Noack
Prof. Dr.-Ing. Benjamin Noack
Institute for Intelligent Cooperating Systems
Current projects
Lazy Estimation in Networked Systems
Duration: 17.04.2023 bis 16.04.2026
The amount of sensor data provided by battery-driven, widely distributed devices is steadily increasing. Since sensor data are typically fed into information processing units, it is worth considering how information processing itself can be exploited to reduce communication and energy demands. For this purpose, this project focuses on information-processing techniques that can incorporate implicit information conveyed by the transmission mechanism. Although a sensor node decides not to send its data, the receiver can still leverage the absence of data to update its state estimates. For instance, sensor readings can be compared against a threshold to decide for a transmission. The receiver can translate this decision rule into information about the data although no transmission took place. Sender and receiver can negotiate such decision rules in order to minimize communication costs, on the transmitting end, and to maximize the retrievable information, on the receiving end. Since threshold-based strategies are far too restrictive for time-varying systems being observed, model-based and data-driven policies will be investigated.
This project primarily investigates stochastic decision rules to trigger transmissions. In contrast to deterministic triggers, stochastic mechanisms can preserve the Gaussianity of the implicit information simplifying the estimator design at the receiver. For instance, a Kalman filter only requires minor adaptions to incorporate implicit information when no transmission event is triggered. The goal of this project is to push the principles of stochastic triggering forward to establish a comprehensive framework of lazy estimation. First, the investigations are concerned with general properties and the design of intelligent trigger decisions to improve the effectiveness and robustness of lazy state estimation. These include model-based and data-driven trigger mechanisms, aperiodic and asynchronous transmission and processing times, as well as the study of unreliable communication links. The results provide the foundations for large-scale lazy estimation with respect to both multisensor systems and high-dimensional state representations. For instance, multiple systems collaboratively monitor a dynamic system and fuse exchanged sensor data and estimates. Such distributed data fusion problems lead to dependent trigger decisions that require self-adapting trigger mechanisms. In particular, the project considers applications in object tracking to evaluate the derived concepts. Lazy estimation shows great potential in the processing of neuromorphic sensor data.
DatAmount - Modelling the Energy and Resource Consumption of Machine Tools Using Intelligent and Data-Efficient Methods
Duration: 01.03.2023 bis 31.08.2025
As part of the DatAmount research project, methods are being developed that make it possible to create energy models of machine tools. These models are suitable for predicting the energetic behavior of machines for new products on the basis of small amounts of data. Since small series are often produced, especially in the SME context, in many cases, there is not enough data to train AI models. Physical modeling, on the other hand, is often very costly. Due to the required CO2 proofs and the climate targets set, companies thus find themselves in a field of tension. On the one hand, accurate models to predict the energy consumption of machines are necessary to remain competitive. On the other hand, the creation of such models is currently either very expensive or not possible. The current mostly manual prediction of energy consumption is also time-consuming and also person-bound. The approach presented here combines physical models of the energy behavior of machines with data-based machine learning models, with particularly data-efficient machine learning models being investigated. This enables an automated, accurate prediction of the energy consumption of machine tools. The benefit for SMEs is the efficient creation of models that can predict the energy consumption and CO2 emissions of new products. These predictions are often necessary to be considered in a tender as proof of energy and resource efficiency is often mandatory in bids from larger companies with CO2 reduction targets.
Ready for Smart City Robots? Multimodal Maps for Autonomous Micromobiles - R4R
Duration: 01.06.2022 bis 31.05.2025
Problem Definition
Autonomously operating mobility systems or delivery services open up considerable development potential with regard to quality of life and services of general interest in non-urban areas such as in the former brown coal regions of Germany. However, assessing the potential success of micromobiles operating autonomously on footpaths and cycle paths requires comprehensive environmental information from the areas of operation, such as minimum path widths, the volume of foot traffic or sight lines. In particular, outside of large cities, this information is incomplete and heterogeneously structured.
Project Objectives
The aim of the project is to design strategies for the bicycle-based collection of environmental data that are relevant for the successful operation of autonomous micromobiles on footpaths (visibility of certain areas, infrastructure parameters, passenger volume, network coverage, environmental data). For this purpose, the project evaluates different collection methods with regard to the efficiency and quality of the aggregated information. The usability of the data will be examined in two concrete smart city/town application scenarios (rental bicycles with autonomous delivery mode and delivery robots) with corresponding studies. In this way, the project contributes to the data-driven development of smart mobility and logistics concepts that cover the specific features of different settlement areas.
