Skip to main content
SpringerLink
Log in

Motion control of multiple humanoids using a hybridized prim’s algorithm-fuzzy controller

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Prim’s algorithm has demonstrated a very effective and selective method of solving the minimum spanning tree optimization problems. It is a greedy algorithm that starts from an empty spanning tree and reaches its goal by picking the minimum weight edges which alternately optimizes the path in less possible time. In this paper, the capability of prim’s algorithm in designing the behavioural controller of a humanoid robot has been shown. Here, a new hybrid PA–Fuzzy motion planning approach has been proposed that uses the concept of minimizing the distance between the robot and obstacles as well as robot and target. An optimal turning angle is generated by the hybrid controller that helps to avoid the obstacles present in the arena to create a collision-free path. The results obtained from hybrid PA–Fuzzy motion planning procedure show the capability of the controller in achieving the optimal paths in different environments with both static and dynamic obstacles. The results observed from simulation and experimental arenas are found to be in satisfactory agreement with each other producing minimal error limits. The developed hybrid technique is compared with some existing methodologies, and significant improvement is found in relation to path length and computational time.

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

  • Bajrami X, Dërmaku A, Demaku N (2015) Artificial neural fuzzy logic algorithm for robot path finding. IFAC-PapersOnLine 48(24):123–127

    Article  Google Scholar 

  • Bakdi A, Hentout A, Boutami H, Maoudj A, Hachour O, Bouzouia B (2017) Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control. Robot Auton Syst 89:95–109

    Article  Google Scholar 

  • Baklouti E, Amor NB, Jallouli M (2017) Reactive control architecture for mobile robot autonomous navigation. Robot Auton Syst 89:9–14

    Article  Google Scholar 

  • Bingul Z (2007) Adaptive genetic algorithms applied to dynamic multiobjective problems. Appl Soft Comput 7(3):791–799

    Article  Google Scholar 

  • Castillo O, Neyoy H, Soria J, Melin P, Valdez F (2015) A new approach for dynamic fuzzy logic parameter tuning in ant colony optimization and its application in fuzzy control of a mobile robot. Appl Soft Comput 28:150–159

    Article  Google Scholar 

  • Faisal M, Hedjar R, Al Sulaiman M, Al-Mutib K (2013) Fuzzy logic navigation and obstacle avoidance by a mobile robot in an unknown dynamic environment. Int J Adv Rob Syst 10(1):37

    Article  Google Scholar 

  • Fakoor M, Kosari A, Jafarzadeh M (2016) Humanoid robot path planning with fuzzy Markov decision processes. J Appl Res Technol 14(5):300–310

    Article  Google Scholar 

  • Hank M, Haddad M (2016) A hybrid approach for autonomous navigation of mobile robots in partially-known environments. Robot Auton Syst 86:113–127

    Article  Google Scholar 

  • Hossain MA, Ferdous I (2015) Autonomous robot path planning in dynamic environment using a new optimization technique inspired by bacterial foraging technique. Robot Auton Syst 64:137–141

    Article  Google Scholar 

  • Juang CF, Lai MG, Zeng WT (2014) Evolutionary fuzzy control and navigation for two wheeled robots cooperatively carrying an object in unknown environments. IEEE Trans Cybern 45(9):1731–1743

    Article  Google Scholar 

  • Karami AH, Hasanzadeh M (2015) An adaptive genetic algorithm for robot motion planning in 2D complex environments. Comput Electr Eng 43:317–329

    Article  Google Scholar 

  • Karray A, Njah M, Feki M, Jallouli M (2016) Intelligent mobile manipulator navigation using hybrid adaptive-fuzzy controller. Comput Electr Eng 56:773–783

    Article  Google Scholar 

  • Kim CJ, Chwa D (2014) Obstacle avoidance method for wheeled mobile robots using interval type-2 fuzzy neural network. IEEE Trans Fuzzy Syst 23(3):677–687

    Article  Google Scholar 

  • Kofinas N, Orfanoudakis E, Lagoudakis MG (2015) Complete analytical forward and inverse kinematics for the NAO humanoid robot. J Intell Robot Syst 77(2):251–264

    Article  Google Scholar 

  • Kumar A, Kumar PB, Parhi DR (2018) Intelligent navigation of humanoids in cluttered environments using regression analysis and genetic algorithm. Arab J Sci Eng 43(12):7655–7678

    Article  Google Scholar 

  • Kumar PB, Mohapatra S, Parhi DR (2019a) An intelligent navigation of humanoid NAO in the light of classical approach and computational intelligence. Comput Anim Virtual Worlds 30(2):e1858

    Article  Google Scholar 

  • Kumar PB, Sahu C, Parhi DR, Pandey KK, Chhotray A (2019b) Static and dynamic path planning of humanoids using an advanced regression controller. Sci Iran Trans B Mech Eng 26(1):375–393

    Google Scholar 

  • Kumar PB, Sethy M, Parhi DR (2019c) An intelligent computer vision integrated regression based navigation approach for humanoids in a cluttered environment. Multimedia Tools Appl 78(9):11463–11486

    Article  Google Scholar 

  • Kumar PB, Sahu C, Parhi DR (2020a) Intelligent navigation of a self-fabricated biped robot using a regression controller. Sci Iran 27(1):262–272

    Google Scholar 

  • Kumar PB, Muni MK, Parhi DR (2020b) Navigational analysis of multiple humanoids using a hybrid regression-fuzzy logic control approach in complex terrains. Appl Soft Comput:106088

  • Lamini C, Benhlima S, Elbekri A (2018) Genetic algorithm based approach for autonomous mobile robot path planning. Procedia Comput Sci 127(C):180–189

