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检索条件"任意字段=International Conference on Multisensor Fusion and Integration for Intelligent Systems"

共 2566 条记录，以下是21-30 订阅

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

2023 IEEE Symposium Sensor Data Fusion and International Con...

引用

2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

ISBN: (纸本)9798350382587

The proceedings contain 37 papers. The topics discussed include: optical flow revisited: how good is dense deep learning based optical flow?;2D-HASAP: two-dimensional heading-aided single-anchor positioning via hidden Markov model map-matching;localization and classification of partial occluded deformable objects with application on the downs and feathers;classification of uncertainty sources for reliable Bayesian estimation;air-to-ground targets re-identification from non-aligned and partially overlapped cameras by homograhy transfer and iterative closest point with Huber loss function;online multi-IMU calibration using visual-inertial odometry;groups of heterogeneous autonomous systems in area reconnaissance;and extended object tracking with doppler velocity-based point registration.

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Groups of heterogeneous autonomous systems in area reconnaissance

Groups of heterogeneous autonomous systems in area reconnais...

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

作者： Tchouchenkov, Igor Segor, Florian Karlsruhe Germany

ISBN: (纸本)9798350382587

Parallel deployment of heterogeneous autonomous assets as swarms or cooperating teams has become a realistic operational scenario nowadays. Especially in time-critical tasks (e.g. the search for missing persons, disaster relief and modern warfare operations) mass deployment of unmanned vehicles can be useful for obvious reasons. An important basis for efficient and effective autonomous reconnaissance or surveillance with an increasing task complexity or number of mobile vehicles is movement optimization considering the boundary conditions like vehicles or sensor capabilities. Special algorithms for such complex reconnaissance missions have been developed at Fraunhofer IOSB that enable fast appropriate planning and dynamic processing in very different situations with minimal effort of the operator. In the following, two reconnaissance methods are described in more detail and their possibilities are discussed and compared. © 2023 IEEE.

关键词： Drones

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Wideband Direction-Of-Arrival Estimation Using Microphone Arrays

Wideband Direction-Of-Arrival Estimation Using Microphone Ar...

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

作者： Varela, MacArena Wirth, Wulf-Dieter Oispuu, Marc Fraunhofer Fkie Sensor Data and Information Fusion Wachtberg Germany

ISBN: (纸本)9798350382587

Acoustic direction estimation for outdoor source localization, such as impulsive sounds and drones, holds significant importance in applications related to search-and-rescue, surveillance, and security. To achieve this goal, microphone arrays, in combination with signal processing methods such as beamforming and detection, can be employed. The choice of beamforming technique can significantly impact the estimated direction of arrival (DOA) of sound events, e.g. due to different levels of sidelobes in the directivity pattern. Hence, this paper introduces a novel coherent broadband beamforming method and compares it to the well-established delay-and-sum beamformer. Both approaches are applied to experimental field data collected in free-field conditions, with a focus on drone rotor noise. © 2023 IEEE.

关键词： Beamforming

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Towards Adaptive Environment Perception and Understanding for Autonomous Mobile Robots

Towards Adaptive Environment Perception and Understanding fo...

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

作者： Hofmann, Christian Taliercio, Franca Walter, Jonas Franke, Jörg Reitelshöfer, Sebastian Friedrich-Alexander-Universität Erlangen-Nürnberg Institute for Factory Automation and Production Systems Erlangen Germany

ISBN: (纸本)9798350382587

Autonomous mobile robots (AMRs) are increasingly used in various applications like intralogistics, hospitality and agriculture. Though, their software and abilities are still mainly designed and implemented for specific environments and tasks, impeding an even more widespread deployment of AMRs. Their environment perception and understanding lacks automated adaption to specific operating environments and *** this paper, we propose a software architecture that allows the automated adaption of AMRs' environment perception and understanding to different operating environments. Further, we provide a concise review of state-of-the-art approaches and technologies needed. We present an exemplary implementation and evaluate the proposed architecture. On this basis, advantages and open research questions of the architecture are derived. © 2023 IEEE.

