Fuzzy Greedy RRT Path Planning Algorithm in a Complex Configuration Space

  • Ehsan TaheriEmail author
  • Mohammad Hossein Ferdowsi
  • Mohammad Danesh
Regular Papers Intelligent Control and Applications


A randomized sampling-based path planning algorithm for holonomic mobile robots in complex configuration spaces is proposed in this article. A complex configuration space for path planning algorithms may cause different environmental constraints including the convex/concave obstacles, narrow passages, maze-like spaces and cluttered obstacles. The number of vertices and edges of a search tree for path planning in these configuration spaces would increase through the conventional randomized sampling-based algorithm leading to exacerbation of computational complexity and required runtime. The proposed path planning algorithm is named fuzzy greedy rapidly-exploring random tree (FG-RRT). The FG-RRT is equipped with a fuzzy inference system (FIS) consisting of two inputs, one output and nine rules. The first input is a Euclidean function applied in evaluating the quantity of selected parent vertex. The second input is a metaheuristic function applied in evaluating the quality of selected parent vertex. The output indicates the competency of the selected parent vertex for generating a random offspring vertex. This algorithm controls the tree edges growth direction and density in different places of the configuration space concurrently. The proposed method is implemented on a Single Board Computer (SBC) through the xPC Target to evaluate this algorithm. For this purpose four test-cases are designed with different complexity. The results of the Processor-in-the-Loop (PIL) tests indicate that FG-RRT algorithm reduces the required runtime and computational complexity in comparison with the conventional and greedy RRT through fewer number of vertices in planning an initial path in significant manner.


Holonomic robot processor-in-the-loop test rapidly-exploring random tree sampling-based path planning single board computer 


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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Ehsan Taheri
    • 1
    Email author
  • Mohammad Hossein Ferdowsi
    • 1
  • Mohammad Danesh
    • 2
  1. 1.Control Group, Electrical Engineering DepartmentMalek-Ashtar University of TechnologyTehranIran
  2. 2.Department of Mechanical EngineeringIsfahan University of TechnologyIsfahanIran

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