In this paper we present a novel strategy for motion planning of autonomous robotic arms in Robotic Minimally Invasive Surgery (R-MIS). We consider a scenario where several laparoscopic tools must move and coordinate in a shared environment. The motion planner is based on a Model Predictive Controller (MPC) that predicts the future behavior of the robots and allows to move them avoiding collisions between the tools and satisfying the velocity limitations. In order to avoid the local minima that could affect the MPC, we propose a strategy for driving it through a sequence of waypoints. The proposed control strategy is validated on a realistic surgical scenario.
Integrating model predictive control and dynamic waypoints generation for motion planning in surgical scenario / Minelli, M.; Sozzi, A.; De Rossi, G.; Ferraguti, F.; Setti, F.; Muradore, R.; Bonfe, M.; Secchi, C.. - (2020), pp. 3157-3163. (Intervento presentato al convegno 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 tenutosi a usa nel 2020) [10.1109/IROS45743.2020.9341673].
Integrating model predictive control and dynamic waypoints generation for motion planning in surgical scenario
Minelli M.;Ferraguti F.;Secchi C.
2020
Abstract
In this paper we present a novel strategy for motion planning of autonomous robotic arms in Robotic Minimally Invasive Surgery (R-MIS). We consider a scenario where several laparoscopic tools must move and coordinate in a shared environment. The motion planner is based on a Model Predictive Controller (MPC) that predicts the future behavior of the robots and allows to move them avoiding collisions between the tools and satisfying the velocity limitations. In order to avoid the local minima that could affect the MPC, we propose a strategy for driving it through a sequence of waypoints. The proposed control strategy is validated on a realistic surgical scenario.Pubblicazioni consigliate
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