Abstract
The selection of an optimal solution from multiple inverse kinematics solutions (IKSs) is a fundamental task in manipulator motion. However, the conventional minimum joint motion criterion (MJM) method suffers from drawbacks such as high computational time and the inability to ensure configuration invariance. With the prevalence of noncuspidal structures in commercial manipulators, a novel IKS selection methodology is exigent. This paper analyzes the limitations of the MJM method by geometric representations of the IKS formal and proposes a novel IKS selection method based on configuration space decomposition. The configuration space of noncuspidal manipulators is partitioned into independent subdomains called uniqueness domains (UD). Subsequently, a bijection between configuration, UD, and IKS is established for selecting IKS, and three important related theorems are proven. The proposed method offers low computational cost, and allows configuration invariance in continuous trajectory tracking or point-to-point planning. Finally, the physical experiment results demonstrate the effectiveness of the proposed method.
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Fu, Z., Yang, W., Yang, Z.: Solution of inverse kinematics for 6r robot manipulators with offset wrist based on geometric algebra. J. Mech. Robot. 5, 031010 (2013). https://doi.org/10.1115/1.4024239
Jiokou Kouabon, A.G., Melingui, A., Mvogo Ahanda, J.J.B., Lakhal, O., Coelen, V., KOM, M., Merzouki, R.: A learning framework to inverse kinematics of high dof redundant manipulators. Mech. Mach. Theory. 153, 103978 (2020). https://doi.org/10.1016/j.mechmachtheory.2020.103978
Lloyd, S., Irani, R.A., Ahmadi, M.: Fast and robust inverse kinematics of serial robots using halley’s method. IEEE T. Robot. 38, 2768–2780 (2022). https://doi.org/10.1109/TRO.2022.3162954
Xiao, F., Li, G., Jiang, D., Xie, Y., Yun, J., Liu, Y., Huang, L., Fang, Z.: An effective and unified method to derive the inverse kinematics formulas of general six-dof manipulator with simple geometry. Mech. Mach. Theory. 159, 104265 (2021). https://doi.org/10.1016/j.mechmachtheory.2021.104265
Zhang, X., Xiao, F., Tong, X., Yun, J., Liu, Y., Sun, Y., Tao, B., Kong, J., Xu, M., Chen, B.: Time optimal trajectory planing based on improved sparrow search algorithm. Front. Bioeng. Biotech. 10, 852408 (2022). https://doi.org/10.3389/fbioe.2022.852408
Wenger, P., Chablat, D.: A review of cuspidal serial and parallel manipulators. J. Mech. Robot. 15, 040801 (2022). https://doi.org/10.1115/1.4055677
Wenger, P.: Uniqueness domains and regions of feasible paths for cuspidal manipulators. IEEE T. Robot. 20, 745–750 (2004). https://doi.org/10.1109/TRO.2004.829467
Parenti-Castelli, V., Innocenti, C.: Position analysis of robot manipulators: regions and subregions. Paper presented at Proceedings of 1988 conference on Advances in Robot Kinematics, Ljubljana, 151–158 Sept. 1988 (1988)
Borrel, P., Liegeois, A.: A study of multiple manipulator inverse kinematic solutions with applications to trajectory planning and workspace determination. Paper presented at Proceedings. 1986 IEEE International Conference on Robotics and Automation, San Francisco, 1180–1185 Apr. 1986 (1986)
Wenger, P.: A new general formalism for the kinematic analysis of all nonredundant manipulators. Paper presented at Proceedings 1992 IEEE International Conference on Robotics and Automation, Nice, 442–447 May. 1992 (1992)
El Omri, J., Wenger, P.: How to recognize simply a non-singular posture changing 3-DOF manipulator. Paper presented at 7th International Conference on Advanced Robotics, 215–222 1995 (1995)
Salunkhe, D.H., Spartalis, C., Capco, J., Chablat, D., Wenger, P.: Necessary and sufficient condition for a generic 3r serial manipulator to be cuspidal. Mech. Mach. Theory. 171, 104729 (2022). https://doi.org/10.1016/j.mechmachtheory.2022.104729
