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In this paper we present a novel on-line method to recursively align point clouds. By considering each point together with the local features of the surface (normal and curvature), our method takes advantage of the 3D structure around the points for the determination of the data association between two clouds. The algorithm relies on a least squares formulation of the alignment problem, that minimizes...
This paper considers subspace recovery in the presence of outliers in a decentralized setting. The intrinsic low-dimensional geometry of the data is exploited to substantially reduce the processing and communication overhead given limited sensing and communication resources at the sensing nodes. A small subset of the data is first selected. The data is embedded into a random low-dimensional subspace...
A number of open cyber-security challenges are arising due to the rapidly evolving scale, complexity, and heterogeneity of modern IT systems and networks. The ease with which copious volumes of operational data can be collected from such systems has produced a strong interest in the use of machine learning (ML) for cyber-security, provided that ML can itself be made sufficiently immune to attack....
We consider the design of self-triggered controllers for Lipschitz nonlinear systems subject to additive disturbances. The goal of the controller design is to avoid measurements and input changes as long as possible, while guaranteeing good performance subject to the worst case disturbances. Furthermore, the controller should be practically implementable. The controller is based on the emulation of...
A closed-loop artificial pancreas (AP) to provide automated treatment for people with type 1 diabetes mellitus has the potential to improve patient health outcomes; however, the system's success hinges on its ability to quickly detect and react to changing blood glucose concentrations (BG). In this study, the impact of measurement lag on AP robust stability, performance, and time-domain disturbance...
Resolvers are used for both absolute angular and linear position sensing. A robust amplitude to phase converter is described for the determination of position from the sine and cosine output signals of the resolver. The scheme is based on a linearization technique for converting the co-sinusoids into a nearly perfect triangular signal from which the angle is determined using simple linear equation...
Animals show remarkable capabilities in navigating their habitat in a fully autonomous and energy-efficient way. In many species, these capabilities rely on a process called path integration, which enables them to estimate their current location and to find their way back home after long-distance journeys. Path integration is achieved by integrating compass and odometric cues. Here we introduce a...
Sufficient conditions for stability of feedback interconnections of negative imaginary systems are derived via an integral quadratic constraint (IQC) approach. These extend existing results in the literature by exploiting the flexibility present at the static and infinite frequencies to reduce conservatism. Negative imaginary transfer functions with poles on the imaginary axis are accommodated using...
Wearable augmented reality (AR) systems have the potential to significantly lower the barriers to accessing information, while leaving the focus of the user's attention on the real world. To reveal their true potential, the human-machine interface is crucial. A touchless point-and-click interface for wearable AR systems may be suitable for use in many real-world applications, but it demands fingertip...
A control algorithm for finite-time tracking of quadrotor is introduced. The algorithm is based on use of feedback linearization method and finite-time output control presented in [17]. In comparison with commonly used in practice control methods like PD-controller the proposed method allows to estimate the first derivatives of the generalized coordinates, that enable to reduce the number of necessary...
Existing methods for smart data reduction are typically sensitive to outlier data that do not follow postulated data models. We propose robust censoring as a joint approach unifying the concepts of robust learning and data censoring. We focus on linear inverse problems and formulate robust censoring through a sparse sensing operator, which is a non-convex bilinear problem. We propose two solvers,...
Depth sensors based on Time-of-Flight (ToF) and Phase Shifting (PS) have complementary strengths and weaknesses. ToF can provide real-time depth but limited in resolution and sensitive to noise. PS can generate accurate and robust depth with high resolution but requires a number of patterns that leads to high latency. In this paper, we propose a novel fusion framework to take advantages of both ToF...
The HiNCube project ran from 2006 to 2013 where a group of students from Narvik University College in Norway designed, built and launched a pico-satellite. Unfortunately, no communication link was established after launch, and this paper details the overall design and highlights many of the different problems and challenges that arose through the project.
Cognitive wireless sensor networks (CWSNs) become promising infrastructures, which can improve spectrum utilization of traditional wireless sensor networks (WSNs). For cognition in WSNs, spectrum sensing is one of the most crucial function to prevent hazardous interferences with the licensed users and to identify available spectrum for improving the spectrum utilization. In this paper, we propose...
This paper presents experimental results of a sensorless control strategy for PWM rectifiers with active filtering function. The proposed technique, already presented for PWM rectifiers, has the capability to reject harmonic components from the grid, and can be employed for harmonic mitigation of shunt connected load. The mitigation of harmonics of the current shaping control is improved with a multiple...
Learning and recognizing the physical activities of human based on wearable sensor has a wide range of applications in many fields such as assistive healthcare and security surveillance. In this paper, we propose an activity recognition framework based on extremely randomized trees and guided random forest to recognize both simple and complex activities from wearable sensor. In order to recognize...
Due to great advancement in the field of science and technology, Wireless Sensor Network (WSN) has been become one of the most attractive and intriguing research area in last few years. Large-scale sensor networks has been deployed by interconnecting several hundred to a few thousand sensors nodes opens up diverse technical challenges and tremendous application possibilities. This paper presents a...
In this paper, we present an object-centric, fixed-dimensional 3D shape representation for robust matching of partially observed object shapes, which is an important component for object categorization from 3D data. A main problem when working with RGB-D data from stereo, Kinect, or laser sensors is that the 3D information is typically quite noisy. For that reason, we accumulate shape information...
Spectrum sensing is the process of identifying idle spectrums and utilizing them by the secondary users such that there is no inference with primary users. Cognitive Radio Network's (CRN) primary challenge is sensing of idle spectrum and efficiently handling that spectrum by the secondary user nodes. The effective and efficient spectrum sensing can achieve by enabling cooperation between nodes to...
This paper presents a novel robust method of self-corrective Initial Alignment of a stationary SINS1 with respect to local-level frame (NED-frame) depending only on the output of a strap-down IMU2. The proposed method provides a superior performance compared to traditionally-known self-corrective initial alignment methods. The main contribution of this paper is the development of a new algorithm which...
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