A New Method to Solve the Kinematic Problems of Parallel Robots Using Generalized Reduced Gradient Algorithm
[abstFig src='/00280003/17.jpg' width=""300"" text='Stewart Gough robot and the equivalent substitutional configuration' ] This paper proposes a new method of solving the kinematic problems for parallel robots. The paper content aims to solve nonlinear optimiz...
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| Vydané v: | Journal of robotics and mechatronics Ročník 28; číslo 3; s. 404 - 417 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Tokyo
Fuji Technology Press Co. Ltd
20.06.2016
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| ISSN: | 0915-3942, 1883-8049 |
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| Abstract | [abstFig src='/00280003/17.jpg' width=""300"" text='Stewart Gough robot and the equivalent substitutional configuration' ] This paper proposes a new method of solving the kinematic problems for parallel robots. The paper content aims to solve nonlinear optimization problems with constraints rather than to directly solve high-order nonlinear systems of equations. The nonlinear optimization problems shall be efficiently solved by applying the Generalized Reduced Gradient algorithm and appropriate downgrade techniques. This new method can be able to find exact kinematic solutions by assigning constraints onto the parameters. The procedure can be done without filtering control results from mathematical solution, from which the control time of manipulators can be reduced. The numerical simulation results in this paper shall prove that the method can be applied to solve kinematic problems for a variety of parallel robots regardless of its structures and degree of freedom (DOF). There are several advantages of the proposed method including its simplicity leading to a shorter computing time as well as achieving high accuracy, high reliability, and quick convergence in final results. Hence, the applicability of this method in solving kinematic problems for parallel manipulators is remarkably high. |
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| AbstractList | [abstFig src='/00280003/17.jpg' width=""300"" text='Stewart Gough robot and the equivalent substitutional configuration' ] This paper proposes a new method of solving the kinematic problems for parallel robots. The paper content aims to solve nonlinear optimization problems with constraints rather than to directly solve high-order nonlinear systems of equations. The nonlinear optimization problems shall be efficiently solved by applying the Generalized Reduced Gradient algorithm and appropriate downgrade techniques. This new method can be able to find exact kinematic solutions by assigning constraints onto the parameters. The procedure can be done without filtering control results from mathematical solution, from which the control time of manipulators can be reduced. The numerical simulation results in this paper shall prove that the method can be applied to solve kinematic problems for a variety of parallel robots regardless of its structures and degree of freedom (DOF). There are several advantages of the proposed method including its simplicity leading to a shorter computing time as well as achieving high accuracy, high reliability, and quick convergence in final results. Hence, the applicability of this method in solving kinematic problems for parallel manipulators is remarkably high. This paper proposes a new method of solving the kinematic problems for parallel robots. The paper content aims to solve nonlinear optimization problems with constraints rather than to directly solve high-order nonlinear systems of equations. The nonlinear optimization problems shall be efficiently solved by applying the Generalized Reduced Gradient algorithm and appropriate downgrade techniques. This new method can be able to find exact kinematic solutions by assigning constraints onto the parameters. The procedure can be done without filtering control results from mathematical solution, from which the control time of manipulators can be reduced. The numerical simulation results in this paper shall prove that the method can be applied to solve kinematic problems for a variety of parallel robots regardless of its structures and degree of freedom (DOF). There are several advantages of the proposed method including its simplicity leading to a shorter computing time as well as achieving high accuracy, high reliability, and quick convergence in final results. Hence, the applicability of this method in solving kinematic problems for parallel manipulators is remarkably high. |
| Author | Trang, Thanh Trung Pham, Thanh Long Li, Wei Guang |
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| Cites_doi | 10.5772/9320 10.1109/70.833183 10.1243/PIME_PROC_1965_180_029_02 10.1016/0094-114X(95)00091-C 10.1002/(SICI)1097-4563(199602)13:2<111::AID-ROB4>3.0.CO;2-W 10.1017/S0263574706003080 10.1007/978-94-017-0657-5_42 10.1016/0094-114X(95)00106-9 10.1115/DETC1992-0203 10.1109/ROBOT.1996.509284 10.1016/j.amc.2011.03.106 10.1016/S0094-114X(01)00034-9 10.1177/0278364904039806 10.1115/1.2919188 10.1016/S0305-0548(98)00013-6 10.1115/1.2836473 10.1109/70.265928 10.1109/70.59354 10.1137/1037125 10.1109/INES.2008.4481271 10.1145/355769.355773 |
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| SubjectTerms | Algorithms Computing time Degrees of freedom Kinematics Manipulators Nonlinear equations Nonlinear systems Optimization Robots |
| Title | A New Method to Solve the Kinematic Problems of Parallel Robots Using Generalized Reduced Gradient Algorithm |
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