In this section
@inproceedings{Cursi:2021:10.1109/IROS45743.2020.9341334,
author = {Cursi, F and Modugno, V and Kormushev, P},
doi = {10.1109/IROS45743.2020.9341334},
pages = {7653--7660},
title = {Model predictive control for a tendon-driven surgical robot with safety constraints in kinematics and dynamics},
url = {http://dx.doi.org/10.1109/IROS45743.2020.9341334},
year = {2021}
}
TY - CPAPER
AB - In fields such as minimally invasive surgery, effective control strategies are needed to guarantee safety andaccuracy of the surgical task. Mechanical designs and actuationschemes have inevitable limitations such as backlash and jointlimits. Moreover, surgical robots need to operate in narrowpathways, which may give rise to additional environmentalconstraints. Therefore, the control strategies must be capableof satisfying the desired motion trajectories and the imposedconstraints. Model Predictive Control (MPC) has proven effective for this purpose, allowing to solve an optimal problem bytaking into consideration the evolution of the system states, costfunction, and constraints over time. The high nonlinearities intendon-driven systems, adopted in many surgical robots, are difficult to be modelled analytically. In this work, we use a modellearning approach for the dynamics of tendon-driven robots.The dynamic model is then employed to impose constraintson the torques of the robot under consideration and solve anoptimal constrained control problem for trajectory trackingby using MPC. To assess the capabilities of the proposedframework, both simulated and real world experiments havebeen conducted
AU - Cursi,F
AU - Modugno,V
AU - Kormushev,P
DO - 10.1109/IROS45743.2020.9341334
EP - 7660
PY - 2021///
SP - 7653
TI - Model predictive control for a tendon-driven surgical robot with safety constraints in kinematics and dynamics
UR - http://dx.doi.org/10.1109/IROS45743.2020.9341334
UR - https://ieeexplore.ieee.org/abstract/document/9341334
UR - http://hdl.handle.net/10044/1/80783
ER -