Within the context of Robotic Minimally Invasive Surgery (R-MIS), we propose a novel linear model predictive controller formulation for the coordination of multiple autonomous robotic arms. The controller is synthesized by formulating a linear approximation of non-linear constraints, which allows the controller to be both computationally faster and better performing due to the increased prediction horizon allowed within the real-time control requirements for the proposed surgical application. The solution is validated under the expected constraints of a surgical scenario in which multiple laparoscopic tools must move and coordinate in a shared environment.
Linear MPC-based Motion Planning for Autonomous Surgery / Minelli, Marco; Sozzi, Alessio; De Rossi, Giacomo; Ferraguti, Federica; Farsoni, Saverio; Setti, Francesco; Muradore, Riccardo; Bonfè, Marcello; Secchi, Cristian. - 2022-October:(2022), pp. 5699-5706. (Intervento presentato al convegno 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 tenutosi a Kyoto, Japan nel 23-27 October 2022) [10.1109/iros47612.2022.9982166].
Linear MPC-based Motion Planning for Autonomous Surgery
Minelli, Marco;Ferraguti, Federica;Farsoni, Saverio;Secchi, Cristian
2022
Abstract
Within the context of Robotic Minimally Invasive Surgery (R-MIS), we propose a novel linear model predictive controller formulation for the coordination of multiple autonomous robotic arms. The controller is synthesized by formulating a linear approximation of non-linear constraints, which allows the controller to be both computationally faster and better performing due to the increased prediction horizon allowed within the real-time control requirements for the proposed surgical application. The solution is validated under the expected constraints of a surgical scenario in which multiple laparoscopic tools must move and coordinate in a shared environment.File | Dimensione | Formato | |
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