Eng During last 365 days Approved articles: 2065,   Articles in work: 293 Declined articles: 786 

Back to contents

Cybernetics and programming

Compensation of the alternating drift of the objective function in solving the inverse problem of the manipulator kinematics in the conditions of a moving target
Galemov Ruslan Takhirovich

graduate student, Department of Robotics and Technical Cybernetics, Siberian Federal University

660041, Russia, Krasnoyarskii krai, g. Krasnoyarsk, prospekt Svobodnyi, 79





The object of the study is to solve the inverse problem of kinematics, as an optimization problem, under the conditions of a moving target. The subject of the study is the consideration of the drift of the objective function, as a result of the movement of the target, in the process of optimization. To solve the inverse problem of the kinematics of a multi-link manipulator, in the conditions of the time-varying position of the target, an effective algorithm for search optimization has been developed. Its essence consists in estimating the drift velocity, the formulated objective function, at each step of the search and taking into account the influence of the drift of the target when choosing the direction of the search. The modification of the method for the variable drift velocity of the objective function is considered. Estimates of the drift velocity are calculated by the recursive least squares method based on two modes: continuous search and search movement with repeated experiments at each vertex. The drift effect on the value of the objective function is obtained by integrating the drift velocity estimates on the time interval between the measurements. The author proposes a method for taking into account the drift of the objective function in the optimization problem. The proposed method showed its effectiveness in optimization problems with one and several extremums, using the example of simplex search and the genetic algorithm, operating under conditions of unstable drift of the objective function. The experimental limits of the effectiveness of the application of the method are determined experimentally.

Keywords: hybrid search, genetic algorithm, simplex search, drift estimations, moving target, direct search methods, inverse kinematics problem, cost function drift, optimization, extremum seeking control



Article was received:


Review date:


Publish date:


This article written in Russian. You can find full text of article in Russian here .

Parker J. K., Khoogar A. R., Goldberg D. E. Inverse kinematics of redundant robots using genetic algorithms / /Robotics and Automation: Proceedings on IEEE International Conference. Scottsdale: IEEE, 1989. P. 271-276.
Yip W. S., Marlin T. E. Designing plant experiments for real-time optimization systems //Control Engineering Practice. 2003. Vol. 11. No. 8. P. 837-845.
Yip W. S., Marlin T. E. The effect of model fidelity on real-time optimization performance //Computers & chemical engineering. 2004. Vol. 28. No. 1-2. P. 267-280.
Xiong Q., Jutan A. Continuous optimization using a dynamic simplex method //Chemical Engineering Science. 2003. Vol. 58. No. 16. P. 3817-3828.
Martínez E. C. Statistical simplex method for experimental design in process optimization //Industrial & engineering chemistry research. Washington: American Chemical Society, 2005. Vol. 44. No. 23. P. 8796-8805.
Carlisle A., Dozier G. Adapting particle swarm optimization to dynamic environments //International conference on artificial intelligence. Las Vegas: Proc. 2000 ICAI, 2000. Vol. 1. P. 429-434.
Branke J. Evolutionary optimization in dynamic environments. Norwell: Kluwer Academic Publishers, 2001. P. 208.
Dréo J., Siarry P. An ant colony algorithm aimed at dynamic continuous optimization //Applied Mathematics and Computation. 2006. Vol. 181. No. 1. P. 457-467.
Krug, G.K., Masal'skii G.B. Simpleksnyi invariantnyi metod eksperimental'noi optimizatsii // Voprosy kibernetiki. Planirovanie eksperimenta i optimizatsiya v sistemakh upravleniya: sb. tr. / pod red. G.K. Kruga, A.P. Voshchinina. M.: Akademiya nauk SSSR. 1981. 155 s.
Galemov R.T., Masal'skii G.B. Planirovanie traektorii manipulyatora dlya dvizhushcheisya tseli // Kibernetika i programmirovanie. 2018. 2. S. 9-28.
Chelouah R., Siarry P., Berthiau G., De Barmon B. An optimization method fitted for model inversion in non destructive control by eddy currents. The European Physical Journal Applied Physics . 2000 . Vol. 12 . No. 3 . P. 231-238.