Calculation of the inverse kinematics solution of the 7-DOF redundant robot manipulator by the firefly algorithm and statistical analysis of the results in terms of speed and accuracy

ABSTRACT In this study, the inverse kinematics solution of a 7-DOF redundant robot manipulator was performed by using firefly algorithm that is a swarm optimization technique. In order to show the power of this technique, a redundant robotic arm which is inadequate inverse kinematic solution by conventional methods has been chosen. Both speed and accuracy are two important factors in robotic studies. For this reason, the comparison of the method used in this study in terms of speed and accuracy has been carried out in depth. The scenario used is as follows: Firstly, the position equations of this manipulator are derived with the DH parameters. Afterward, the position of the end effector is obtained in the work space according to the forward kinematic calculation. Finally, the joint angles that will be directed to the calculated position values with the least error are obtained by the firefly algorithm and the obtained result is compared with other swarm algorithms such as particle swarm optimization and artificial bee colony.

[1]  Lingling Huang,et al.  A global best artificial bee colony algorithm for global optimization , 2012, J. Comput. Appl. Math..

[2]  Tugrul Cavdar,et al.  A New Heuristic Approach for Inverse Kinematics of Robot Arms , 2013 .

[3]  Pedram Masajedi,et al.  Verification of bee algorithm based path planning for a 6DOF manipulator using ADAMS , 2013 .

[4]  Dervis Karaboga,et al.  A comprehensive survey: artificial bee colony (ABC) algorithm and applications , 2012, Artificial Intelligence Review.

[5]  Oscar Castillo,et al.  Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot , 2016, Sensors.

[6]  Li Zhang,et al.  A novel artificial bee colony algorithm for inverse kinematics calculation of 7-DOF serial manipulators , 2017, Soft Computing.

[7]  Simon X. Yang,et al.  Bioinspired Intelligent Algorithm and Its Applications for Mobile Robot Control: A Survey , 2015, Comput. Intell. Neurosci..

[8]  Dervis Karaboga,et al.  A survey: algorithms simulating bee swarm intelligence , 2009, Artificial Intelligence Review.

[9]  Rasit Köker,et al.  A neuro-genetic-simulated annealing approach to the inverse kinematics solution of robots: a simulation based study , 2015, Engineering with Computers.

[10]  Dayal R. Parhi,et al.  Advancement in navigational path planning of robots using various artificial and computing techniques , 2018, ICRA 2018.

[11]  Bibhuti Bhusan Biswal,et al.  Prediction of Inverse Kinematics for a 6-DOF Industrial Robot Arm Using Soft Computing Techniques , 2017, SocProS.

[12]  Rajeevlochana G. Chittawadigi,et al.  RoboAnalyzer: Robot Visualization Software for Robot Technicians , 2017, AIR '17.

[13]  Xin-She Yang,et al.  A Novel Hybrid Firefly Algorithm for Global Optimization , 2016, PloS one.

[14]  V. N. Iliukhin,et al.  The Modeling of Inverse Kinematics for 5 DOF Manipulator , 2017 .

[15]  Nicolas Mansard,et al.  Trajectory generation for quadrotor based systems using numerical optimal control , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[16]  Serkan Dereli,et al.  A meta-heuristic proposal for inverse kinematics solution of 7-DOF serial robotic manipulator: quantum behaved particle swarm algorithm , 2019, Artificial Intelligence Review.

[17]  Andries Petrus Engelbrecht,et al.  Inertia weight control strategies for particle swarm optimization , 2016, Swarm Intelligence.

[18]  Janez Brest,et al.  A comprehensive review of firefly algorithms , 2013, Swarm Evol. Comput..

[19]  Amrit Pal Singh,et al.  Comparative Study of Firefly Algorithm and Particle Swarm Optimization for Noisy Non- Linear Optimization Problems , 2012 .

[20]  Serdar Kucuk,et al.  Energy minimization for 3-RRR fully planar parallel manipulator using particle swarm optimization , 2013 .

