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Hunter B. Gilbert

8 accepted papers

2019

Learning to Navigate Endoscopic Capsule Robots

RA-L 2019

Deep reinforcement learning (DRL) techniques have been successful in several domains, such as physical simulations, computer games, and simulated robotic tasks, yet the transfer of these successful learning concepts from simulations into the real world scenarios remains still a challenge. In this le

Cited by 28SourceScholar
2018

Endo-VMFuseNet: A Deep Visual-Magnetic Sensor Fusion Approach for Endoscopic Capsule Robots

ICRA 2018poster

In the last decade, researchers and medical device companies have made major advances towards transforming passive capsule endoscopes into active medical robots. One of the major challenges is to endow capsule robots with accurate perception of the environment inside the human body, which will provi…

Cited by 8SourceScholar
2015

A motion planning approach to automatic obstacle avoidance during concentric tube robot teleoperation

ICRA 2015poster

Concentric tube robots are thin, tentacle-like devices that can move along curved paths and can potentially enable new, less invasive surgical procedures. Safe and effective operation of this type of robot requires that the robot's shaft avoid sensitive anatomical structures (e.g., critical vessels…

Cited by 61SourceScholar
2015

Designing snap-free concentric tube robots: A local bifurcation approach

ICRA 2015poster

In designing concentric tube robots, it is often desirable to use curvatures that are as high as possible. However, with high curvatures comes the potential for elastic instabilities. This can be addressed by motion planning or by designing the robot to preclude the possibility of instability. In th…

Cited by 55SourceScholar