Skip to main content
SpringerLink
Log in

Fuzzy obstacle avoidance optimization of soccer robot based on an improved genetic algorithm

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Due to its high-tech confrontation and entertainment, soccer robots have attracted a large number of researchers to participate in it. Robot obstacle avoidance is an active research branch in the field of intelligent robot technology, and is a comprehensive subject covering multiple disciplines. The traditional obstacle avoidance method of soccer robots has the disadvantages of poor local optimization ability and slow convergence speed, and it is easy to fall into local extreme points. Based on the active obstacle avoidance strategy of local sensors and processors, this paper studies the method of automatic extraction and optimization of fuzzy rules of fuzzy path planner by genetic algorithm. This fuzzy control method does not depend on accurate environmental information, and has a small amount of computation and learning ability. A fitness function for evaluating the validity of a rule is proposed. The simulation results show that the algorithm has good applicability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Chantsalnyam T, Park JH, Ham WC et al (2017) Obstacle avoidance extremum seeking control based on constrained derivative-free optimization. Int J Control Autom Syst 15(5):1–10

    Google Scholar 

  • Chen T, Chuang YH (2015) Fuzzy and nonlinear programming approach for optimizing the performance of ubiquitous hotel recommendation. J Ambient Intell Human Comput 9(2):275–284

    Article  Google Scholar 

  • Chen Y, Hu HJ, Ma CM et al (2018) Stroke-related changes in the complexity of muscle activation during obstacle crossing using fuzzy approximate entropy analysis. Front Neurol 9:131

    Article  Google Scholar 

  • Cheng X, Long R, Chen H (2017) Obstacle diagnosis of green competition promotion: a case study of provinces in China based on catastrophe progression and fuzzy rough set methods. Environ Sci Pollut Res 9(14):87

    Google Scholar 

  • Cui M, Liu H, Liu W et al (2017) An adaptive unscented Kalman filter-based controller for simultaneous obstacle avoidance and tracking of wheeled mobile robots with unknown slipping parameters. J Intell Robot Syst 23(5):1–16

    Google Scholar 

  • Fang W, Akash V, Song SG et al (2017) A compact magnetic field-based obstacle detection and avoidance system for miniature spherical robots. Sensors 17(6):1231–1250

    Article  Google Scholar 

  • Hassansodhro A, Pirbhulal S, Luo Z et al (2019) Towards an optimal resource management for IoT based green and sustainable smart cities. J Clean Prod 220:1167–1179

    Article  Google Scholar 

  • Hu P, Liu X, Li K et al (2017) A closed loop control algorithm for obstacle avoidance based on the transformation of master and slave tasks. J Mech Eng 53(1):21

    Article  Google Scholar 

  • Ijaz S, Hashmi FA, Asghar S et al (2017) Vector based genetic algorithm to optimize predictive analysis in network security. Appl Intell 48(2):1–11

    Google Scholar 

  • Kalogeiton VS, Ioannidis K, Sirakoulis GC et al (2019) Real-time active SLAM and obstacle avoidance for an autonomous robot based on stereo vision. Cybern Syst 50(3):1–22

    Article  Google Scholar 

  • Kapse V, Jharia B, Thakur SS et al (2017) Design of analog fuzzy controller for autonomous mobile robot. Int J Uncertain Fuzziness Knowl-Based Syst 25(3):477–494

    Article  Google Scholar 

  • Kim H, Cheang UK, Rogowski LW et al (2018) Motion planning of particle based microrobots for static obstacle avoidance. J Micro-Bio Robot 2(21):9–17

    Google Scholar 

  • Kun W, Bingyin R (2018) A method on dynamic path planning for robotic manipulator autonomous obstacle avoidance based on an improved RRT algorithm. Sensors 18(2):571

    Article  Google Scholar 

  • Lee G, Chwa D (2017) Decentralized behavior-based formation control of multiple robots considering obstacle avoidance. Intell Serv Robot 1(12):3–9

    Google Scholar 

  • Nakhaeinia D, Karasfi B (2013) A behavior-based approach for collision avoidance of mobile robots in unknown and dynamic environments. J Intell Fuzzy Syst 24(2):299–311

    Article  MathSciNet  Google Scholar 

  • Rasekhipour Y, Khajepour A, Chen SK et al (2017) A potential field-based model predictive path-planning controller for autonomous road vehicles. IEEE Trans Intell Transp Syst 18(5):1255–1267

    Article  Google Scholar 

  • Tobias N, Alonso-Mora J, Domahidi A et al (2017) Real-time motion planning for aerial videography with dynamic obstacle avoidance and viewpoint optimization. IEEE Robot Autom Lett 2(3):1696–1703

    Article  Google Scholar 

  • Ton C, Kan Z, Mehta SS (2018) Obstacle avoidance control of a human-in-the-loop mobile robot system using harmonic potential fields. Robotica 36(4):1–21

    Article  Google Scholar 

  • Wang JW, Tsai SH, Li HX (2018) Spatially piecewise fuzzy control design for sampled-data exponential stabilization of semi-linear parabolic PDE systems. IEEE Trans Fuzzy Syst 26(5):2967–2980

    Article  Google Scholar 

  • Wei J, Wu G, Yu L et al (2019) Manipulator multi-objective motion optimization control for high voltage power cable mobile operation robot. J Ambient Intell Human Comput 10:893–905

    Article  Google Scholar 

  • Wu X, Wang S, Xing M (2018) Observer-based leader-following formation control for multi-robot with obstacle avoidance. IEEE Access 7:14791–14798

    Article  Google Scholar 

  • Zhao Y, Chai X, Gao F et al (2018) Obstacle avoidance and motion planning scheme for a hexapod robot Octopus-III. Robot Auton Syst 103:199–212

    Article  Google Scholar 

  • Zheng W, Xiao Z, Hongjie S et al (2018) Obstacle detection and obstacle avoidance of AGV based on binocular vision. Comput Integr Manuf Syst 24(2):400–409

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Sports Teaching, Qufu Normal University, Rizhao, 276826, China

    Deping Chen

Authors
  1. Deping Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Deping Chen.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, D. Fuzzy obstacle avoidance optimization of soccer robot based on an improved genetic algorithm. J Ambient Intell Human Comput 11, 6187–6198 (2020). https://doi.org/10.1007/s12652-019-01636-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-019-01636-0

Keywords

Search

Navigation