Visual Servoing of a 3R Robot by Metaheuristic Algorithms

  • Inssaf HARRADE National School of Applied Sciences, Sidi Mohamed Ben Abdellah-Fez University, Engineering Systems and Applications Laboratory, Fez, Morocco.
  • Achraf DAOUI National School of Applied Sciences, Sidi Mohamed Ben Abdellah-Fez University, Engineering Systems and Applications Laboratory, Fez, Morocco.
  • Zakaria CHALH National School of Applied Sciences, Sidi Mohamed Ben Abdellah-Fez University, Engineering Systems and Applications Laboratory, Fez, Morocco.
  • Mhamed SAYYOURI National School of Applied Sciences, Sidi Mohamed Ben Abdellah-Fez University, Engineering Systems and Applications Laboratory, Fez, Morocco.
Keywords: Metaheuristic algorithms, 3R robot, joint position, visual servoing, optimal trajectory.

Abstract

In planar robot control, the singularity problem is frequently encountered when determining the geometric or kinematic robot model. To overcome this problem, a new method is presented in this paper. Indeed, this method is used to compute the joint positions of 3R robots with high accuracy. The main idea of the proposed method is to use a metaheuristic algorithm for retrieving the coordinates of four reference points in the object image that is captured by a hand-eye camera of the 3R robot. Then, the joint positions are estimated by using a metaheuristic algorithm. The resulting positions are then used for controlling the 3R robot for moving to the desired position. The simulation experiments are conducted by using several metaheuristic algorithms with the same population size (N = 400). The obtained results show the high accuracy of the proposed method in terms of determining the exact positions of the 3R robot joints, which leads to finding the optimal robot trajectory.

References

S.Wang, K.Zhang, G.Herrmann, An Adaptive Controller for Robotic Manipulators with Unknown Kinematics and Dynamics, IFACPapersOnLine 53:8796–8801. https://doi.org/10.1016/j.ifacol.2020.12.1385, 2020.

Y.Shirai, H.Inoue , Guiding a robot by visual feedback in assembling tasks, Pattern recognition 5:99–108, 1973.

J.Landuré , Etude du lieu des singularités d’un manipulateur parallèle sphérique redondant, PhD Thesis, Université Laval, 2017.

M.Furet , Analyse cinétostatique de mécanismes de tenségrité: Application à la modélisation de cous d’oiseaux et de manipulateurs bio-inspirés, PhD Thesis, Ecole Centrale de Nantes, 2020.

A.Liégeois , Modélisation et commande des robots manipulateurs, Techniques de l’Ingénieur, S 7:730, 2000.

D.Chablat, R.Jha, F.Rouillier, G.Moroz, Non-singular assembly mode changing trajectories in the workspace for the 3-RPS parallel robot, In: Advances in Robot Kinematics. Springer, pp 149–159, 2014.

D.Chablat, P.Wenger , Séparation des solutions aux modèles géomètriques direct et inverse pour les manipulateurs pleinement parallèles, Mechanism and Machine Theory 36:763–783, 2001.

AC.Reddy , Difference between Denavit-Hartenberg (DH) classical and modified conventions for forwarding kinematics of robots with a case study, In: International Conference on Advanced Materials and Manufacturing Technologies (AMMT). JNTUH College of Engineering Hyderabad Chandigarh, India, pp 267–286, 2014.

R.Fleurmond , Asservissement visuel coordonné de deux bras manipulateurs, PhD Thesis, Universite Toulouse III Paul Sabatier, 2015.

AY.Tamtsia , Nouvelles contributions `a l’application des moments en asservissement visuel, PhD Thesis, Universit´e Blaise Pascal- Clermont-Ferrand II, 2013.

IH.Aguilar , Commande des bras manipulateurs et retour visuel pour des applications `a la robotique de service, PhD Thesis, Thèse de doctorat, Université Toulouse III, 2007.

A.Krupa , Contributions à l’asservissement visuel échographique, SPhD Thesis, Université Rennes 1, 2012.

Z.Li, Q.Chen, V.Koltun, Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search, In Advances in Neural Information Processing Systems. Curran Associates, Inc, 2018.

F.Gueye , Algorithmes de recherche d’itinéraires en transport multimodal, PhD Thesis, Toulouse, INSA, 2010.

T.Dokeroglu, E.Sevinc, T.Kucukyilmaz, A.Cosar , A survey on new generation metaheuristic algorithms, Computers & Industrial Engineering 137:106040. https://doi.org/10.1016/j.cie.2019.106040, 2019.

X-S.Yang, Harmony search as a metaheuristic algorithm, In Music-inspired harmony search algorithm. Springer, pp 1–14, 2009.

SO.Degertekin , Improved harmony search algorithms for sizing optimization of truss structures Computers & Structures 92:229–241, 2012.

D.Karaboga, B.Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, Journal of global optimization 39:459–471, 2007.

R.Rao , Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems, Decision science letters 5:1–30, 2016.

AH.Gandomi, X-S.Yang, AH.Alavi, Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems, Engineering with computers 29:17–35, 2013.

Published
2023-01-23
How to Cite
HARRADE, I., DAOUI, A., CHALH, Z., & SAYYOURI, M. (2023). Visual Servoing of a 3R Robot by Metaheuristic Algorithms. Statistics, Optimization & Information Computing, 11(1), 116-124. https://doi.org/10.19139/soic-2310-5070-1552
Section
Research Articles