Baili, M., Wenger, P., Chablat, D.: A classification of 3R orthogonal manipulators by the topology of their workspace. Paper presented at IEEE International Conference on Robotics and Automation, New Orleans, 1933–1938 Apr. 2004 (2004)
Wenger, P.: Cuspidal and noncuspidal robot manipulators. Robotica. 25, 677–689 (2007). https://doi.org/10.1017/S0263574707003761
Wenger, P.: Design of cuspidal and non-cuspidal robot manipulators. Paper presented at International Conference on Robotics and Automation, New Orleans, 2172–2177 Apr. 1997 (1997)
Kalra, P., Mahapatra, P.B., Aggarwal, D.K.: An evolutionary approach for solving the multimodal inverse kinematics problem of industrial robots. Mech. Mach. Theory. 41, 1213–1229 (2006). https://doi.org/10.1016/j.mechmachtheory.2005.11.005
Lee, C.s.g., Ziegler, M.: Geometric approach in solving inverse kinematics of puma robots. IEEE T. Aero. Elec. Sys. AES-20, 695–706 (1984). https://doi.org/10.1109/TAES.1984.310452
Balkan, T., Özgören, M.K., Sahir Arıkan, M.A., Baykurt, H.M.: A method of inverse kinematics solution including singular and multiple configurations for a class of robotic manipulators. Mech. Mach. Theory. 35, 1221–1237 (2000). https://doi.org/10.1016/S0094-114X(99)00079-8
Xu, Z., Zhou, X., Wu, H., Li, X., Li, S.: Motion planning of manipulators for simultaneous obstacle avoidance and target tracking: an rnn approach with guaranteed performance. IEEE T. Ind. Electron. 69, 3887–3897 (2021). https://doi.org/10.1109/TIE.2021.3073305
Liu, B., Fu, W., Wang, W., Li, R., Gao, Z., Peng, L., Du, H.: Cobot motion planning algorithm for ensuring human safety based on behavioral dynamics. Sensors. 22, 4376 (2020). https://doi.org/10.3390/s22124376
Yahşi, O.S., Özgören, K.: Minimal joint motion optimization of manipulators with extra degrees of freedom. Mech. Mach. Theory. 19, 325–330 (1984). https://doi.org/10.1016/0094-114X(84)90066-1
Nearchou, A.C.: Solving the inverse kinematics problem of redundant robots operating in complex environments via a modified genetic algorithm. Mech. Mach. Theory. 33, 273–292 (1998). https://doi.org/10.1016/S0094-114X(97)00034-7
Wang, L.-C.T., Chen, C.C.: A combined optimization method for solving the inverse kinematics problems of mechanical manipulators. IEEE T. Robotic. Autom. 7, 489–499 (1991). https://doi.org/10.1109/70.86079
Deng, H., Xie, C.: An improved particle swarm optimization algorithm for inverse kinematics solution of multi-dof serial robotic manipulators. Soft Comput. 25, 13695–13708 (2021). https://doi.org/10.1007/s00500-021-06007-6
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
Schreiber, L.-T., Gosselin, C.: Determination of the inverse kinematics branches of solution based on joint coordinates for universal robots-like serial robot architecture. J. Mech. Robot. 14, 034501 (2021). https://doi.org/10.1115/1.4052805
Adam, W., Nikos, A., Miatliuk, Kanstantsin, Moulianitis, Vassilis, Valsamos, C.: Optimization of dynamic task location within a manipulator’s workspace for the utilization of the minimum required joint torques. Electronics. (2021). https://doi.org/10.3390/electronics10030288
Liu, Y., Xiao, F., Tong, X., Tao, B., Xu, M., Jiang, G., Chen, B., Cao, Y., Sun, N.: Manipulator trajectory planning based on work subspace division. Concurrency and Computation: Practice and Experience. 34, 6710 (2022). https://doi.org/10.1002/cpe.6710
Pieper, D.: The kinematics of manipulation under computer control. PhD thesis, Stanford University Stanford, CA, USA (1968)
Liu, Q., Yang, D., Hao, W., Wei, Y.: Research on Kinematic Modeling and Analysis Methods of UR Robot. Paper presented at IEEE 4th Information Technology and Mechatronics Engineering Conference , Chongqing, 159–164 Dec. 2018 (2018)
Villani, V., Pini, F., Leali, F., Secchi, C.: Survey on human-robot collaboration in industrial settings: Safety, intuitive interfaces and applications. Mechatronics. 55, 248–266 (2018). https://doi.org/10.1016/j.mechatronics.2018.02.009
Li, G., Xiao, F., Zhang, X., Tao, B., Jiang, G.: An inverse kinematics method for robots after geometric parameters compensation. Mech. Mach. Theory. 174, 104903 (2022). https://doi.org/10.1016/j.mechmachtheory.2022.104903
