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Actuated reflector-based three-dimensional ultrasound imaging with adaptive-delay synthetic aperture focusing

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arXiv 2021年

作者： Tang, Yichuan Tsumura, Ryosuke Kaminski, Jakub T. Zhang, Haichong K. The Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Biomedical Engineering Computer Science and Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Three-dimensional (3D) ultrasound (US) imaging addresses the limitation in field-of-view (FOV) in conventional two-dimensional (2D) US imaging by providing 3D viewing of the anatomy. 3D US imaging has been extensively adapted for diagnosis and image-guided surgical intervention. However, conventional approaches to implement 3D US imaging require either expensive and sophisticated 2D array transducers, or external actuation mechanisms to move a one-dimensional array mechanically. Here, we propose a 3D US imaging mechanism using actuated acoustic reflector instead of the sensor elements for volume acquisition with significantly extended 3D FOV, which can be implemented with simple hardware and compact size. To improve image quality on the elevation plane, we introduce an adaptive-delay synthetic aperture focusing (AD-SAF) method for elevation beamforming. We first evaluated the proposed imaging mechanism and AD-SAF with simulated point targets and cysts targets. Results of point targets suggested improved image quality on the elevation plane, and results of cysts targets demonstrated a potential to improve 3D visualization of human anatomy. We built a prototype imaging system that has a 3D FOV of 38 mm (lateral) by 38 mm (elevation) by 50 mm (axial) and collected data in imaging experiments with phantoms. Experimental data showed consistency with simulation results. The AD-SAF method enhanced quantifying the cyst volume size in the breast mimicking phantom compared to without elevation beamforming. These results suggested that the proposed 3D US imaging mechanism could potentially be applied in clinical scenarios. Copyright © 2021, The Authors. All rights reserved.

关键词： Phantoms

Synthesis of Proactive Sensor Placement In Probabilistic Attack Graphs

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arXiv 2022年

作者： Li, Lening Ma, Haoxiang Han, Shuo Fu, Jie Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Electrical & Computer Engineering University of Florida GainesvilleFL32611 United States The Department of Electrical & Computer Engineering University of Illinois at Chicago ChicagoIL60607 United States

This paper studies the deployment of joint moving target defense (MTD) and deception against multi-stage cyberattacks. Given the system equipped with MTD that randomizes between different configurations, we investigate how to allocate a bounded number of sensors in each configuration to optimize the attack detection rate before the attacker achieves its objective. Specifically, two types of sensors are considered: intrusion detectors that are observable by the attacker and stealthy sensors that are not observable to the attacker. We propose a two-step optimization-based approach for allocating intrusion detectors and stealthy sensors: Firstly, the defender allocates intrusion detectors assuming the attacker will best respond to evade detection by intrusion detectors. Secondly, the defender will allocate stealthy sensors, given the best response attack strategy computed in the first step, to further reduce the attacker's chance of success. We illustrate the effectiveness of the proposed methods using a cyber defense example. Copyright © 2022, The Authors. All rights reserved.

关键词： Intrusion detection

Classification of Infant Sleep/Wake States: Cross-Attention among Large Scale Pretrained Transformer Networks using Audio, ECG, and IMU Data

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arXiv 2023年

作者： Chang, Kai Chieh Hasegawa-Johnson, Mark McElwain, Nancy L. Islam, Bashima Department of Electrical and Computer Engineering University of Illinois Urbana Champaign United States Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign United States Department of Human Development and Family Studies University of Illinois Urbana-Champaign United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute United States