2023
Book chapter
Classification of uncertainty sources for reliable Bayesian estimation
Duník, Jinřich; Straka, Ondřej; Noack, Benjamin
In: 2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI), insges. 8 S.
Book chapter
Productive teaming under uncertainty: when a human and a machine classify objects together
Rother, Anne; Notni, Gunther; Hasse, Alexander; Noack, Benjamin; Beyer, Christian; Reißmann, Jan; Zhang, Chen; Ragni, Marco; Arlinghaus, Julia C.; Spiliopoulou, Myra
In: 2023 IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO) , 2023 - [Piscataway, NJ] : IEEE, S. 9-14
Book chapter
Conservative data reduction for covariance matrices using elementwise event triggers
Funk, Christopher; Noack, Benjamin
In: FUSION 2023 / International Conference on Information Fusion , 2023 - [Piscataway, NJ] : IEEE, insges. 6 S.
Book chapter
Graduated moving Window optimization as a flexible framework for multi-object tracking
Funk, Christopher; Noack, Benjamin
In: 2023 American Control Conference (ACC) , 2023 - [Piscataway, NJ] : IEEE ; Tan, Xiaobo, S. 4864-4870
Book chapter
Statistical approach for preload monitoring of ball screw drives
Mayer, Jana; Klumpp, Vesa; Hillenbrand, Jonas; Noack, Benjamin
In: IEEE SENSORS 2023 - Piscataway, NJ, USA : IEEE, insges. 4 S.
Book chapter
Event-based colored-noise Kalman filtering for improved resource effiency
Schmitt, Eva Julia; Noack, Benjamin
In: 2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI), insges. 7 S.
Peer-reviewed journal article
Receding horizon cost-aware adaptive sampling for environmental monitoring
Westermann, Johannes; Mayer, Jana; Petereit, Janko; Noack, Benjamin
In: IEEE control systems letters - New York, NY : IEEE, Bd. 7 (2023), S. 1069-1074
Peer-reviewed journal article
Distributed range-only localization that preserves sensor and navigator privacies
Ristic, Marko; Noack, Benjamin; Hanebeck, Uwe D.
In: IEEE transactions on automatic control / Institute of Electrical and Electronics Engineers - New York, NY : Institute of Electrical and Electronics Engineers, Bd. 68 (2023), Heft 12, S. 7151-7163
Peer-reviewed journal article
Discriminative feature learning through feature distance loss
Schlagenhauf, Tobias; Lin, Yiwen; Noack, Benjamin
In: Machine vision and applications - Berlin : Springer, Bd. 34 (2023), Heft 2, Artikel 25, insges. 13 S.
2022
Book chapter
Privileged estimate fusion with correlated Gaussian keystreams
Ristic, Marko; Noack, Benjamin
In: CDC 22 / IEEE Conference on Decision and Control , 2022 - [Piscataway, NJ] : IEEE, S. 7732-7739
Book chapter
Event-based Kalman filtering exploiting correlated trigger information
Noack, Benjamin; Öhl, Clemens; Hanebeck, Uwe D.
In: Konferenz: 25th International Conference on Information Fusion, FUSION, Linköping, Sweden, 04-07 July 2022, 2022 25th International Conference on Information Fusion (FUSION)/ International Conference on Information Fusion - [Piscataway, NJ]: IEEE . - 2022, insges. 8 S.
Book chapter
Encrypted fast covariance intersection without leaking fusion weights
Ristic, Marko; Noack, Benjamin
In: International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) - [Piscataway, NJ] : IEEE . - 2022, insges. 6 S.
2021
Book chapter
Kalman filtered compressive sensing using pseudo-measurements
Zhao, Haibin; Funk, Christopher; Noack, Benjamin; Hanebeck, Uwe; Beigl, Michael
In: 2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2021) - Karlsruhe - 2021, paper 66
Peer-reviewed journal article
Cryptographically privileged state estimation with Gaussian keystreams
Ristic, Marko; Noack, Benjamin; Hanebeck, Uwe D.
In: IEEE control systems letters - New York, NY: IEEE, Bd. 6 (2021), S. 602-607
Peer-reviewed journal article
Secure Fast Covariance Intersection Using Partially Homomorphic and Order Revealing Encryption Schemes
Ristic, Marko; Noack, Benjamin; Hanebeck, Uwe D.
