Analysis of Hybrid Technique for Motion Planning of Humanoid NAO

(1) * Abhishek Kumar Kashyap Mail (Robotics Laboratory, Mechanical Engineering Department, National Institute of Technology, Rourkela, India)
(2) Dayal R. Parhi Mail (Robotics Laboratory, Mechanical Engineering Department, National Institute of Technology, Rourkela, India)
(3) Anish Pandey Mail (School of Mechanical Engineering, Kalinga Institute of Industrial Technology, India)
*corresponding author

Abstract


The navigation of a humanoid robot is essential because it is the basic requirement of any assigned task. Singly used motion planning techniques may take a long path to reach the target and increase the computational cost. Therefore, in this article, a hybrid controller is employed in the humanoid NAO for motion planning assignment. The Eagle strategy (ES) with Ant colony optimization (ACO) is introduced in this article for evaluating precise steering angles for humanoid robots as they traverse a route from a reference point to a target point. This enables the robot to achieve its specific target more quickly by avoiding barriers and obtaining the minimal global direction. The hybridized ES-ACO approach is critical in determining precise steering angles to escape obstacles.  The details of terrain are obtained using vision and ultrasonic sensors, which also include the barriers ranges to the ES as an input variable. The ES's input parameters are the barrier ranges from the NAO in front, left, and right directions, and the technique's output variable is the precise steering angle. The designed controller is tested in both a simulation and an experimental setting with a variety of obstacles. The outcomes of both simulation and experimental conditions are compared, and a strong correlation is identified in those with the fewest deviations.

Keywords


Humanoid NAO; Webots; Eagle strategy; Ant colony optimization

   

DOI

https://doi.org/10.31763/ijrcs.v1i1.285
      

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References


[1] A. K. Kashyap, D. R. Parhi, and S. Kumar, "Dynamic Stabilization of NAO Humanoid Robot Based on Whole-Body Control with Simulated Annealing," Int. J. Humanoid Robot., vol. 17, no. 03, p. 2050014, 2020. https://doi.org/10.1142/S0219843620500140

[2] A. K. Kashyap and A. Pandey, "Different Nature-Inspired Techniques Applied for Motion Planning of Wheeled Robot: A Critical Review," Int. J. Adv. Robot. Autom., vol. 3, no. 2, pp. 1–10, 2018. https://doi.org/10.15226/2473-3032/3/2/00136

[3] K. P. Lagaza, A. K. Kashyap, and A. Pandey, "Spider Monkey Optimization Algorithm Based Collision-Free Navigation and Path Optimization for a Mobile Robot in the Static Environment," in Advances in Mechanical Engineering, 2020, pp. 1459–1473. https://doi.org/10.1007/978-981-15-0124-1_128

[4] A. K. Kashyap, A. Pandey, A. Chhotray, and D. R. Parhi, "Controlled Gait Planning of Humanoid Robot NAO Based on 3D-LIPM Model," SSRN Electron. J., 2020. https://doi.org/10.2139/ssrn.3552498

[5] A. K. Kashyap and A. Pandey, "Optimized Path Planning for Three-Wheeled Autonomous Robot Using Teaching–Learning-Based Optimization Technique," in Advances in Materials and Manufacturing Engineering, 2020, pp. 49–57. https://doi.org/10.1007/978-981-15-1307-7_5

[6] A. K. Kashyap, K. Pirewa Lagaza, and A. Pandey, "Dynamic Path Planning for Autonomous Mobile Robot using Minimum Fuzzy Rule Based Controller with Avoidance of Moving Obstacles," in 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE), 2018, pp. 3330–3335. https://doi.org/10.1109/ICRIEECE44171.2018.9009120

[7] D. Murray and C. Jennings, "Stereo vision based mapping and navigation for mobile robots," Proceedings of International Conference on Robotics and Automation, Albuquerque, NM, USA, 1997, vol. 2, 1997, pp. 1694-1699. https://doi.org/10.1109/ROBOT.1997.614387

[8] B.B.V.L. Deepak, D.R. Parhi, S. Kundu, "Innate Immune based Path Planner of an Autonomous Mobile Robot," Procedia Eng., vol. 38, 2012, pp. 2663–2671. https://doi.org/10.1016/j.proeng.2012.06.313

