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Chris Bedell

dblp:54/9963 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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
1 paper
Robot manipulation · 50% Optimization for machine learning · 50%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › medical robotics
concentric tube robot design
0.112011
Design optimization of concentric tube robots based on task and anatomical constraints · ICRA 2011
Machine learning › Optimization for machine learning
optimization
0.112011
Design optimization of concentric tube robots based on task and anatomical constraints · ICRA 2011
Medical and health informatics › surgical robotics
minimally invasive surgery
0.012011
Design optimization of concentric tube robots based on task and anatomical constraints · ICRA 2011

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

optimization framework · 0.2
YearPublicationVenuePosition
2011 Design optimization of concentric tube robots based on task and anatomical constraints
abstract
Concentric tube robots are a novel continuum robot technology that is well suited to minimally invasive surgeries inside small body cavities such as the heart. These robots are constructed of concentrically combined pre-curved elastic tubes to form 3D curves. Each telescopic section of the robot is either of fixed or variable curvature. One advantage of this approach is that the component tube curvatures, lengths and stiffnesses can easily be fabricated to be procedure- and patient-specific. This paper proposes an optimization framework for solving the robot design problem. Given a 3D description of the constraining anatomy, the number of fixed and variable curvature robot sections and a tip workspace description, the algorithm solves for the robot design that possesses the desired workspace, remains inside the anatomical constraints and minimizes the curvature and length of all sections. The approach is illustrated in the context of beating-heart closure of atrial septal defects.
Chris Bedell, Jesse Lock, Andrew H. C. Gosline, Pierre E. Dupont
ICRA1