关键词： Semantics

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Encrypted Fast Covariance Intersection Without Leaking fusion Weights

Encrypted Fast Covariance Intersection Without Leaking Fusio...

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IEEE international conference on multisensor fusion and integration for intelligent systems (MFI)

作者： Ristic, Marko Noack, Benjamin Otto von Guericke Univ OVGU Inst Intelligent Cooperating Syst ICS Autonomous Multisensor Syst Grp AMS Magdeburg Germany

ISBN: (数字)9781665460262

ISBN: (纸本)9781665460262

State estimate fusion is a common requirement in distributed sensor networks and can be complicated by untrusted participants or network eavesdroppers. We present a method for computing the common Fast Covariance Intersection fusion algorithm on an untrusted cloud without disclosing individual estimates or the fused result. In an existing solution to this problem, fusion weights corresponding to estimate errors are leaked to the cloud to perform the fusion. In this work, we present a method that guarantees no data identifying estimators or their estimated values is leaked to the cloud by requiring an additional computation step by the party querying the cloud for the fused result. The Paillier encryption scheme is used to homomorphically compute separate parts of the computation that can be combined after decryption. This encrypted Fast Covariance Intersection algorithm can be used in scenarios where the fusing cloud is not trusted and any information on estimator performances must remain confidential.

关键词： Cloud computing Computational modeling Weather forecasting Estimation Encryption Task analysis intelligent systems

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multisensor Estimation fusion Based on Kernel Mean Embedding 27

Multisensor Estimation Fusion Based on Kernel Mean Embedding

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27th international conference on Information fusion (fusion)

作者： Luo, Mingjie Zhou, Jie Zou, Qingke Sichuan Univ Coll Math Chengdu 610064 Sichuan Peoples R China

ISBN: (纸本)9798350371420;9781737749769

This work deals with the estimation fusion for distributed multisensor systems under the framework of local estimates being taken as probability density functions. The estimation fusion is formulated to an optimization problem that minimizes the sum of squared distances between the fused probability density and each local probability density. The maximum mean discrepancy, which is a distance between two probability density functions, is considered. It is defined by the kernel mean embeddings from the probability density function space to a reproducing kernel Hilbert space. For the quadratic, cubic and Gaussian kernels, either the analytical solutions are derived or the numerical methods are developed for solving the aforementioned optimization problem. Numerical experiments are provided to illustrate the performance of the proposed estimation fusion methods.

关键词： Distributed estimation fusion reproducing kernel Hilbert space kernel mean embedding maximum mean discrepancy

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Classification of Uncertainty Sources for Reliable Bayesian Estimation

Classification of Uncertainty Sources for Reliable Bayesian ...

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

作者： Duník, Jinřich Straka, Ondřej Noack, Benjamin University of West Bohemia Faculty of Applied Sciences Department of Cybernetics Univerzitní 8 Pilsen306 14 Czech Republic Otto von Guericke University Magdeburg Institute for Intelligent Cooperating Systems Autonomous Multisensor Systems Group Magdeburg Germany

ISBN: (纸本)9798350382587

Recursive Bayesian estimation has emerged as a key tool for estimating the unknown state of a system. The wide range of applications has resulted in a correspondingly wide variety of estimation algorithms. The Kalman filter and its derivatives, like extended and unscented Kalman filters, are the most prominent examples, while non-Gaussian full-blown filters are on the rise with the increasing availability of computational power. The filtering results are naturally accompanied by an assessment of the estimate's uncertainty. However, this assessment may mislead the user into believing that the estimate is reliable, i.e., that the uncertainty reported by the filter matches the actual uncertainty. For a filter to assess its uncertainty correctly, often strict requirements must be met. The misalignment can be attributed to different origins, for which this work proposes a classification covering different stages of a filter design. Approximations and assumptions made in each class impair the filter's reliability. This paper provides a conceptual perspective on how reliability can be defined and how it can be assessed. An example of a reliability index is examined in a simulated scenario to illustrate how it can contribute to a better understanding of the overall performance of a filter. © 2023 IEEE.