[9] J.-A. Meyer and D. Filliat, "Map-based navigation in mobile robots," Cogn. Syst. Res., vol. 4, no. 4, pp. 283–317, 2003. https://doi.org/10.1016/S1389-0417(03)00007-X

[10] K. H. Kowdiki, R. K. Barai, and S. Bhattacharya, "Leader-follower formation control using artificial potential functions: A kinematic approach," IEEE-International Conf. Adv. Eng. Sci. Manag. ICAESM-2012, pp. 500–505, 2012. https://ieeexplore.ieee.org/abstract/document/6216054

[11] P. Shi and Y. Zhao, "An efficient path planning algorithm for mobile robot using improved potential field," in 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2009, pp. 1704–1708. https://doi.org/10.1109/ROBIO.2009.5420407

[12] J. Sfeir, M. Saad, and H. Saliah-Hassane, "An improved Artificial Potential Field approach to real-time mobile robot path planning in an unknown environment," ROSE 2011 - IEEE Int. Symp. Robot. Sensors Environ. Proc., pp. 208–213, 2011. https://doi.org/10.1109/ROSE.2011.6058518

[13] H. Choset and P. Pignon, "Coverage Path Planning: The Boustrophedon Cellular Decomposition," F. Serv. Robot., pp. 203–209, 1998. https://doi.org/10.1007/978-1-4471-1273-0_32

[14] L. E. Kavraki, P. Švestka, J. C. Latombe, and M. H. Overmars, "Probabilistic roadmaps for path planning in high-dimensional configuration spaces," IEEE Trans. Robot. Autom., vol. 12, no. 4, pp. 566–580, 1996. https://doi.org/10.1109/70.508439

[15] T. A. Cargill, "A robust distributed solution to the dining philosophers problem," Softw. Pract. Exp., vol. 12, no. 10, pp. 965–969, 1982. https://doi.org/10.1002/spe.4380121009

[16] H. Wedde, "A starvation-free solution of the dining philosophers' problem by use of interaction systems," in International Symposium on Mathematical Foundations of Computer Science, 1981, pp. 534–543. https://doi.org/10.1007/3-540-10856-4_122

[17] A. Pandey, A. K. Kashyap, D. R. Parhi, and B. K. Patle, "Autonomous mobile robot navigation between static and dynamic obstacles using multiple ANFIS architecture," World J. Eng., vol. 16, no. 2, pp. 275–286, 2019. https://doi.org/10.1108/WJE-03-2018-0092

[18] A. K. Kashyap, D. R. Parhi, M. K. Muni, and K. K. Pandey, "A hybrid technique for path planning of humanoid robot NAO in static and dynamic terrains," Appl. Soft Comput., vol. 96, p. 106581, 2020. https://doi.org/10.1016/j.asoc.2020.106581

[19] A. K. Kashyap, D. Parhi, and A. Pandey, "Improved Modified Chaotic Invasive Weed Optimization Approach to Solve Multi-Target Assignment for Humanoid Robot," J. Robot. Control, vol. 2, no. 3, pp. 194–199, 2021. https://doi.org/10.18196/jrc.2377

[20] A. K. Kashyap and D. R. Parhi, "Dynamic walking of humanoid robot on flat surface using amplified LIPM plus flywheel model," International Journal of Intelligent Unmanned Systems, vol. ahead-of-p, no. ahead-of-print. 2021. https://doi.org/10.1108/IJIUS-09-2020-0039

[21] A. K. Kashyap and D. R. Parhi, "Particle Swarm Optimization aided PID gait controller design for a humanoid robot," ISA Trans., 2020. https://doi.org/10.1016/j.isatra.2020.12.033

[22] H. Yapıcı and N. Çetinkaya, "An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization," Math. Probl. Eng., vol. 2017, pp. 1–11, 2017. https://doi.org/10.1155/2017/1063045

[23] M. Dorigo, V. Maniezzo, and A. Colorni, "Ant system: Optimization by a colony of cooperating agents," IEEE Trans. Syst. Man, Cybern. Part B Cybern., vol. 26, no. 1, pp. 29–41, 1996. https://doi.org/10.1109/3477.484436

[24] A. K. Kashyap and D. R. Parhi, "Optimization of stability of humanoid robot NAO using ant colony optimization tuned MPC controller for uneven path," Soft Comput., vol. 1, 2021. https://doi.org/10.1007/s00500-020-05515-1


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International Journal of Robotics and Control Systems
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