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Robotic optimization with high-dimensional Pareto front visualization | ||
| Journal of Mathematical Modeling | ||
| دوره 14، شماره 3، آبان 2026، صفحه 1093-1105 اصل مقاله (1.14 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2026.31644.2849 | ||
| نویسنده | ||
| Artem Maminov* | ||
| Federal Research Center ``Computer Science and Control'' of the Russian Academy of Sciences (FRC CSC RAS), Moscow, Russia | ||
| چکیده | ||
| In this paper, we consider an approach for multi-criteria optimization of key design characteristics for robots. We use 5 criteria: Workspace Area, Space Utilization Index, Global Dexterity Index, Global Manipulability Index and Global Resistivity Index. The first two characterize workspace, while the latter three evaluate kinematic performance throughout the workspace. The Pareto-set visualization for such problem can be a challenging task, since the objective space is five-dimensional. We consider clustering approach for efficient reduction of the number of Pareto points. The calculation of the indexes is performed automatically using interval analysis techniques. The experimental validation was performed for three parallel manipulators: 2-RPR, DexTar, PRRRP. We compare the proposed approach with random sampling method and exact Pareto front, calculated with ``brute force'' algorithm. | ||
| کلیدواژهها | ||
| Robot workspace؛ multiobjective optimization؛ interval analysis؛ parallel robots؛ kinematic performance | ||
| مراجع | ||
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