networks in ANFIS makes the measured distance value of the residual covariance consistent with its actual value. The data fusion algorithm within the controller of the mobile robot fuses the input from ultrasonic and infrared sensors for better environment perception. The results indicate that the data fusion algorithm provides minimal root mean square error (RMSE) and mean absolute percentage error (MAPE) when compared with that of the individual sensors.

Keywords:

fuzzy ANFIS data fusion membership functions evaluation ultrasonic sensor IR sensor error analysis 

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Copyright information

© Allerton Press, Inc. 2018

Authors and Affiliations

  1. 1.Department of Electronics and Communication Engineering, Othakkal Mandapam PostCoimbatoreIndia
  2. 2.Department of Mechanical Engineering Amrita School of EngineeringCoimbatore Amrita Vishwa VidyapeethamIndia

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