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Louis A. Lobes Jr.

dblp:51/10867 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
3 papers
Motion planning and robot control · 60% Robot manipulation · 29% 3D vision · 11%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%
Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 100%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control
0.312017
Toward monocular camera-guided retinal vein cannulation with an actively stabilized handheld robot · ICRA 2017
Robotics › Robot manipulation › medical robotics
tremor cancellation
0.222012
Micron: An Actively Stabilized Handheld Tool for Microsurgery · IEEE Trans. Robotics 2012
Vision-based retinal membrane peeling with a handheld robot · ICRA 2012
Robotics › Motion planning and robot control › robot control › stabilization control
active stabilization
0.112012
Micron: An Actively Stabilized Handheld Tool for Microsurgery · IEEE Trans. Robotics 2012
Medical and health informatics › ophthalmology
retinal surgery
0.112012
Vision-based retinal membrane peeling with a handheld robot · ICRA 2012
Health and well-being technologies
microsurgery
0.112012
Micron: An Actively Stabilized Handheld Tool for Microsurgery · IEEE Trans. Robotics 2012
Computer vision › 3D vision › 3d reconstruction
surface reconstruction
0.112017
Toward monocular camera-guided retinal vein cannulation with an actively stabilized handheld robot · ICRA 2017
Robotics › Robot manipulation
micromanipulation
0.012012
Vision-based retinal membrane peeling with a handheld robot · ICRA 2012

Methods — techniques the papers use, named apart from their topics

motion scaling · 0.6velocity limiting · 0.3stereo vision · 0.3piezoelectric actuation · 0.3optical position measurement · 0.3control filter design · 0.3laser beam scanning · 0.3homography matrix estimation · 0.3
YearPublicationVenuePosition
2017 Toward monocular camera-guided retinal vein cannulation with an actively stabilized handheld robot
abstract
In this paper we describe work towards retinal vessel cannulation using an actively stabilized handheld robot, guided by monocular vision. We employ a previously developed monocular camera based surface reconstruction method using automated laser beam scanning over the retina. We use the reconstructed plane to find a coordinate transform between the 2D image plane coordinate system and the global 3D frame. Within a hemispherical region around the target, we use motion scaling for higher precision. The contribution of this work is the homography matrix estimation using monocular vision and application of the previously developed laser surface reconstruction to Micron guided vein cannulation. Experiments are conducted in a wet eye phantom to show the higher accuracy of the surface reconstruction as compared to standard stereo reconstruction. Further, experiments to show the increased surgical accuracy due to motion scaling are also carried out.
Shohin Mukherjee, Sungwook Yang, Robert A. MacLachlan, Louis A. Lobes Jr., Joseph N. Martel, Cameron N. Riviere
ICRA4
2016 Comparative Evaluation of Handheld Robot-Aided Intraocular Laser Surgery
abstract
This paper presents robot-aided intraocular laser surgery using a handheld robot known as Micron. The micromanipulator incorporated in Micron enables visual servoing of a laser probe, while maintaining a constant distance of the tool tip from the retinal surface. The comparative study was conducted with various control methods for evaluation of robot-aided intraocular laser surgery.
Sungwook Yang, Robert A. MacLachlan, Joseph N. Martel, Louis A. Lobes Jr., Cameron N. Riviere
IEEE Trans. Robotics4
2012 Vision-based retinal membrane peeling with a handheld robot
abstract
Peeling delicate retinal membranes, which are often less than 5 µm thick, is one of the most challenging retinal surgeries. Preventing rips and tears caused by tremor and excessive force can decrease injury and reduce the need for follow up surgeries. We propose the use of a fully handheld microsurgical robot to suppress tremor while enforcing helpful constraints on the motion of the tool. Using stereo vision and tracking algorithms, the robot activates motion-scaled behavior as the tip reaches the surface, providing finer control during the critical step of engaging the membrane edge. A hard virtual fixture just below the surface limits the total downward force that can be applied. Furthermore, velocity limiting during the peeling helps the surgeon maintain a smooth, constant force while lifting and delaminating the membrane. On a phantom consisting of plastic wrap stretched across a rubber slide, we demonstrate our approach reduces maximum force by 40-70%.
Brian C. Becker, Robert A. MacLachlan, Louis A. Lobes Jr., Cameron N. Riviere
ICRA3
2012 Micron: An Actively Stabilized Handheld Tool for Microsurgery
abstract
We describe the design and performance of a hand-held actively stabilized tool to increase accuracy in micro-surgery or other precision manipulation. It removes involuntary motion such as tremor by actuating the tip to counteract the effect of the undesired handle motion. The key components are a three-degree-of-freedom piezoelectric manipulator that has 400 μm range of motion, 1 N force capability, and bandwidth over 100 Hz, and an optical position measurement subsystem that acquires the tool pose with 4 μm resolution at 2000 samples/s. A control system using these components attenuates hand motion by at least 15 dB (a fivefold reduction). By considering the effect of the frequency response of Micron on the human visual feedback loop, we have developed a filter that reduces unintentional motion, yet preserves intuitive eye-hand coordination. We evaluated the effectiveness of Micron by measuring the accuracy of the human/machine system in three simple manipulation tasks. Handheld testing by three eye surgeons and three non-surgeons showed a reduction in position error of between 32% and 52%, depending on the error metric.
Robert A. MacLachlan, Brian C. Becker, Jaime Cuevas Tabarés, Gregg Podnar, Louis A. Lobes Jr., Cameron N. Riviere
IEEE Trans. Robotics5