Kebria, P.M., Al-wais, S., Abdi, H., Nahavandi, S.: Kinematic and dynamic modelling of UR5 manipulator. Paper presented at IEEE International Conference on Systems, Man, and Cybernetics, Budapest, 4229–4234 Oct. 2016 (2016)
Mavroidis, C., Ouezdou, F.B., Bidaud, P.: Inverse kinematics of six-degree of freedom general and special manipulators using symbolic computation. Robotica. 12, 421–430 (1994). https://doi.org/10.1017/S0263574700017975
Gualtieri, M., Platt, R.: Robotic pick-and-place with uncertain object instance segmentation and shape completion. IEEE Robot. Autom. Lett. 6, 1753–1760 (2021). https://doi.org/10.1109/LRA.2021.3060669
Zhang, X., Li, G., Xiao, F., Jiang, D., Tao, B., Kong, J., Jiang, G., Liu, Y.: An inverse kinematics framework of mobile manipulator based on unique domain constraint. Mech. Mach. Theory. 183, 105273 (2020). https://doi.org/10.1016/j.mechmachtheory.2023.105273
Acknowledgements
This work was supported by grants of the National Natural Science Foundation of China (Grant Nos.52075530,51575407, 51975324, 51505349, 61733011, 41906177); the Grants of Hubei Provincial Department of Education (D20191105); the Grants of National Defense PreResearch Foundation of Wuhan University of Science and Technology (GF201705) and Open Fund of the Key Laboratory for Metallurgical Equipment and Control of Ministry of Education in Wuhan University of Science and Technology (2018B07,2019B13) and Open Fund of Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance in China Three Gorges University (2020KJX02, 2021KJX13); Science and Technology Planning Project of Inner Mongolia Autonomous Region (2020GG0105).
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Conceptualization and methodology, X.F.Z.; experiment, X.F.Z.; writing-original draft preparation, X.F.Z.; supervision, G.F.L and M.M.X; review and editing, J.T.Y and D.J.; funding acquisition, G.F.L.. All authors have read and agreed to the published version of the manuscript.
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Appendix A: Inverse Kinematics of 6R Ball Wrist Manipulator
Appendix A: Inverse Kinematics of 6R Ball Wrist Manipulator
This appendix derives the inverse kinematics of the 6R ball-wrist manipulator based on the method in reference [4]. In this appendix, the exponential product method is used, because its convenience brings more compact kinematic equations [36].
1.1 A.1 Recalls of Exponential Product Method
The relative motion between adjacent joints is described by the exponential product formula (POE), as shown in Eq. A1,
where q is the angle of rotation. w is the unit vector of the rotation axis and w is its anti-symmetric matrix. I is a 3×3 identity matrix. r is a point on the axis of rotation. \({\xi }\)= (w v)\(^T\) is the Lie algebraic representation of a Euclidean group SE(3), called twist.
The \(e^{q \hat{\varvec{w}}}\) can be calculated by Rodrigues formula as Eq. A2.
The forward kinematics of the manipulator can be represented by Eq. A3.
where g\(_0\) is the initial pose matrix of T under S, and T\(_t\) denotes the pose of EE, expands as follows
1.2 A.2 Inverse Kinematics Solution of 6R Ball Wrist Manipulator
The twists of the 6R ball wrist manipulator are shown in Table 5. The initial pose matrix g\(_0\) is given in Eq. A5. The forward kinematic model of the manipulator can be obtained from Eq. A3.
Four equations can be obtained by decoupling Eq. A2, which are shown as follow
where \(\varvec{p}_{m 1}\) = \([p_x, p_y, -a_{1}]^\textrm{T}\), \(\varvec{x}_{m 1}\) = \([c_{1}, s_{1}, -1]^\textrm{T}\), \(\varvec{p}_{m 2}\) = \([1, a_{1}, -1]^\textrm{T}\), \(\varvec{x}_{m 2}\) = \([0, 1, p_z]^\textrm{T}\), \(\varvec{z}_{L}\) = \([c_{1}c_{23}, s_{1}c_{23}, -s_{23}]^\textrm{T}\).
From the Eq. A8, the analytical formula of q\(_1\) is obtained
where k\(_1\) = \(\pm 1\), which is the first ambiguous symbol, and \(\arctan \)2( , ) denotes the arctangent function.