Infant sleep is critical to brain and behavioral development. Prior studies on infant sleep/wake classification have been largely limited to reliance on expensive and burdensome polysomnography (PSG) tests in the laboratory or wearable devices that collect single-modality data. To facilitate data collection and accuracy of detection, we aimed to advance this field of study by using a multi-modal wearable device, LittleBeats (LB), to collect audio, electrocardiogram (ECG), and inertial measurement unit (IMU) data among a cohort of 28 infants. We employed a 3-branch (audio/ECG/IMU) large scale transformer-based neural network (NN) to demonstrate the potential of such multi-modal data. We pretrained each branch independently with its respective modality, then finetuned the model by fusing the pretrained transformer layers with cross-attention. We show that multi-modal data significantly improves sleep/wake classification (accuracy = 0.880), compared with use of a single modality (accuracy = 0.732). Our approach to multi-modal mid-level fusion may be adaptable to a diverse range of architectures and tasks, expanding future directions of infant behavioral research. © 2023, CC BY.

关键词： Electrocardiograms

CoFi: Coarse-to-fine ICP for LiDAR Localization in an efficient long-lasting point cloud map

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arXiv 2021年

作者： Lyu, Yecheng Huang, Xinming Zhang, Ziming Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

— LiDAR odometry and localization has attracted increasing research interest in recent years. In the existing works, iterative closest point (ICP) is widely used since it is precise and efficient. Due to its non-convexity and its local iterative strategy, however, ICP-based method easily falls into local optima, which in turn calls for a precise initialization. In this paper, we propose CoFi, a Coarse-to-Fine ICP algorithm for LiDAR localization. Specifically, the proposed algorithm down-samples the input point sets under multiple voxel resolution, and gradually refines the transformation from the coarse point sets to the fine-grained point sets. In addition, we propose a map based LiDAR localization algorithm that extracts semantic feature points from the LiDAR frames and apply CoFi to estimate the pose on an efficient point cloud map. With the help of the Cylinder3D algorithm for LiDAR scan semantic segmentation, the proposed CoFi localization algorithm demonstrates the state-of-the-art performance on the KITTI odometry benchmark, with significant improvement over the literature. Copyright © 2021, The Authors. All rights reserved.

关键词： Geometry

Enabling 3D Object Detection with a Low-Resolution LiDAR

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arXiv 2021年

作者： Bai, Lin Zhao, Yiming Huang, Xinming The Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Light Detection And Ranging (LiDAR) has been widely used in autonomous vehicles for perception and localization. However, the cost of a high-resolution LiDAR is still prohibitively expensive, while its low-resolution counterpart is much more affordable. Therefore, using low-resolution LiDAR for autonomous driving is an economically viable solution, but the point cloud sparsity makes it extremely challenging. In this paper, we propose a two-stage neural network framework that enables 3D object detection using a low-resolution LiDAR. Taking input from a low-resolution LiDAR point cloud and a monocular camera image, a depth completion network is employed to produce dense point cloud that is subsequently processed by a voxel-based network for 3D object detection. Evaluated with KITTI dataset for 3D object detection in Bird-Eye View (BEV), the experimental result shows that the proposed approach performs significantly better than directly applying the 16-line LiDAR point cloud for object detection. For both easy and moderate cases, our 3D vehicle detection results are close to those using 64-line high-resolution LiDARs. Copyright © 2021, The Authors. All rights reserved.

关键词： Object detection

LQG Reference Tracking with Safety and Reachability Guarantees under Unknown False Data Injection Attacks

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arXiv 2021年

作者： Li, Zhouchi Niu, Luyao Clark, Andrew Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

We investigate a linear quadratic Gaussian (LQG) tracking problem with safety and reachability constraints in the presence of an adversary who mounts an FDI attack on an unknown set of sensors. For each possible set of compromised sensors, we maintain a state estimator disregarding the sensors in that set, and calculate the optimal LQG control input at each time based on this estimate. We propose a control policy which constrains the control input to lie within a fixed distance of the optimal control input corresponding to each state estimate. The control input is obtained at each time step by solving a quadratically constrained quadratic program (QCQP). We prove that our policy can achieve a desired probability of safety and reachability using the barrier certificate method. Our control policy is evaluated via a numerical case study. Copyright © 2021, The Authors. All rights reserved.

