Integrating model predictive control and dynamic waypoints generation for motion planning in surgical scenario
Contributo in Atti di convegno
Data di Pubblicazione:
2020
Citazione:
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. (2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 usa 2020) [10.1109/IROS45743.2020.9341673].
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.
Tipologia CRIS:
Relazione in Atti di Convegno
Elenco autori:
Minelli, M.; Sozzi, A.; De Rossi, G.; Ferraguti, F.; Setti, F.; Muradore, R.; Bonfe, M.; Secchi, C.
Link alla scheda completa:
Titolo del libro:
IEEE International Conference on Intelligent Robots and Systems