[21]  A. Alimi,et al.  Inverse Kinematics Using Particle Swarm Optimization, A Statistical Analysis , 2013 .

[22]  Sanyang Liu,et al.  Improved artificial bee colony algorithm for global optimization , 2011 .

[23]  Gisele L. Pappa,et al.  An ant colony-based semi-supervised approach for learning classification rules , 2015, Swarm Intelligence.

[24]  Kerim Çetinkaya,et al.  Comparison of four different heuristic optimization algorithms for the inverse kinematics solution of a real 4-DOF serial robot manipulator , 2015, Neural Computing and Applications.

[25]  Adel M. Alimi,et al.  IK-FA, a New Heuristic Inverse Kinematics Solver Using Firefly Algorithm , 2015, Computational Intelligence Applications in Modeling and Control.

[26]  Xin-She Yang,et al.  Firefly Algorithm: Recent Advances and Applications , 2013, ArXiv.

[27]  Mostafa A. El-Hosseini,et al.  A new ABC variant for solving inverse kinematics problem in 5 DOF robot arm , 2018, Appl. Soft Comput..

[28]  T. Latty,et al.  Collective behaviour and swarm intelligence in slime moulds. , 2016, FEMS microbiology reviews.

[29]  Sunil Kumar Kashyap,et al.  On firefly algorithm: optimization and application in mobile robot navigation , 2017 .

[30]  Peng Zhang,et al.  Characterizing and Modeling the Dynamics of Activity and Popularity , 2013, PloS one.

[31]  Carlos Martín-Vide,et al.  Special Issue on Second International Conference on the Theory and Practice of Natural Computing, TPNC 2013 , 2016, Soft Comput..

[32]  S. G. Ponnambalam,et al.  Obstacle avoidance control of redundant robots using variants of particle swarm optimization , 2012 .

[33]  Hui Wang,et al.  Firefly algorithm with neighborhood attraction , 2017, Inf. Sci..

[34]  Anish Pandey,et al.  Path planning in uncertain environment by using firefly algorithm , 2018, Defence Technology.

[35]  R. L. Jhala,et al.  Optimal Motion Planning For a Robot Arm by Using Artificial Bee Colony ( ABC ) Algorithm , 2012 .

[36]  Thomas Stützle,et al.  Ant Colony Optimization: Overview and Recent Advances , 2018, Handbook of Metaheuristics.

[37]  Changhe Li,et al.  A survey of swarm intelligence for dynamic optimization: Algorithms and applications , 2017, Swarm Evol. Comput..

[38]  Katia P. Sycara,et al.  Human Interaction With Robot Swarms: A Survey , 2016, IEEE Transactions on Human-Machine Systems.

[39]  Hui Wang,et al.  Randomly attracted firefly algorithm with neighborhood search and dynamic parameter adjustment mechanism , 2017, Soft Comput..

[40]  Serkan Dereli In a research on how to use inverse kinematics solution of actual intelligent optimization method , 2016 .

[41]  Christian Blum,et al.  Swarm Intelligence in Optimization and Robotics , 2015, Handbook of Computational Intelligence.

[42]  Xin-She Yang,et al.  Firefly Algorithm, Lévy Flights and Global Optimization , 2010, SGAI Conf..

[43]  Hui Wang,et al.  Firefly algorithm with adaptive control parameters , 2016, Soft Computing.

[44]  Pasquale Chiacchio,et al.  Topological Analysis of Global Inverse Kinematic Solutions for Redundant Manipulators , 2019 .

[45]  Bijaya K. Panigrahi,et al.  A hybridization of an improved particle swarm optimization and gravitational search algorithm for multi-robot path planning , 2016, Swarm Evol. Comput..

[46]  Arpan Kumar Kar,et al.  Swarm Intelligence: A Review of Algorithms , 2017 .

[47]  Gustavo Scaglia,et al.  Interpolation Based Controller for Trajectory Tracking in Mobile Robots , 2017, J. Intell. Robotic Syst..