In: IEEE Control Systems Letters, Institute of Electrical and Electronics Engineers (IEEE), 2021, Bd. 5, Heft 1, S. 217-222
Peer-reviewed journal article
Conservative quantization of covariance matrices with applications to decentralized information fusion
Funk, Christopher; Noack, Benjamin; Hanebeck, Uwe D.
In: Sensors - Basel: MDPI, Bd. 21 (2021), 9, insges. 21 S.
Peer-reviewed journal article
Fully Decentralized Estimation Using Square-Root Decompositions
Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Journal of Advances in Information Fusion, Bd. 16, 1, S. 3-16, 2021
2020
Peer-reviewed journal article
Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking
Maier, Georg; Pfaff, Florian; Pieper, Christoph; Gruna, Robin; Noack, Benjamin; Kruggel-Emden, Harald; Längle, Thomas; Hanebeck, Uwe D.; Beyerer, Jürgen
In: In: Transactions on Industrial Electronics, 2020
Peer-reviewed journal article
Characterizing Material Flow in Sensor-Based Sorting Systems Using an Instrumented Particle
Maier, Georg; Pfaff, Florian; Bittner, Andrea; Gruna, Robin; Noack, Benjamin; Kruggel-Emden, Harald; Hanebeck, Uwe D.; Längle, Thomas; Beyerer, Jürgen
In: In: at -- Automatisierungstechnik, Bd. 4, 2020
Peer-reviewed journal article
Predictive Tracking with Improved Motion Models for Optical Belt Sorting
Pfaff, Florian; Pieper, Christoph; Maier, Georg; Noack, Benjamin; Gruna, Robin; Kruggel-Emden, Harald; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Längle, Thomas; Beyerer, Jürgen
In: In: at -- Automatisierungstechnik, Bd. 4, 2020
Article in conference proceedings
Reconstruction of Cross-Correlations between Heterogeneous Trackers Using Deterministic Samples
Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 21st IFAC World Congress (IFAC 2020), 2020
Article in conference proceedings
Improved Pose Graph Optimization for Planar Motions Using Riemannian Geometry on the Manifold of Dual Quaternions
Li, Kailai; Cox, Johannes; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 21st IFAC World Congress (IFAC 2020), 2020
Article in conference proceedings
Fully Decentralized Estimation Using Square-Root Decompositions
Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 23rd International Conference on Information Fusion (Fusion 2020), 2020
Article in conference proceedings
Conservative Quantization of Fast Covariance Intersection
Funk, Christopher; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2020), 2020
Article in conference proceedings
State Estimation with Event-Based Inputs Using Stochastic Triggers
Noack, Benjamin; Funk, Christopher; Radtke, Susanne; Hanebeck, Uwe D.
In: In: Proceedings of the 21st IFAC World Congress (IFAC 2020), 2020
2019
Peer-reviewed journal article
Gaussianity-Preserving Event-Based State Estimation with an FIR-Based Stochastic Trigger
Schmitt, Eva Julia; Noack, Benjamin; Krippner, Wolfgang; Hanebeck, Uwe D.
In: In: IEEE Control Systems Letters, Bd. 3, 3, S. 769-774, 2019, 2475-1456
Article in conference proceedings
State Estimation with Model-Mismatch-Based Secrecy against Eavesdroppers
Özgen, Selim; Kohn, Saskia; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2019 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2019), 2019
Article in conference proceedings
Nonlinear Decentralized Data Fusion with Generalized Inverse Covariance Intersection
Noack, Benjamin; Orguner, Umut; Hanebeck, Uwe D.
In: In: Proceedings of the 22nd International Conference on Information Fusion (Fusion 2019), 2019
Article in conference proceedings
Consistent Fusion in Networks Using Square-root Decompositions of Correlations
Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 22nd International Conference on Information Fusion (Fusion 2019), 2019
Article in conference proceedings
Feature-Aided Multitarget Tracking for Optical Belt Sorters
Kronauer, Tobias; Pfaff, Florian; Noack, Benjamin; Tian, Wei; Maier, Georg; Hanebeck, Uwe D.
