2021 IEEE 24th International Conference on Information Fusion (FUSION)最新文献_第4页

Comparison of Discrete and Continuous State Estimation with Focus on Active Flux Scheme 离散状态估计与连续状态估计的比较——以有源磁链方案为重点

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9626836

Jakub Matousek, J. Duník, M. Brandner, V. Elvira

引用次数: 1

State Estimation of Articulated Vehicles Using Deformed Superellipses 基于变形超椭圆的铰接车辆状态估计

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9626881

Lino Antoni Giefer, J. Clemens

{"title":"State Estimation of Articulated Vehicles Using Deformed Superellipses","authors":"Lino Antoni Giefer, J. Clemens","doi":"10.23919/fusion49465.2021.9626881","DOIUrl":"https://doi.org/10.23919/fusion49465.2021.9626881","url":null,"abstract":"State estimation of objects plays an important role in various kinds of applications in the fields of robotics and autonomous vehicles. With the continuous advancement of sensors with high spatial resolution, especially light detection and ranging (LiDAR), the interest in accurate and reliable extended object trackers has grown over the last years. Classical state estimation approaches assume static and symmetric shapes, such as rectangles or ellipses, or compositions of those. The disadvantage of that assumption is obvious: deformations, as in the case of articulated vehicles driving along curves, cannot be captured appropriately. In this paper, we tackle this problem by proposing a novel approach to state estimation employing deformed superellipses. This allows a closed-form mathematical description of an articulated object’s state in the Euclidean plane consisting of its pose and shape. Two additional state parameters are introduced capturing the deformation angle and the joint’s position. We evaluate the proposed approach to state estimation of articulated objects employing a model fitting algorithm of simulated LiDAR measurements and show the improvements compared to classical shape assumptions. Furthermore, we discuss the use of our approach in a tracking algorithm.","PeriodicalId":226850,"journal":{"name":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121542246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extended Object Tracking with Spatial Model Adaptation Using Automotive Radar 基于空间模型自适应的汽车雷达扩展目标跟踪

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9626890

Gang Yao, P. Wang, K. Berntorp, Hassan Mansour, P. Boufounos, P. Orlik

引用次数: 0

Cognitive Active Sonar Tracking for Optimum Performance in Clutter 杂波环境下认知主动声纳跟踪的最佳性能

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9627029

D. Grimmett, D. Abraham, Ricki Alberto

引用次数: 1

Uncertainty-Aware Recurrent Encoder-Decoder Networks for Vessel Trajectory Prediction 船舶轨迹预测的不确定性感知循环编码器-解码器网络

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9626839

Samuele Capobianco, N. Forti, L. Millefiori, P. Braca, P. Willett

引用次数: 11

Observability Informed Partial-Update Schmidt Kalman Filter 可观测性通知部分更新施密特卡尔曼滤波

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9626946

J. H. Ramos, Davis W. Adams, K. Brink, M. Majji

{"title":"Observability Informed Partial-Update Schmidt Kalman Filter","authors":"J. H. Ramos, Davis W. Adams, K. Brink, M. Majji","doi":"10.23919/fusion49465.2021.9626946","DOIUrl":"https://doi.org/10.23919/fusion49465.2021.9626946","url":null,"abstract":"The partial-update filter concept is a recent development that generalizes the Schmidt Kalman filter and extends the range of nonlinearities and uncertainties that a Kalman filter can tolerate. Similar to the Schmidt filter, the intention of the partial-update filter is to ameliorate the negative impact that certain states have within the filter, often due to their poor observability. In contrast with the Schmidt filter, the partial-update filter can update the problematic states at any time step. In practice, the partial-update technique can apply a full (nominal), partial, or no update (Schmidt) to states, depending on user-selected percentages (or weights) that indicate how much of the nominal Kalman update is applied. To date, the update percentages are selected via trial and error, and any change in the system configuration requires re-tuning. Furthermore, because the update percentages are fixed, the partial-update is agnostic to situations where a full update, or even a Schmidt-like filter can be more suitable. To address these drawbacks, this paper proposes two observability informed approaches for online weight selection that do not require manual tuning. The proposed techniques are targeted for systems where the states to be partially updated are only the problematic states. Numerical simulation results demonstrate that the proposed approaches produce estimates comparable to those of a manually fine-tuned fixed partial-update, and that they leverage occasions where local observability increases to produce more accurate estimates.","PeriodicalId":226850,"journal":{"name":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122998492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Distributed MHT with Passive Sensors 具有无源传感器的分布式MHT

