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Tuning of Robot Navigation Performance Using Factorial Design

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Abstract

A fuzzy logic controller for mobile robot navigation involves some parametric choices for membership functions for the robot’s forward and angular velocities. In the literature, ad hoc choices are generally made for the number and type of membership functions associated with the fuzzy algorithm. In this work, a Design of Experiments strategy is adopted to study the effect of choices for five factors in a fractional factorial experiment, followed by a full factorial experiment. A fractional factorial experiment with resolution V was implemented to study the effect of type/number of membership functions for forward and angular velocities, in addition to LiDAR range on the robot’s navigation time. The robot’s navigation time is formulated mathematically as a function of the significant factors, using the regression equation extracted from the analysis. The optimization of this regression equation revealed that the robot’s navigation time is minimized using five triangular membership functions for forward velocity with a 6 m LiDAR range. Finally, a confirmation experiment is implemented to validate the adopted regression equation’s prediction under untested combinations of factors and the results of this experiment confirm those obtained from the fractional and full factorial experiments. When the algorithm was re-evaluated using the results of this study, a significant improvement in performance was realized.

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Authors and Affiliations

  1. Department of Electrical, Computer Engineering and Computer Science, University of Detroit Mercy, Detroit, MI, USA

    Amna Mazen, Mariam Faied & Mohan Krishnan

  2. Faculty of Engineering, Fayoum University, Fayoum, Egypt

    Amna Mazen

Authors
  1. Amna Mazen
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  2. Mariam Faied
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  3. Mohan Krishnan
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Contributions

A.M., M.F. and M.K. contributed to the design of the research, to the analysis of the results and to the writing of the manuscript. A.M. performed the experiments.

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Correspondence to Amna Mazen.

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Mazen, A., Faied, M. & Krishnan, M. Tuning of Robot Navigation Performance Using Factorial Design. J Intell Robot Syst 105, 50 (2022). https://doi.org/10.1007/s10846-022-01659-4

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