DOI: 10.5937/jaes0-30557

This is an open access article distributed under the CC BY 4.0

Volume 19 article 832 pages: 592-599

Finding the inverse kinematic solution of a serial manipulator has always attracted the attention of optimization enthusiasts, as the solution space is highly nonlinear and, depending on the number of degrees of freedom, has multiple solutions. In the literature, one can find several proposed solutions using heuristic techniques; however, for highly redundant manipulators, e.g., seven or more, the discussions focused on minimizing the positional error. In this paper,a metaheuristic approach is presented to solve not only the inverse kinematics of a 7 and 8 DOF manipulators but the proposed algorithm is used to find the robot’s poses for trajectory planning where the robot is required to meet the desired position and orientation based on quaternion representation of each point along the path. The metaheuristic approach used in this paper is particle swarm optimization (PSO), where the unit quaternion is used in the objective function to find the orientation error. The results prove that the use of the unit quaternion representation improved the performance of the algorithm and that our approach can be used not only for individual poses but for trajectory planning.

The authors would like to thank theInstituto Politécnico Nacionalfor the funding of this work through project SIP20200631.

1. Dereli, S., Köker, R. A meta-heuristic proposal for inverse kinematics solution of 7-DOF serial robotic manipulator: quantum behaved particle swarm algorithm. Artif Intell Rev 53, 949–964 (2020). https://doi.org/10.1007/s10462-019-09683-x

2. C. Tsai, C. Hung and C. Chang, "Trajectory planning and control of a 7-DOF robotic manipulator," 2014 International Conference on Advanced Robotics and Intelligent Systems (ARIS), Taipei, 2014, pp. 78-84, doi: 10.1109/ARIS.2014.6871496.

3. Dereli, S., Köker, R. Simulation based calculation of the inverse kinematics solution of 7-DOF robot manipulator using artificial bee colony algorithm. SN Appl. Sci. 2, 27 (2020). https://doi.org/10.1007/s42452-019-1791-7

4. M. Alkayyali and T. A. Tutunji, "PSO-based Algorithm for Inverse Kinematics Solution of Robotic Arm Manipulators," 2019 20th International Conference on Research and Education in Mechatronics (REM), Wels, Austria, 2019, pp. 1-6, doi: 10.1109/REM.2019.8744103.

5. Zhang, L., Xiao, N. A novel artificial bee colony algorithm for inverse kinematics calculation of 7-DOF serial manipulators. Soft Comput 23, 3269–3277 (2019). https://doi.org/10.1007/s00500-017-2975-y

6. Z. Zeng, Z. Chen, G. Shu and Q. Chen, "Optimization of analytical inverse kinematic solution for redundant manipulators using GA-PSO algorithm," 2018 IEEE Industrial Cyber-Physical Systems (ICPS), St. Petersburg, 2018, pp. 446-451, doi: 10.1109/ICPHYS.2018.8390746.

7. A. Umar, Z. Shi, W. Wang and Z. I. B. Farouk, "A Novel Mutating PSO Based Solution For Inverse Kinematic Analysis Of Multi Degree-Of-Freedom Robot Manipulators," 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), Dalian, China, 2019, pp. 459-463, doi: 10.1109/ICAICA.2019.8873449.

8. Serkan Dereli & Raşit Köker (2020) 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, Inverse Problems in Science and Engineering, 28:5, 601-613, DOI: 10.1080/17415977.2019.1602124

9. S. V. Reyes and S. P. Gardini, "Inverse kinematics of Manipulator Robot using a PSO Metaheuristic with Adaptively Exploration," 2019 IEEE XXVI International Conference on Electronics, Electrical Engineering and Computing (INTERCON), Lima, Peru, 2019, pp. 1-4, doi: 10.1109/INTERCON.2019.8853568.

10. Nguyen M.T., Yuan C., Huang J.H. (2019) Kinematic Analysis of A 6-DOF Robotic Arm. In: Uhl T. (eds) Advances in Mechanism and Machine Science. IFToMM WC 2019. Mechanisms and Machine Science, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-030-20131-9_292

11. R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995, pp. 39-43, doi: 10.1109/MHS.1995.494215.

12. Burke, Edmund K., and Graham Kendall, eds. “Search Methodologies” (2014). doi:10.1007/978-1-4614-6940-7.