Motion compensation is a prominent application in robotic beating heart surgery, with significant potential benefits for both surgeons and patients. In this paper we investigate an activate assistance control scheme o...
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ISBN:
(纸本)9781479901890
Motion compensation is a prominent application in robotic beating heart surgery, with significant potential benefits for both surgeons and patients. In this paper we investigate an activate assistance control scheme on a simple tracking task, which helps the surgeon guide the robot on a predefined reference. The control is implemented on top of a shared control system, which serves as a basis for implementing higher level controllers. Experiments with a trained surgeon are also presented, which show the positive effect of the approach.
This paper proposes a novel technique for applying virtual fixtures in a changing environment. The main targeted application is robotic beating heart surgery, which enables the surgeon to operate directly on a beating...
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ISBN:
(纸本)9781479909964
This paper proposes a novel technique for applying virtual fixtures in a changing environment. The main targeted application is robotic beating heart surgery, which enables the surgeon to operate directly on a beating heart. Using a motion compensation framework, the motion of the heart surface is stabilized in a virtual space, which is presented to the surgeon to operate in. Consequently, the fixture is implemented in this static space, bypassing problems of dynamic fixtures such as position update, placement and force transients. Randomized experiments were performed using a trained surgeon comparing our approach to simple motion compensation and no compensation at all. The positive effect of the fixture in surgical accuracy for a tracking task is also discussed.
A new soft computing method using Fuzzy Cognitive Maps for modeling and predicting Parkinson's disease has been proposed. A decision support system based on human knowledge and experience, with a Fuzzy Cognitive M...
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ISBN:
(纸本)9781479909964
A new soft computing method using Fuzzy Cognitive Maps for modeling and predicting Parkinson's disease has been proposed. A decision support system based on human knowledge and experience, with a Fuzzy Cognitive Map trained using unsupervised Nonlinear Hebbian Leanring algorithm are proposed. The basic theories of this learning method are reviewed and presented. The initial values of concepts are represented as fuzzy membership values and trained to get new updated weight matrix and new concept values. Simulations are performed and very interesting results are obtained and discussed. A comparison between the results with and without a learning algorithm is considered.
A hybrid energy system is an excellent solution to the problem of not being able to meet the power demand using a single energy source. Such a system incorporates a combination of one or more renewable energy source (...
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ISBN:
(纸本)9781479909964
A hybrid energy system is an excellent solution to the problem of not being able to meet the power demand using a single energy source. Such a system incorporates a combination of one or more renewable energy source (RES) such as solar photovoltaic, wind-energy, geothermal, and could also have a conventional generator for backup. This paper discusses different system components of a hybrid energy system and develops a theoretical model to find an acceptable combination of energy components. A theoretical model of a hybrid energy system, using Fuzzy Cognitive Maps (FCMs) and learning algorithms, is presented. FCMs perform well even with missing data and despite nonlinearities, which such systems usually have. The simulation results verified the effectiveness and reliability of the proposed hybrid energy system.
In this paper, a control problem for a class of nonlinear coupled dynamical systems is proposed and a continuous nonlinear feedback control law is designed using direct Lyapunov method to solve the proposed control pr...
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In this paper, a control problem for a class of nonlinear coupled dynamical systems is proposed and a continuous nonlinear feedback control law is designed using direct Lyapunov method to solve the proposed control problem. Moreover, synchronization problem for a special case of this class nonlinear coupled dynamical systems is concerned. Numerical examples show the effectiveness and advantage of the designed continuous nonlinear control law and derived synchronization result.
Strategic perspectives of sustainable development are considered and discussed. The concept of environmental sustainability is addressed and its relation to sustainable development is discussed. By undertaking mathema...
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Strategic perspectives of sustainable development are considered and discussed. The concept of environmental sustainability is addressed and its relation to sustainable development is discussed. By undertaking mathematical calculations and geometrical axioms, this study shows a different approach in regional development based on various settings between three fundamental concepts: Education + Research- Innovation + Entrepreneurship. The Triangle of Knowledge (ToK) is defined using the above three fundamental concepts. The Triangle of Knowledge refers to the interaction between education, research-innovation and entrepreneurship, which are key drivers for the Knowledge-Based-Society (KBS). This concept relates to the need to pay attention on an equal basis to the three factors on a systemic and continuous way. Particular contribution to the Triangle of Knowledge is attempted, through the introduction of Excellence within the proposed Equilateral Triangular Model Approach (ETMA). A new performance index is defined, the Excellence Performance Indicator (EPI) and used on this new proposed methodology of ETMA. A number of simulation runs using ETMA and the Triangle of Knowledge(ToK) is performed and a number of interesting results are obtained and discussed.
This paper presents a shared control approach for motion compensation in robotic beating heart surgery. Motion compensation consists of three main tasks; motion synchronization, image stabilization and shared control....
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ISBN:
(纸本)9781467356404
This paper presents a shared control approach for motion compensation in robotic beating heart surgery. Motion compensation consists of three main tasks; motion synchronization, image stabilization and shared control. The paper discusses a unifying framework under which the three tasks combine seamlessly. In this work, the planar 1-manifold case is considered, where a strip-wise affine map is performed to achieve image stabilization onto a canonical space, where shared control emerges naturally. A prototype teleoperation system is also described, implementing the algorithms. Experiments were performed with medically trained users, and the positive effect of motion compensation is analyzed.
In this paper experimental results of testing slip-based traction control system (TCS) with an on-line road condition estimation are presented. TCS is designed for a car with in-wheel electric motors, so that estimati...
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ISBN:
(纸本)9781479909964
In this paper experimental results of testing slip-based traction control system (TCS) with an on-line road condition estimation are presented. TCS is designed for a car with in-wheel electric motors, so that estimation and control are implemented independently for each wheel thus enabling the optimal friction coefficient for every wheel, even if they are on different surfaces or have different tire characteristics. A road condition is approximated using a function which is estimated in the real-time and used as the input to the TCS. The design of the presented TCS is based on the wheel slip ratio, controlled to it's optimal value by a PI controller and with the addition of a feedforward branch for the transition response speed up. System is tested on a newly developed experimental setup consisting of the wheel with embedded (in-wheel) motor rolling on the metal drum loaded by the second motor simulating car behaviour.
The most standard image object detectors are usually comprised of one or multiple feature extractors or classifiers within a sliding window framework. Nevertheless, this type of approach has demonstrated a very limite...
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The most standard image object detectors are usually comprised of one or multiple feature extractors or classifiers within a sliding window framework. Nevertheless, this type of approach has demonstrated a very limited performance under datasets of cluttered scenes and real life situations. To tackle these issues, LIDAR space is exploited here in order to detect 2D objects in 3D space, avoiding all the inherent problems of regular sliding window techniques. Additionally, we propose a relational parts-based pedestrian detection in a probabilistic non-iid framework. With the proposed framework, we have achieved state-of-the-art performance in a pedestrian dataset gathered in a challenging urban scenario. The proposed system demonstrated superior performance in comparison with pure sliding-window-based image detectors.
A method for Kinect sensor was presented based on SLAM (simultaneous localization and mapping) problem via inverse depth parameterization model, where the depth of features from Kinect was employed to improve the conv...
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A method for Kinect sensor was presented based on SLAM (simultaneous localization and mapping) problem via inverse depth parameterization model, where the depth of features from Kinect was employed to improve the convergence of method. To further improve the accuracy and robustness, SURF (speed up robust features) feature detection operator was adopted to extract image features, and extended Kalman filter (EKF) was used to estimate the trajectory of camera and the position of features. Experimental results are given to demonstrate the effectiveness and applicability of the proposed method.
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