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9627003

S. Coraluppi, C. Rago, C. Carthel, Brandon Bale

引用次数: 2

Shooter Localization Based on TDOA and N-Shape Length Measurements of Distributed Microphones 基于TDOA和n形长度测量的分布式传声器射手定位

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9626905

S. Koch, Luisa Still, M. Oispuu, W. Koch

引用次数: 1

Markov Logic meets Graph Neural Networks: A Study for Situational Awareness 马尔可夫逻辑与图神经网络:情境感知的研究

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9627010

V. Nguyen

{"title":"Markov Logic meets Graph Neural Networks: A Study for Situational Awareness","authors":"V. Nguyen","doi":"10.23919/fusion49465.2021.9627010","DOIUrl":"https://doi.org/10.23919/fusion49465.2021.9627010","url":null,"abstract":"Situational awareness requires continual learning from observations and adaptive reasoning from domain and contextual knowledge. The integration of reasoning and learning has been a standing goal of machine learning and AI in general, and a pressing need for real-world situational awareness in particular. Representative techniques among the numerous methods proposed include integrating logics with learning formalisms, whether probabilistic graphical models or neural methods. These techniques are motivated by the need to model and exploit the symmetry, regularities and complex relations between entities exhibited in real world scenarios (in the form of relational or graph data) for effective reasoning and learning. In this work, we investigate the benefits of integrating two prominent methods for reasoning and learning with relational/graph data, Markov Logic Networks (or simply Markov Logic) and Graph Neural Networks. The former is well-recognised for its powerful representation and uncertainty handling, while the latter have gained much attention due to their efficiency in handling large-scale graph datasets. This paper reports on the potential benefits of combining their respective strengths and applying them to a use case illustration in the maritime domain, together with empirical results.","PeriodicalId":226850,"journal":{"name":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126799038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Game-Theoretic Approach for Grace-Period Policy in Supercomputers 超级计算机宽限期策略的博弈论方法

2021 IEEE 24th International Conference on Information Fusion (FUSION) Pub Date : 2021-11-01 DOI: 10.23919/fusion49465.2021.9626952

Fei He, N. Rao, Chris Y. T. Ma

{"title":"Game-Theoretic Approach for Grace-Period Policy in Supercomputers","authors":"Fei He, N. Rao, Chris Y. T. Ma","doi":"10.23919/fusion49465.2021.9626952","DOIUrl":"https://doi.org/10.23919/fusion49465.2021.9626952","url":null,"abstract":"Job scheduling at supercomputing facilities is important for achieving high utilization of these valuable resources while ensuring effective execution of jobs submitted by users. The jobs are scheduled according to their specified resource demands such as expected job completion times, and the available resources based on allocations. Jobs that overrun their allocated times are terminated, for example, after a grace-period. It is non-trivial and often very complex for users to accurately estimate the completion times of their jobs, and consequently they face a dilemma: underestimate the job time to have a higher priority and risk job termination due to overrun, or overestimate it to ensure its completion and risk its delayed execution. In this paper, we investigate whether providing grace-period can benefit facility performance by developing a game- theoretic model between a facility provider and multiple users for a simplified scheduling scenario based on job execution times. We present closed-form expressions for the provider’s and user’s best-response strategies to maximize their respective utility functions. We describe conditions under which offering a grace-period is advantageous to both facility provider and users by deriving the Nash equilibrium of the game.","PeriodicalId":226850,"journal":{"name":"2021 IEEE 24th International Conference on Information Fusion (FUSION)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124884288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0