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

Sozzi, Alessio;Farsoni, Saverio;Bonfe', Marcello;
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.
2022
9781665479271
Autonomous robotics; Linear approximations; Linear modeling; Minimally-invasive surgery; Model predictive controllers; Motion-planning; Non-linear constraints; Prediction horizon; Real-time control; Synthesised
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2553370
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