Abstract
Solving the inverse kinematics of redundant and hyper-redundant manipulators is more challenging because their kinematic redundancy leads to a more complicated mapping from end-effector pose to configuration space. A heuristic inverse kinematics solver, called Forward And Backward Reaching Inverse Kinematics (FABRIK), has been demonstrated to solve the inverse kinematics of complex chain systems with fast convergence and simple implementation. However, as the pose precision of the end-effector increases to a higher value, such as \( 10^{-6} \), FABRIK converges slowly in some configurations and thus exhibits unstable convergence behavior. Hence, this paper presents a novel inverse kinematics algorithm that combines FABRIK and the sequential quadratic programming (SQP) algorithm, in which the joint angles deduced by FABRIK will be taken as the initial seed of the SQP algorithm to realize fast convergence. Meanwhile, a universal and non-trivial mapping from joint Cartesian positions to joint angles is included to enable the extension of FABRIK to redundant and hyper-redundant manipulators while retaining its simplicity. With the \( 10^{-6} \) pose error constraint, quantitative tests on serial chain manipulators demonstrate that the combined algorithm outperforms FABRIK in terms of success rate and runtime. Meanwhile, some popular inverse kinematics algorithms are treated as benchmarks to compare with the combined algorithm. Finally, simulations using serial chain manipulators indicate the effectiveness of the combined algorithm on path tracking.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Wolf, A., Brown, H.B., Casciola, R., Costa, A., Schwerin, M., Shamas, E., Choset, H.: A mobile hyper redundant mechanism for search and rescue tasks. In: Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003)(Cat. No. 03CH37453), vol. 3, pp. 2889–2895 (2003). IEEE. https://doi.org/10.1109/IROS.2003.1249309
Mu, Z., Liu, T., Xu, W., Lou, Y., Liang, B.: A hybrid obstacle-avoidance method of spatial hyper-redundant manipulators for servicing in confined space. Robotica 37(6), 998–1019 (2019). https://doi.org/10.1017/S0263574718001406
Kim, J., Kwon, S.-I., Moon, Y., Kim, K.: Cable-movable rolling joint to expand workspace under high external load in a hyper-redundant manipulator. IEEE/ASME Trans. Mechatron. 27(1), 501–512 (2021). https://doi.org/10.1109/TMECH.2021.3067335
Sadeghian, H., Zokaei, F., Hadian Jazi, S.: Constrained kinematic control in minimally invasive robotic surgery subject to remote center of motion constraint. J. Intell. Robot. Syst. 95(3), 901–913 (2019). https://doi.org/10.1007/s10846-018-0927-0
Aristidou, A., Lasenby, J.: FABRIK: A fast, iterative solver for the inverse kinematics problem. Graph. Model. 73(5), 243–260 (2011). https://doi.org/10.1016/j.gmod.2011.05.003
Aristidou, A., Chrysanthou, Y., Lasenby, J.: Extending FABRIK with model constraints. Comput. Animat. Virtual Worlds 27(1), 35–57 (2016). http://dx.doi.org/10.1002/cav.1630
Beeson, P., Ames, B.: TRAC-IK: An open-source library for improved solving of generic inverse kinematics. In: 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), pp. 928–935 (2015). IEEE. https://doi.org/10.1109/HUMANOIDS.2015.7363472
Marić, F., Giamou, M., Hall, A.W., Khoubyarian, S., Petrović, I., Kelly, J.: Riemannian optimization for distance-geometric inverse kinematics. IEEE Trans. Robot. 38(3), 1703–1722 (2021). https://doi.org/10.1109/TRO.2021.3123841
Ananthanarayanan, H., Ordóñez, R.: Real-time inverse kinematics of (2n+1) DOF hyper-redundant manipulator arm via a combined numerical and analytical approach. Mech. Mach. Theory 91, 209–226 (2015). https://doi.org/10.1016/j.mechmachtheory.2015.04.011
Lloyd, S., Irani, R.A., Ahmadi, M.: Fast and robust inverse kinematics of serial robots using halley’s method. IEEE Trans. Robot. 38(5), 2768–2780 (2022). https://doi.org/10.1109/TRO.2022.3162954
Zhao, J., Xu, Z., Zhao, L., Li, Y., Ma, L., Liu, H.: A novel inverse kinematics for solving repetitive motion planning of 7-DOF SRS manipulator. Robotica. 1–18 (2022). https://doi.org/10.1017/S0263574722001370
Long, M.K.: Task-directed inverse kinematics for redundant manipulators. J. Intell. Robot. Syst. 6(2), 241–261 (1992). https://doi.org/10.1007/BF00248018
