employee from 01.01.2019 until now
Saint-Petersburg, St. Petersburg, Russian Federation
Russian Federation
UDK 519.176 Экстремальные задачи теории графов
The paper considers an urgent scientific problem of optimizing the modes of movement of manipulators in an automated technological process. A method for optimizing the trajectory of movement of manipulators in an automated technological process is presented. The developed trajectory optimization method is used to increase the speed and optimize the movement of various manipulators
motion optimization, manipulators, technological process, motion trajectories
1. Robot skills for manufacturing: From concept to industrial deployment / Pedersen M.R., Nalpantidis L. et. al. // Robotics and Computer-Integrated Manufacturing, 37, 282-291.
2. Faulwasser T., Weber T., Zometa P., Findeisen R. Implementation of nonlinear model predictive path-following control for an industrial robot. IEEE Transactions on Control Systems Technology, 25(4), 1505-1511.
3. Kaltsoukalas K., Makris S., Chryssolouris G. On generating the motion of industrial robot manipulators. Robotics and Computer-Integrated Manufacturing, 32, 65-71.
4. Meleshkova Z., Ivanov S.E., Ivanova L. Application of Neural ODE with embedded hybrid method for robotic manipulator control //Procedia Computer Science, 2021, 193, 314-324.
5. Ivanov S., Ivanova L., Meleshkova Z. Calculation and Optimization of Industrial Robots Motion // 2020 26th Conference of Open Innovations Association (FRUCT). IEEE, 2020, 115-123.
6. Televnoy A., Ivanov S.E., Zudilova T., Ivanova L.N. Transformation method for a nonlinear manipulator model // Procedia Computer Science, 2021, 193, 295-305.
7. Ivanov S.E., Zudilova T., Voitiuk T., Ivanova, L.N. Mathematical Modeling of the Dynamics of 3-DOF Robot-Manipulator with Software Control // Procedia Computer Science, 2020, 178, 311-319.
8. Borisov O.I., Gromov V.S., Pyrkin A.A., Bobtsov A.A. Stabilization of linear plants with unknown delay and sinusoidal disturbance compensation // 2016 24th Mediterranean Conference on Control and Automation (MED). IEEE, 2016, 426-430.
9. LaValle S. M., Branicky M.S., Lindemann S.R. On the relationship between classical grid search and probabilistic roadmaps // The International Journal of Robotics Research, 2004, 23, 7-8, 673-692.
10. Leven P., Hutchinson S. Using manipulability to bias sampling during the construction of probabilistic roadmaps //IEEE Transactions on Robotics and Automation, 2003, 19, 6, 1020-1026.
11. Isto P. Constructing probabilistic roadmaps with powerful local planning and path optimization //IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2002, 3, 2323-2328.
12. Output control algorithms of dynamic positioning and disturbance rejection for robotic vessel / Wang J., Pyrkin A. A. et. al. //IFAC-PapersOnLine, 2015, 48, 11, 295-300.
13. Simple robust and adaptive tracking control for mobile robots / Pyrkin A.A., Bobtsov A.A. et. al. // IFAC-PapersOnLine, 2015, 48, 11, 143-149.
