University of Guilan Journal of Mathematical Modeling 2345-394X 14 3 2026 08 01 Robotic optimization with high-dimensional Pareto front visualization 1093 1105 9545 10.22124/jmm.2026.31644.2849 EN Artem Maminov Federal Research Center ``Computer Science and Control'' of the Russian Academy of Sciences (FRC CSC RAS), Moscow, Russia Journal Article 2025 09 09 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. https://jmm.guilan.ac.ir/article_9545_20612cd4b82a496094330a52ce39a5fc.pdf