关键词： Reliability

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Self-organising Distributed Sensor fusion Networks for Hierarchical Swarm Control and Supervision

Self-organising Distributed Sensor Fusion Networks for Hiera...

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

作者： Rockbach, Jonas D. Schlangen, Isabel Bennewitz, Maren Fraunhofer Fkie Human-Machine Systems Wachtberg Germany Fraunhofer Fkie Sensor Data and Information Fusion Wachtberg Germany University of Bonn Humanoid Robots Lab Bonn Germany

ISBN: (纸本)9798350382587

Mobile sensor networks can be realised using robot swarms where simple robots interact only locally to achieve swarm scalability and robustness. One of the main challenges is to develop suitable sensor fusion methods, both for autonomous swarms and human supervisory control, without gravely reducing the benefits of decentralisation. Hence, we introduce the Self-organising Hierarchical Extending (SHE) approach for distributed sensor fusion in robot swarms under communication and control constraints found in harsh, heterogeneous, and dynamic environments. The SHE approach is designed for fast autonomous swarm control in local environments, radially extending the sensor-effector range of a central node for global autonomous or human supervisory control. We discuss possible approaches to distributed object search and a SHE fusion architecture. An exemplary simulation based on the virtual pheromone approach provides a proof of concept for a self-organised, hierarchical, and extending fusion topology with a minimal robot controller. © 2023 IEEE.

关键词： Sensor networks

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On Visualisation of Linear Estimation and fusion: From Equations to Ellipses

On Visualisation of Linear Estimation and Fusion: From Equat...

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

作者： Ajgl, Jiří Straka, Ondřej University of West Bohemia Faculty of Applied Sciences European Centre of Excellence - New Technologies for Information Society Department of Cybernetics Pilsen Czech Republic

ISBN: (纸本)9798350382587

Visualisation of mathematical objects often leads to faster and easier comprehension of theories. On the other hand, deriving conclusions exclusively from a graphical interpretation can be misleading. A typical case in estimation is an ellipse, which corresponds to contour lines of a bivariate Gaussian density. This paper combines insights from various areas. Algebraic relations are presented first, geometric objects are shown subsequently. Constructions of ellipses by determining radii and positions of tangent lines are discussed. The stress is laid on exposition of linear estimation with a focus on methodology of fusion of estimates, especially in the case when cross-correlations of estimation errors are not fully known. The exposition also covers multidimensional variables, where the ellipses become ellipsoids. © 2023 IEEE.

关键词： Visualization

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Architecture and design of AI based air situation assessment

Architecture and design of AI based air situation assessment

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2023 IEEE Symposium Sensor Data fusion and international conference on multisensor fusion and integration, SDF-MFI 2023

作者： Gehlen, Joshua Govaers, Felix Ulmke, Martin Fischer, Andre Fraunhofer Fkie Sensor Data and Information Fusion Wachtberg53343 Germany Airbus Defence and Space GmbH Airspace Control C2 Solutions Immenstaad88090 Germany

ISBN: (纸本)9798350382587

This paper focuses on the architecture and design criteria of an artificial intelligence-based military air situation assessment system, specifically on the expanded classification of hostile entities and their intentions. The ability to accurately expand classification information with details like its intention is critical for military operations. The paper presents a new architecture that is based on artificial intelligence and is specifically designed for this purpose. The design criteria include the selection of appropriate algorithms that are suitable for the classification of hostile entities and their targets based on a small set of data. The paper also discusses the importance of integrating expert knowledge, such as military-specific threat profiles and tactics, into the system. The presented design criteria improves the classification of hostile entities and their targets, thereby increasing the safety and success of military missions. © 2023 IEEE.

关键词： Bayesian networks

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