Karpińska, J., Tchoń, K., Janiak, M.: Approximation of jacobian inverse kinematics algorithms: differential geometric vs. variational approach. J. Intell. Robot. Syst. 68(3), 211–224 (2012). https://doi.org/10.1007/s10846-012-9679-4
Orocos kinematics and dynamics. [Online]. https://www.orocos.org/kdl.html. Accessed 20 Dec 2022
Fletcher, R.: Practical Methods of Optimization, 2nd edn. John Wiley & Sons (1987)
Xie, S., Sun, L., Wang, Z., Chen, G.: A speedup method for solving the inverse kinematics problem of robotic manipulators. Int. J. Adv. Rob. Syst. 19(3), 1–10 (2022). https://doi.org/10.1177/17298806221104602
Shirafuji, S., Ota, J.: Kinematic synthesis of a serial robotic manipulator by using generalized differential inverse kinematics. IEEE Trans. Robot. 35(4), 1047–1054 (2019). https://doi.org/10.1109/TRO.2019.2907810
Wang, L.-C., Chen, C.-C.: A combined optimization method for solving the inverse kinematics problems of mechanical manipulators. IEEE Trans. Robot. Autom. 7(4), 489–499 (1991). https://doi.org/10.1109/70.86079
Martin, A., Barrientos, A., Del Cerro, J.: The Natural-CCD algorithm, a novel method to solve the inverse kinematics of hyper-redundant and soft robots. Soft Robot. 5(3), 242–257 (2018). https://doi.org/10.1089/soro.2017.0009
Tao, S., Yang, Y.: Collision-free motion planning of a virtual arm based on the FABRIK algorithm. Robotica 35(6), 1431–1450 (2017). https://doi.org/10.1017/S0263574716000205
Tao, S., Tao, H., Yang, Y.: Extending FABRIK with obstacle avoidance for solving the inverse kinematics problem. J. Rob. 2021 (2021). https://doi.org/10.1155/2021/5568702
Gangqi, D., Panfeng, H., Yongjie, W., Rongsheng, L.: A modified forward and backward reaching inverse kinematics based incremental control for space manipulators. Chinese J. Aeronaut. (2021). https://doi.org/10.1016/j.cja.2021.08.014
Kolpashchikov, D.Y., Laptev, N.V., Danilov, V.V., Skirnevskiy, I.P., Manakov, R.A., Gerget, O.M.: FABRIK-based inverse kinematics for multi-section continuum robots. In: 2018 18th International Conference on Mechatronics-Mechatronika (ME), pp. 1–8. IEEE (2018)
Wu, H., Yu, J., Pan, J., Li, G., Pei, X.: CRRIK: A fast heuristic algorithm for the inverse kinematics of continuum robot. J. Intell. Robot. Syst. 105(3), 1–21 (2022). https://doi.org/10.1007/s10846-022-01672-7
Santos, P.C., Freire, R.C.S., Carvalho, E.A.N., Molina, L., Freire, E.O.: M-FABRIK: A new inverse kinematics approach to mobile manipulator robots based on FABRIK. IEEE Access 8, 208836–208849 (2020). https://doi.org/10.1109/ACCESS.2020.3038424
Xie, Y., Zhang, Z., Wu, X., Shi, Z., Chen, Y., Wu, B., Mantey, K.A.: Obstacle avoidance and path planning for multi-joint manipulator in a space robot. IEEE Access 8, 3511–3526 (2019). https://doi.org/10.1109/ACCESS.2019.2961167
Wang, Y., Zhao, C., Wang, X., Zhang, P., Li, P., Liu, H.: Inverse kinematics of a 7-DOF spraying robot with 4R 3-DOF non-spherical wrist. J. Intell. Robot. Syst. 101(4), 1–17 (2021). https://doi.org/10.1007/s10846-021-01338-w
Chirikjian, G.S., Burdick, J.W.: A modal approach to hyper-redundant manipulator kinematics. IEEE Trans. Robot. Autom. 10(3), 343–354 (1994). https://doi.org/10.1109/70.294209
Zaplana, I., Hadfield, H., Lasenby, J.: Closed-form solutions for the inverse kinematics of serial robots using conformal geometric algebra. Mech. Mach. Theory 173, 104835 (2022). https://doi.org/10.1016/j.mechmachtheory.2022.104835
Diankov, R.: Automated construction of robotic manipulation programs. PhD dissertation, Carnegie Mellon Univ. (2010)
Shimizu, M., Kakuya, H., Yoon, W.-K., Kitagaki, K., Kosuge, K.: Analytical inverse kinematic computation for 7-DOF redundant manipulators with joint limits and its application to redundancy resolution. IEEE Trans. Robot. 24(5), 1131–1142 (2008). https://doi.org/10.1109/TRO.2008.2003266
Yang, X., Zhao, Z., Xu, Z., Li, Y., Zhao, J., Liu, H.: General inverse kinematics method for 7-DOF offset manipulators based on arm angle parameterization. Acta Astronaut. 202, 263–277 (2023). https://doi.org/10.1016/j.actaastro.2022.10.026
Xu, W., Mu, Z., Liu, T., Liang, B.: A modified modal method for solving the mission-oriented inverse kinematics of hyper-redundant space manipulators for on-orbit servicing. Acta Astronaut. 139, 54–66 (2017). https://doi.org/10.1016/j.actaastro.2017.06.015
