@conference{Minelli2020,
title = {Integrating Model Predictive Control and Dynamic Waypoints Generation for Motion Planning in Surgical Scenario},
author = {Marco Minelli, Alessio Sozzi, Giacomo De Rossi, Federica Ferraguti, Francesco Setti, Riccardo Muradore, Marcello Bonfè, Cristian Secchi},
editor = {IEEE },
doi = {10.1109/IROS45743.2020.9341673},
year = {2020},
date = {2020-10-24},
booktitle = {2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
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.},
keywords = {Collision avoidance, Minimally invasive surgery, Planning, Predictive models, Robot kinematics, Robots, Tools},
pubstate = {published},
tppubtype = {conference}
}

@conference{Sayols2020,
title = {Global/local motion planning based on Dynamic Trajectory Reconfiguration and Dynamical Systems for autonomous surgical robots},
author = {Narcís Sayols, Alessio Sozzi, Nicola Piccinelli, Albert Hernansanz, Alicia Casals, Marcello Bonfè, and Riccardo Muradore,},
editor = {IEEE},
doi = {10.1109/ICRA40945.2020.9197525},
year = {2020},
date = {2020-09-15},
booktitle = {2020 IEEE International Conference on Robotics and Automation (ICRA)},
abstract = {This paper addresses the generation of collision-free trajectories for the autonomous execution of assistive tasks in Robotic Minimally Invasive Surgery (R-MIS). The proposed approach takes into account geometric constraints related to the desired task, like for example the direction to approach the final target and the presence of moving obstacles. The developed motion planner is structured as a two-layer architecture: a global level computes smooth spline-based trajectories that are continuously updated using virtual potential fields; a local level, exploiting Dynamical Systems based obstacle avoidance, ensures collision free connections among the spline control points. The proposed architecture is validated in a realistic surgical scenario.},
keywords = {assistive tasks, autonomous execution, autonomous surgical, Collision avoidance, collision free connections, collision-free trajectories, desired task, developed motion planner, dynamical systems based obstacle avoidance, final target, geometric constraints, global level computes smooth spline-based trajectories, Medical robotics, mobile robots, motion control, moving obstacles, realistic surgical scenario, Robots, splines (mathematics), Surgery, surgery INSPEC: Non-Controlled Indexing robotic minimally invasive surgery, Task analysis, Tools, Trajectory, two-layer architecture},
pubstate = {published},
tppubtype = {conference}
}