    Article  Google Scholar 

  • Larik A, Haider S (2019) A framework based on evolutionary algorithm for strategy optimization in robot soccer. Soft Comput 23(16):7287–7302

    Article  Google Scholar 

  • Likaj R, Bajrami X, Shala A, Pajaziti A (2017) Path finding for a mobile robot using fuzzy and genetic algorithms. Int J Mech Eng Technol (IJMET) 8(8):659–669

    Google Scholar 

  • Liu Z, Xu S, Zhang Y, Chen X, Chen CP (2014) Interval type-2 fuzzy kernel based support vector machine algorithm for scene classification of humanoid robot. Soft Comput 18(3):589–606

    Article  Google Scholar 

  • Low ES, Ong P, Cheah KC (2019) Solving the optimal path planning of a mobile robot using improved Q-learning. Robot Auton Syst 115:143–161

    Article  Google Scholar 

  • Manen S, Guillaumin M, Van Gool L (2013) Prime object proposals with randomized prim’s algorithm. In: Proceedings of the IEEE international conference on computer vision, pp 2536–2543

  • Masmoudi MS, Krichen N, Masmoudi M, Derbel N (2016) Fuzzy logic controllers design for omnidirectional mobile robot navigation. Appl Soft Comput 49:901–919

    Article  Google Scholar 

  • Mo H, Xu L (2015) Research of biogeography particle swarm optimization for robot path planning. Neurocomputing 148:91–99

    Article  Google Scholar 

  • Omrane H, Masmoudi MS, Masmoudi M (2016) Fuzzy logic based control for autonomous mobile robot navigation. Comput Intell Neurosci. https://doi.org/10.1155/2016/9548482

    Article  Google Scholar 

  • Pandey A, Parhi DR (2014) MATLAB simulation for mobile robot navigation with hurdles in cluttered environment using minimum rule based fuzzy logic controller. Procedia Technol 14(1):28–34

    Article  Google Scholar 

  • Pandey A, Parhi DR (2017) Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm. Defence Technol 13(1):47–58

    Article  Google Scholar 

  • Pandey A, Kumar S, Pandey KK, Parhi DR (2016) Mobile robot navigation in unknown static environments using ANFIS controller. Perspect Sci 8:421–423

    Article  Google Scholar 

  • Parhi DR (2005) Navigation of mobile robots using a fuzzy logic controller. J Intell Robot Syst 42(3):253–273

    Article  Google Scholar 

  • Parhi DR, Kumar PB (2019) Smart navigation of humanoid robots using DAYKUN-BIP virtual target displacement and Petri-Net strategy. Robotica 37(4):626–640

    Article  Google Scholar 

  • Peterson JL (1981) Petri Net theory and the modeling of systems. Prentice Hall PTR, Upper Saddle River

    MATH  Google Scholar 

  • Pham DT, Parhi DR (2003) Navigation of multiple mobile robots using a neural network and a Petri Net model. Robotica 21(1):79–93

    Article  Google Scholar 

  • Pothal JK, Parhi DR (2015) Navigation of multiple mobile robots in a highly clutter terrains using adaptive neuro-fuzzy inference system. Robot Auton Syst 72:48–58

    Article  Google Scholar 

  • Rath AK, Das HC, Parhi DR, Kumar PB (2018a) Application of artificial neural network for control and navigation of humanoid robot. J Mech Eng Sci 12(2):3529–3538

    Article  Google Scholar 

  • Rath AK, Parhi DR, Das HC, Muni MK, Kumar PB (2018b) Analysis and use of fuzzy intelligent technique for navigation of humanoid robot in obstacle prone zone. Defence Technol 14(6):677–682

    Article  Google Scholar 

  • Sahoo B, Parhi DR, Priyadarshi BK (2018) Analysis of path planning of humanoid robots using neural network methods and study of possible use of other AI techniques. In: Emerging trends in engineering, science and manufacturing (ETESM-2018), IGIT, Sarang, India

  • Sahu C, Parhi DR, Kumar PB (2018) An approach to optimize the path of humanoids using adaptive ant colony optimization. J Bionic Eng 15(4):623–635

    Article  Google Scholar 

  • Seven U, Akbas T, Fidan KC, Erbatur K (2012) Bipedal robot walking control on inclined planes by fuzzy reference trajectory modification. Soft Comput 16(11):1959–1976

    Article  Google Scholar 

  • Vas P, Chen J, Stronach AF (1994) Fuzzy control of AC drives. IET, London

    Book  Google Scholar 

  • Yakoubi MA, Laskri MT (2016) The path planning of cleaner robot for coverage region using genetic algorithms. J Innov Digit Ecosyst 3(1):37–43

    Article  Google Scholar 

Download references

Funding

No funding was received for this research.

Author information

Authors and Affiliations

  1. Robotics Laboratory, Mechanical Engineering Department, National Institute of Technology Rourkela, Rourkela, Odisha, 769008, India

    Manoj Kumar Muni, Dayal R. Parhi & Saroj Kumar

  2. Mechanical Engineering Department, National Institute of Technology Hamirpur, Hamirpur, Himachal Pradesh, 177005, India

    Priyadarshi Biplab Kumar

Authors
  1. Manoj Kumar Muni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dayal R. Parhi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Priyadarshi Biplab Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Saroj Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All the authors contributed equally to the manuscript.

Corresponding author

Correspondence to Manoj Kumar Muni.

Ethics declarations

Conflict of interest

The authors declare no potential conflicts of interests.

Additional information

Communicated by V. Loia.

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

Muni, M.K., Parhi, D.R., Kumar, P.B. et al. Motion control of multiple humanoids using a hybridized prim’s algorithm-fuzzy controller. Soft Comput 25, 1159–1180 (2021). https://doi.org/10.1007/s00500-020-05212-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-020-05212-z

Keywords

Search

Navigation