TY - GEN
T1 - Increasing precision of the Raven-II surgical robot by applying cascade control
AU - Schwaner, Kim Lindberg
AU - Jensen, Pernille Tine
AU - Savarimuthu, Thiusius Rajeeth
PY - 2018
Y1 - 2018
N2 - Automated execution of surgical procedures using a robot has the potential to facilitate training of novice surgeons and reduce workload. However, many current surgical robots are not built for autonomous task execution, but manual teleoperation, which means that they are often imprecise. This also applies to the Raven-II surgical robot.This paper explores a cascade control scheme applied to the Raven-II. This scheme is beneficial in the face of the significant dynamics of the robot. The hypothesis is that this alternative control scheme, compared to the previous method, will reduce the trajectory-following error and improve robot precision.To compare controller performances, an initial qualitative experiment is carried out with the three positioning joints of the robot, where individual joints are each commanded to move along smooth reference trajectories in joint-space. A more quantitative measure is found in a second experiment in which the control methods are compared by looking at their ability to follow the same predefined path between 500 randomly generated tool-space configurations.The cascade control scheme is shown to better achieve tight control, reduce trajectory-following error and improve robot precision even with less-than-optimally tuned gain parameters. The improvement is modest when compared to the error in the robot state estimate.
AB - Automated execution of surgical procedures using a robot has the potential to facilitate training of novice surgeons and reduce workload. However, many current surgical robots are not built for autonomous task execution, but manual teleoperation, which means that they are often imprecise. This also applies to the Raven-II surgical robot.This paper explores a cascade control scheme applied to the Raven-II. This scheme is beneficial in the face of the significant dynamics of the robot. The hypothesis is that this alternative control scheme, compared to the previous method, will reduce the trajectory-following error and improve robot precision.To compare controller performances, an initial qualitative experiment is carried out with the three positioning joints of the robot, where individual joints are each commanded to move along smooth reference trajectories in joint-space. A more quantitative measure is found in a second experiment in which the control methods are compared by looking at their ability to follow the same predefined path between 500 randomly generated tool-space configurations.The cascade control scheme is shown to better achieve tight control, reduce trajectory-following error and improve robot precision even with less-than-optimally tuned gain parameters. The improvement is modest when compared to the error in the robot state estimate.
U2 - 10.1109/ROBIO.2018.8664821
DO - 10.1109/ROBIO.2018.8664821
M3 - Article in proceedings
SN - 978-1-7281-0378-5
SP - 1138
EP - 1144
BT - Proceedings of the 2018 IEEE International Conference on Robotics and Biomimetics
PB - IEEE
T2 - 2018 IEEE International Conference on Robotics and Biomimetics
Y2 - 12 December 2018 through 15 December 2018
ER -