关键词： Quadratic programming

Abstraction-Free Control Synthesis to Satisfy Temporal Logic Constraints under Sensor Faults and Attacks

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Abstraction-Free Control Synthesis to Satisfy Temporal Logic...

IEEE Conference on Decision and Control

作者： Luyao Niu Zhouchi Li Andrew Clark Department of Electrical and Computer Engineering Network Security Lab University of Washington Seattle WA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA Department McKelvey School of Engineering Electrical and Systems Engineering Washington University in St. Louis St. Louis MO

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We study the problem of synthesizing a controller to satisfy a complex task in the presence of sensor faults and attacks. We model the task using Gaussian distribution temporal logic (GDTL), and propose a solution approach that does not rely on computing any finite abstraction to model the system. We decompose the GDTL specification into a sequence of reach-avoid sub-tasks. We develop a class of fault-tolerant finite time convergence control barrier functions (CBFs) to guarantee that a dynamical system reaches a set within finite time almost surely in the presence of malicious attacks. We use the fault-tolerant finite time convergence CBFs to guarantee the satisfaction of ‘reach’ property. We ensure ‘avoid’ part in each sub-task using fault-tolerant zeroing CBFs. These fault-tolerant CBFs formulate a set of linear constraints on the control input for each sub-task. We prove that if the error incurred by system state estimation is bounded by a certain threshold, then our synthesized controller fulfills each reach-avoid sub-task almost surely for any possible sensor fault and attack, and thus the GDTL specification is satisfied with probability one. We demonstrate our proposed approach using a numerical study on the coordination of two wheeled mobile robots.

关键词： Fault tolerance Sufficient conditions Computational modeling Fault tolerant systems Gaussian distribution Robot sensing systems Mobile robots

LiDAR odometry methodologies for autonomous driving: A survey

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arXiv 2021年

作者： Jonnavithula, Nikhil Lyu, Yecheng Zhang, Ziming Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Vehicle odometry is an essential component of an automated driving system as it computes the vehicle's position and orientation. The odometry module has a higher demand and impact in urban areas where the global navigation satellite system (GNSS) signal is weak and noisy. Traditional visual odometry methods suffer from the diverse illumination status and get disparities during pose estimation, which results in significant errors as the error accumulates. Odometry using light detection and ranging (LiDAR) devices has attracted increasing research interest as LiDAR devices are robust to illumination variations. In this survey, we examine the existing LiDAR odometry methods and summarize the pipeline and delineate the several intermediate steps. Additionally, the existing LiDAR odometry methods are categorized by their correspondence type, and their advantages, disadvantages, and correlations are analyzed across-category and within-category in each step. Finally, we compare the accuracy and the running speed among these methodologies evaluated over the KITTI odometry dataset and outline promising future research directions. © 2021, CC BY.

关键词： Optical radar

Safety-critical control synthesis for unknown sampled-data systems via control barrier functions

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arXiv 2021年

作者： Niu, Luyao Zhang, Hongchao Clark, Andrew Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

As the complexity of control systems increases, safety becomes an increasingly important property since safety violations can damage the plant and put the system operator in danger. When the system dynamics are unknown, safety-critical synthesis becomes more challenging. Additionally, modern systems are controlled digitally and hence behave as sampled-data systems, i.e., the system dynamics evolve continuously while the control input is applied at discrete time steps. In this paper, we study the problem of control synthesis for safety-critical sampled-data systems with unknown dynamics. We overcome the challenges introduced by sampled-data implementation and unknown dynamics by constructing a set of control barrier function (CBF)-based constraints. By satisfying the constructed CBF constraint at each sampling time, we guarantee the unknown sampled-data system is safe for all time. We formulate a non-convex program to solve for the control signal at each sampling time. We decompose the non-convex program into two convex sub-problems. We illustrate the proposed approach using a numerical case study. © 2021, CC BY.

关键词： Sampled data control systems