9 research outputs found
Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities
Robotic assistance allows surgeons to perform dexterous and tremor-free
procedures, but robotic aid is still underrepresented in procedures with
constrained workspaces, such as deep brain neurosurgery and endonasal surgery.
In these procedures, surgeons have restricted vision to areas near the surgical
tooltips, which increases the risk of unexpected collisions between the shafts
of the instruments and their surroundings. In this work, our
vector-field-inequalities method is extended to provide dynamic
active-constraints to any number of robots and moving objects sharing the same
workspace. The method is evaluated with experiments and simulations in which
robot tools have to avoid collisions autonomously and in real-time, in a
constrained endonasal surgical environment. Simulations show that with our
method the combined trajectory error of two robotic systems is optimal.
Experiments using a real robotic system show that the method can autonomously
prevent collisions between the moving robots themselves and between the robots
and the environment. Moreover, the framework is also successfully verified
under teleoperation with tool-tissue interactions.Comment: Accepted on T-RO 2019, 19 Page
Vitreoretinal Surgical Robotic System with Autonomous Orbital Manipulation using Vector-Field Inequalities
Vitreoretinal surgery pertains to the treatment of delicate tissues on the
fundus of the eye using thin instruments. Surgeons frequently rotate the eye
during surgery, which is called orbital manipulation, to observe regions around
the fundus without moving the patient. In this paper, we propose the autonomous
orbital manipulation of the eye in robot-assisted vitreoretinal surgery with
our tele-operated surgical system. In a simulation study, we preliminarily
investigated the increase in the manipulability of our system using orbital
manipulation. Furthermore, we demonstrated the feasibility of our method in
experiments with a physical robot and a realistic eye model, showing an
increase in the view-able area of the fundus when compared to a conventional
technique. Source code and minimal example available at
https://github.com/mmmarinho/icra2023_orbitalmanipulation.Comment: 7 pages, 7 figures, accepted on ICRA202
Single-Shot Pose Estimation of Surgical Robot Instruments' Shafts from Monocular Endoscopic Images
Surgical robots are used to perform minimally invasive surgery and alleviate
much of the burden imposed on surgeons. Our group has developed a surgical
robot to aid in the removal of tumors at the base of the skull via access
through the nostrils. To avoid injuring the patients, a collision-avoidance
algorithm that depends on having an accurate model for the poses of the
instruments' shafts is used. Given that the model's parameters can change over
time owing to interactions between instruments and other disturbances, the
online estimation of the poses of the instrument's shaft is essential. In this
work, we propose a new method to estimate the pose of the surgical instruments'
shafts using a monocular endoscope. Our method is based on the use of an
automatically annotated training dataset and an improved pose-estimation
deep-learning architecture. In preliminary experiments, we show that our method
can surpass state of the art vision-based marker-less pose estimation
techniques (providing an error decrease of 55% in position estimation, 64% in
pitch, and 69% in yaw) by using artificial images.Comment: Accepted on ICRA 2020, 7 page
MBAPose: Mask and Bounding-Box Aware Pose Estimation of Surgical Instruments with Photorealistic Domain Randomization
Surgical robots are controlled using a priori models based on robots'
geometric parameters, which are calibrated before the surgical procedure. One
of the challenges in using robots in real surgical settings is that parameters
change over time, consequently deteriorating control accuracy. In this context,
our group has been investigating online calibration strategies without added
sensors. In one step toward that goal, we have developed an algorithm to
estimate the pose of the instruments' shafts in endoscopic images. In this
study, we build upon that earlier work and propose a new framework to more
precisely estimate the pose of a rigid surgical instrument. Our strategy is
based on a novel pose estimation model called MBAPose and the use of synthetic
training data. Our experiments demonstrated an improvement of 21 % for
translation error and 26 % for orientation error on synthetic test data with
respect to our previous work. Results with real test data provide a baseline
for further research.Comment: 8 pages, submitted to IROS202
Whole-Body Bilateral Teleoperation of a Redundant Aerial Manipulator
Attaching a robotic manipulator to a flying base allows for significant
improvements in the reachability and versatility of manipulation tasks. In
order to explore such systems while taking advantage of human capabilities in
terms of perception and cognition, bilateral teleoperation arises as a
reasonable solution. However, since most telemanipulation tasks require visual
feedback in addition to the haptic one, real-time (task-dependent) positioning
of a video camera, which is usually attached to the flying base, becomes an
additional objective to be fulfilled. Since the flying base is part of the
kinematic structure of the robot, if proper care is not taken, moving the video
camera could undesirably disturb the end-effector motion. For that reason, the
necessity of controlling the base position in the null space of the
manipulation task arises. In order to provide the operator with meaningful
information about the limits of the allowed motions in the null space, this
paper presents a novel haptic concept called Null-Space Wall. In addition, a
framework to allow stable bilateral teleoperation of both tasks is presented.
Numerical simulation data confirm that the proposed framework is able to keep
the system passive while allowing the operator to perform time-delayed
telemanipulation and command the base to a task-dependent optimal pose.Comment: to be published in 2020 IEEE International Conference on Robotics and
Automation (ICRA
Virtual Fixture Assistance for Suturing in Robot-Aided Pediatric Endoscopic Surgery
The limited workspace in pediatric endoscopic surgery makes surgical suturing
one of the most difficult tasks. During suturing, surgeons have to prevent
collisions between tools and also collisions with the surrounding tissues.
Surgical robots have been shown to be effective in adult laparoscopy, but
assistance for suturing in constrained workspaces has not been yet fully
explored. In this letter, we propose guidance virtual fixtures to enhance the
performance and the safety of suturing while generating the required task
constraints using constrained optimization and Cartesian force feedback. We
propose two guidance methods: looping virtual fixtures and a trajectory
guidance cylinder, that are based on dynamic geometric elements. In simulations
and experiments with a physical robot, we show that the proposed methods
achieve a more precise and safer looping in robot-assisted pediatric endoscopy.Comment: Accepted on RA-L/ICRA 2020, 8 Pages. Fixed a few typo