Comparative Analysis of Three Obstacle Detection and Avoidance Algorithms for a Compact Differential Drive Robot I N V-Rep

  • Chika Yinka-Banjo
  • Obawole Daniel
  • Sanjay MisraEmail author
  • Oluranti Jonathan
  • Hector Florez
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1051)


The aim of this research is to build a compact differential drive robot using the Virtual Robotics Experimentation Platform. Sensors are embedded in the Pioneer 3-dx mobile robot to provide necessary data from the real world to the robot. The main purpose of the mobile robot is its ability to arrive at a given destination (goal) precisely and astutely, hence, significantly reducing the risk of human mistakes. Many existing algorithms like obstacle detection, lane detection is combined to provide the essential and basic control functionalities to the car. The mobile robot controller model runs on a series of benchmark tasks, and its performance is compared to conventional controllers. During the scope of this project, comparisons between different algorithms, hardware and tools have been made to choose the best-fit for the project. The results are obstacle detection algorithms and a terrain handling feature, that works very well in simulations and real-life situations. The major tailbacks during the development of this project were limitations caused by low hardware computational power, the presence of stronger processors would exponentially increase the throughput and consequently improve the accuracy of the scene objects and the obstacle detection algorithms.


Bug Pioneer 3-DX VREP Sonar API OS Scene 



The authors gratefully acknowledge the support of African Institute for Mathematical Sciences (AIMS), Alumni small research grant (AASRG), the Organisation for Women in Science for the Developing World (OWSD), and L’oreal-Unesco for Women in Science.

The authors of this research also appreciate the immense contribution of Covenant University Centre for Research, Innovation, and Discovery (CUCRID) for its support for this research.


  1. 1.
    Günther, M., Weihmann, T.: Climbing in hexapods: a plain model for heavy slopes. J. Theor. Biol. 293, 82–86 (2011). Jena, Germany, Copyright © 2011 Elsevier Ltd. All rights reservedCrossRefGoogle Scholar
  2. 2.
    Ferrell, C.: A comparison of three insect-inspired locomotion controllers. Robot. Autom. Syst. 16, 135–159 (1995). Cambridge, Copyright © 1995 Published by Elsevier B.V.CrossRefGoogle Scholar
  3. 3.
    Misra, S., Alfa, A.A., Olaniyi, M.O., Adewale, S.O.: Exploratory study of techniques for exploiting instruction-level parallelism. In: GCSIT 2014 – Global Summit on Computer and Information Technology, Tunisia, pp 1–6 (2014)Google Scholar
  4. 4.
    Navarro-Serment, L.: A beacon system for the localization of distributed robotic teams. In.: Proceedings of the International Conference on Field and Service Robotics (1999)Google Scholar
  5. 5.
    Omichi, T.: Hierarchy control system for vehicle navigation based on information of sensor fusion perception depending on measuring distance layer. In: Proceedings of the International Conference on Field and Service Robotics (1999)Google Scholar
  6. 6.
    Soto, A.: Cyber-ATVS: dynamic and distributed reconnaissance and surveillance using all terrain UGVS. In: Proceedings of the International Conference on Field and Service Robotics (1999) Google Scholar
  7. 7.
    Prassler, E.: Maid: a robotic wheelchair roaming in a railway station. In: Proceedings of the International Conference on Field and Service Robotics (1999)Google Scholar
  8. 8.
    Thrun, S.: Experiences with two deployed interactive tour-guide robots. In: Proceedings of the International Conference on Field and Service Robotics (1999)Google Scholar
  9. 9.
    Borenstein, J.: Obstacle avoidance with ultrasonic sensors (1999)Google Scholar
  10. 10.
    Guruprasad, K.R.: A real time path planning algorithm for a mobile robot in an unknown environment. In: Advanced Computing, Networking and Security (ADCON) (2011)Google Scholar
  11. 11.
    Sankaranarayanan, A., Vidyasagar, M.: Path Planning for Moving a Point Object Amidst Unknown obstacles in a plane (1991)Google Scholar
  12. 12.
    Okewu, E., Misra, S.: Applying metaheuristic algorithm to the admission problem as a combinatorial optimization problem. Front. Artif. Intell. Appl. 282, 53–64 (2016)Google Scholar
  13. 13.
    Noborio: Evaluation of path length made in sensor-based path-planning with the alternative following. In: Proceedings of the IEEE International Conference of Robotics and Automation (2001)Google Scholar
  14. 14.
    Buniyamin, N.: A simple local path planning algorithm for autonomous mobile robots. Int. J. Syst. Appl. Eng. Dev. 5(2), 151–159 (2011)Google Scholar
  15. 15.
    Kamon, I., Rivlin, E.: Sensory-based motion planning with global proofs. IEEE Trans. Robot. Autom. 13(6), 814–822 (1997)CrossRefGoogle Scholar
  16. 16.
    ASSIS: A Scalable Constructive Path Planning for Mobile Agents based on the Compact Genetic Algorithm (2017)Google Scholar
  17. 17.
    Kanehiro, F.: Open HRP: open architecture humanoid robotics platform. J. Robot. Res., Int (2004)Google Scholar
  18. 18.
    Ng, J.: An Analysis of Mobile Robot Navigation Algorithms in Unknown Environments (2010)Google Scholar
  19. 19.
    Pallottino, P.L.: Distributed Robotic Systems (2015)Google Scholar
  20. 20.
    Freese, M.: Collision detection distance calculation and proximity sensor simulation using oriented bounding box trees. In: 4th International Conference on Advanced Mechatronics (2004)Google Scholar
  21. 21.
    Pandya, H.V.: Mobile Manipulator based Framework for Dataset Generation and Algorithm Testing (2015)Google Scholar
  22. 22.
    Ramli, N.R.: An Overview of Simulation Software for, pp. 3–5 (2015) Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer SciencesUniversity of LagosLagosNigeria
  2. 2.Covenant UniversityOtaNigeria
  3. 3.Universidad Distrital Francisco Jose de Caldas BogotaBogotaColombia

Personalised recommendations