51,446 research outputs found
Optimal Actuator Location of the Minimum Norm Controls for Stochastic Heat Equations
In this paper, we study the approximate controllability for the stochastic
heat equation over measurable sets, and the optimal actuator location of the
minimum norm controls. We formulate a relaxed optimization problem for both
actuator location and its corresponding minimum norm control into a two-person
zero sum game problem and develop a sufficient and necessary condition for the
optimal solution via Nash equilibrium. At last, we prove that the relaxed
optimal solution is an optimal actuator location for the classical problem
Observability Inequality of Backward Stochastic Heat Equations for Measurable Sets and Its Applications
This paper aims to provide directly the observability inequality of backward
stochastic heat equations for measurable sets. As an immediate application, the
null controllability of the forward heat equations is obtained. Moreover, an
interesting relaxed optimal actuator location problem is formulated, and the
existence of its solution is proved. Finally, the solution is characterized by
a Nash equilibrium of the associated game problem
Multi-stage Suture Detection for Robot Assisted Anastomosis based on Deep Learning
In robotic surgery, task automation and learning from demonstration combined
with human supervision is an emerging trend for many new surgical robot
platforms. One such task is automated anastomosis, which requires bimanual
needle handling and suture detection. Due to the complexity of the surgical
environment and varying patient anatomies, reliable suture detection is
difficult, which is further complicated by occlusion and thread topologies. In
this paper, we propose a multi-stage framework for suture thread detection
based on deep learning. Fully convolutional neural networks are used to obtain
the initial detection and the overlapping status of suture thread, which are
later fused with the original image to learn a gradient road map of the thread.
Based on the gradient road map, multiple segments of the thread are extracted
and linked to form the whole thread using a curvilinear structure detector.
Experiments on two different types of sutures demonstrate the accuracy of the
proposed framework.Comment: Submitted to ICRA 201
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