Equations A6 and A7 are squared and summed to obtain the equality
and the analytical formula of q\(_{3}\) is
where k\(_2\) = \(\pm 1\), which is the second ambiguous symbol.
Simultaneous Eqs. A6 and A7 can be obtained
The solution of q\(_{6}\) can be obtained by putting q\(_{1}\), q\(_{2}\) and q\(_{3}\) into Eq. A9,
where k\(_3\) = \(\pm 1\), which is the third ambiguous symbol.
There are the following constraints
where \(\varvec{h}_{n 1}\) = [s\(_1\), c\(_1\), 0]\(^\textrm{T}\), \(\varvec{h}_{n 2}\) = [-c\(_1\)s\(_{23}\), -s\(_1\)s\(_{23}\), -c\(_{23}\)]\(^\textrm{T}\), \(\varvec{h}_{n 3}\) = \(\varvec{o}c_6 + \varvec{n}s_6\).
Therefore, the solution of \(q_4\) and \(q_5\) can be obtained
1.3 A.3 Inverse Kinematics of UR-like Manipulator
Similar to the procedure shown in Appendix A.1, the twists of the UR-like robot are first established, as shown in Table 6.
The initial pose matrix \(\varvec{g}_0\) is given in Eq. A18. The forward kinematic model of the manipulator can be obtained from Eq. A3.
By decoupling the forward kinematic we can obtain Eq. A19
where \(\varvec{g}_1=\varvec{g}_0\). We denote the left side of Eq. A19 as \(\varvec{T}_{\varvec{L}1}\) and the right side as \(\varvec{T}_{\varvec{R}1}\) and use the \(\varvec{T}_{(i, j)}\) to denote the element in row i and column j of the matrix T.
From \(\varvec{T}_{\varvec{L}1(1,4)}\) \(^2\) + \(\varvec{T}_{\varvec{L}1(2,4)}\) \(^2\) = \(\varvec{T}_{\varvec{R}1(1,4)}\) \(^2\) + \(\varvec{T}_{\varvec{R}1(2,4)}\) \(^2\), Eq. A20 can be obtained
where \(k_1 = \pm 1\), which is the first ambiguous symbol.
Let \(k_1\sqrt{(p_x^2+p_y^2-a_4^2)}=A\). Substituting A into \(\varvec{T}_{\varvec{L}}\), the solution to \(q_1\) can be obtained from \(\varvec{T}_{\varvec{L}1(1,4)}\) = \(\varvec{T}_{\varvec{R}1(1,4)}\) and \(\varvec{T}_{\varvec{L}1(2,4)}\) = \(\varvec{T}_{\varvec{R}1(2,4)}\), as shown in Eq. A21.
Denote Eq. A22 as \(\varvec{T}_{\varvec{L}2}=\varvec{T}_{\varvec{R}2}\). From \(\varvec{T}_{\varvec{L}2(2,3)}=\varvec{T}_{\varvec{R}2(2,3)}\), we can get \(q_5\)
where \(k_2 =\pm 1\), which is the second ambiguous symbol.
Similarly, by \(\varvec{T}_{\varvec{L}2(2,1)}=\varvec{T}_{\varvec{R}2(2,1)}\), \(q_6\) is obtained
The solution of \(q_{234}\) is obtained from \(\varvec{T}_{\varvec{L}1(3,1)}=\varvec{T}_{\varvec{R}1(3,1)}\) and \(\varvec{T}_{\varvec{L}1(3,3)}=\varvec{T}_{\varvec{R}1(3,3)}\)
Then, put \(q_{234}\) into Eq. A20 and combine \(\varvec{T}_{\varvec{L}1(3,4)}=\varvec{T}_{\varvec{R}1(3,4)}\), the solution of \(q_3\) is obtained.
where \(k_3 = \pm 1\), which is the third ambiguous symbol.
By taking \(q_3\) into \(\varvec{T}_{\varvec{L}1(1,4)}=\varvec{T}_{\varvec{R}1(1,4)}\) and Eq. A18, we can obtain
where \(n=a_3s_3\), \(m=a_2+a_3c_3\).
Finally,
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Zhang, X., Li, G., Xu, M. et al. A Novel Method for Selecting Inverse Kinematic Solutions Based on Configuration Space Partition for 6R Noncuspidal Manipulators. J Intell Robot Syst 110, 7 (2024). https://doi.org/10.1007/s10846-023-02029-4
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DOI: https://doi.org/10.1007/s10846-023-02029-4