Parker, J.K., Khoogar, A.R., Goldberg, D.E.: Inverse kinematics of redundant robots using genetic algorithms. In: 1989 IEEE International Conference on Robotics and Automation, pp. 271–272. IEEE Computer Society (1989). https://doi.org/10.1109/ROBOT.1989.100000
Morell, A., Tarokh, M., Acosta, L.: Inverse kinematics solutions for serial robots using support vector regression. In: 2013 IEEE International Conference on Robotics and Automation, pp. 4203–4208. IEEE (2013). https://doi.org/10.1109/ICRA.2013.6631171
Falconi, R., Grandi, R., Melchiorri, C.: Inverse kinematics of serial manipulators in cluttered environments using a new paradigm of particle swarm optimization. IFAC Proc. 47(3), 8475–8480 (2014). https://doi.org/10.3182/20140824-6-ZA-1003.01094
Starke, S., Hendrich, N., Magg, S., Zhang, J.: An efficient hybridization of genetic algorithms and particle swarm optimization for inverse kinematics. In: 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 1782–1789. IEEE (2016). https://doi.org/10.1109/ROBIO.2016.7866587
Starke, S., Hendrich, N., Krupke, D., Zhang, J.: Evolutionary multi-objective inverse kinematics on highly articulated and humanoid robots. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 6959–6966. IEEE (2017). https://doi.org/10.1109/IROS.2017.8206620
Starke, S., Hendrich, N., Zhang, J.: Memetic evolution for generic full-body inverse kinematics in robotics and animation. IEEE Trans. Evol. Comput. 23(3), 406–420 (2018). https://doi.org/10.1109/TEVC.2018.2867601
Marconi, G.M., Camoriano, R., Rosasco, L., Ciliberto, C.: Structured prediction for CRiSP inverse kinematics learning with misspecified robot models. IEEE Robot. Autom. Lett. 6(3), 5650–5657 (2021). https://doi.org/10.1109/LRA.2021.3063978
Xie, Z., Jin, L., Luo, X., Hu, B., Li, S.: An acceleration-level data-driven repetitive motion planning scheme for kinematic control of robots with unknown structure. IEEE Trans. Syst. Man Cybern. Syst. (2021). https://doi.org/10.1109/TSMC.2021.3129794
Kraft, D.: A software package for sequential quadratic programming. Forschungsbericht- Deutsche Forschungs- und Versuchsanstalt fur Luft- und Raumfahrt (1988)
Paul, R.P.: Robot Manipulators: Mathematics, Programming, and Control: the Computer Control of Robot Manipulators. MIT Press (1981)
Zhao, J., Zhao, Z., Yang, X., Zhao, L., Yang, G., Liu, H.: Inverse kinematics and workspace analysis of a novel SSRMS-type reconfigurable space manipulator with two lockable passive telescopic links. Mech. Mach. Theory 180, 105152 (2023). https://doi.org/10.1016/j.mechmachtheory.2022.105152
Yoshikawa, T.: Manipulability of robotic mechanisms. Int. J. Rob. Res. 4(2), 3–9 (1985). https://doi.org/10.1177/027836498500400201
Lynch, K.M., Park, F.C.: Modern Robotics: Mechanics, Planning, and Control. Cambridge University Press (2017)
Dufour, K., Suleiman, W.: On maximizing manipulability index while solving a kinematics task. J. Intell. Robot. Syst. 100, 3–13 (2020). https://doi.org/10.1007/s10846-020-01171-7
Jin, L., Li, S., La, H.M., Luo, X.: Manipulability optimization of redundant manipulators using dynamic neural networks. IEEE Trans. Ind. Electron. 64(6), 4710–4720 (2017). https://doi.org/10.1109/TIE.2017.2674624
Funding
This work has been supported by the National Natural Science Foundation of China [Project Number: 92148203], the State Key Laboratory of Robotics and System (HIT) [Project Number: SKLRS202201A01], and the Key Lab. of Science and Technology on Space Flight Dynamics [Project Number: XTB6142210210303].
Author information
Authors and Affiliations
Contributions
Zichun Xu: Conceptualization, Implementation, Analysis, and Writing. Yuntao Li, Xiaohang Yang, and Zhiyuan Zhao: Discussion, Writing, Editing, and Reviewing. Jingdong Zhao and Hong Liu: Supervision and Finalizing.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix A: DH Parameters for 7-, 9-, and 15-DOF Serial Chain Arms
Appendix A: DH Parameters for 7-, 9-, and 15-DOF Serial Chain Arms
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Xu, Z., Li, Y., Yang, X. et al. A Combined Inverse Kinematics Algorithm Using FABRIK with Optimization. J Intell Robot Syst 108, 62 (2023). https://doi.org/10.1007/s10846-023-01895-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10846-023-01895-2