In: In: Proceedings of the 22nd International Conference on Information Fusion (Fusion 2019), 2019
Article in conference proceedings
Distributed Estimation with Partially Overlapping States based on Deterministic Sample-based Fusion
Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2019 European Control Conference (ECC 2019), 2019
Article in conference proceedings
Geometry-Driven Deterministic Sampling for Nonlinear Bingham Filtering
Li, Kailai; Frisch, Daniel; Noack, Benjamin; Hanebeck, Uwe
In: In: Proceedings of the 2019 European Control Conference (ECC 2019), 2019
Article in conference proceedings
Comparative Study of Track-to-Track Fusion Methods for Cooperative Tracking with Bearings-only Measurements
Radtke, Susanne; Li, Kailai; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2019 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2019), 2019
2018
Book chapter
State Estimation in Networked Control Systems with Delayed and Lossy Acknowledgments
Rosenthal, Florian; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System, Springer International Publishing, S. 22-38, 2018, 978-3-319-90509-9
Peer-reviewed journal article
Optimally Distributed Kalman Filtering with Data-Driven Communication
Dormann, Katharina; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Sensors, Bd. 18, 4, 2018, 1424-8220
Peer-reviewed journal article
Numerical Modelling of an Optical Belt Sorter Using a DEMCFD Approach Coupled with Particle Tracking and Comparison with Experiments
Pieper, Christoph; Pfaff, Florian; Maier, Georg; Kruggel-Emden, Harald; Wirtz, Siegmar; Noack, Benjamin; Gruna, Robin; Scherer, Viktor; Hanebeck, Uwe D.; Längle, Thomas; Beyerer, Jürgen
In: In: Powder Technology, Bd. 370, S. 181-193, 2018
Peer-reviewed journal article
On Directional Splitting of Gaussian Density in Nonlinear Random Variable Transformation
Duník, Jindich; Straka, Ondej; Noack, Benjamin; Steinbring, Jannik; Hanebeck, Uwe D.
In: In: IET Signal Processing, 2018, 1751-9683
Article in conference proceedings
Scheduling of Measurement Transmission in Networked Control Systems Subject to Communication Constraints
Rosenthal, Florian; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2018 American Control Conference (ACC 2018), 2018
Article in conference proceedings
Wavefront Orientation Estimation Based on Progressive Bingham Filtering
Li, Kailai; Frisch, Daniel; Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the IEEE ISIF Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF 2018), 2018
Article in conference proceedings
Reconstruction of Cross-Correlations with Constant Number of Deterministic Samples
Radtke, Susanne; Noack, Benjamin; Hanebeck, Uwe D.; Straka, Ondej
In: In: Proceedings of the 21st International Conference on Information Fusion (Fusion 2018), 2018
Article in conference proceedings
Retrodiction of Data Association Probabilities via Convex Optimization
Özgen, Selim; Hanebeck, Uwe D.; Noack, Benjamin; Huber, Marco; Rosenthal, Florian; Mayer, Jana
In: In: Proceedings of the 21st International Conference on Information Fusion (Fusion 2018), 2018
Article in conference proceedings
Encrypted Multisensor Information Filtering
Aristov, Mikhail; Noack, Benjamin; Hanebeck, Uwe D.; Müller-Quade, Jörn
In: In: Proceedings of the 21st International Conference on Information Fusion (Fusion 2018), 2018
2017
Peer-reviewed journal article
Motion-Based Material Characterization in Sensor-Based Sorting
Maier, Georg; Pfaff, Florian; Becker, Florian; Pieper, Christoph; Gruna, Robin; Noack, Benjamin; Kruggel-Emden, Harald; Längle, Thomas; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Beyerer, Jürgen
In: In: tm - Technisches Messen, De Gruyter, 2017
Peer-reviewed journal article
Decentralized Data Fusion with Inverse Covariance Intersection
Noack, Benjamin; Sijs, Joris; Reinhardt, Marc; Hanebeck, Uwe D.
In: In: Automatica, Bd. 79, S. 35-41, 2017
Peer-reviewed journal article
Real-Time Motion Prediction Using the Chromatic Offset of Line Scan Cameras
Pfaff, Florian; Maier, Georg; Aristov, Mikhail; Noack, Benjamin; Gruna, Robin; Hanebeck, Uwe D.; Längle, Thomas; Beyerer, Jürgen; Pieper, Christoph; Kruggel-Emden, Harald; Wirtz, Siegmar; Scherer, Viktor
In: In: at - Automatisierungstechnik, De Gruyter, 2017
Peer-reviewed journal article
Real-Time Multitarget Tracking for Sensor-Based Sorting
Maier, Georg; Pfaff, Florian; Wagner, Matthias; Pieper, Christoph; Gruna, Robin; Noack, Benjamin; Kruggel-Emden, Harald; Längle, Thomas; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Beyerer, Jürgen
In: In: Journal of Real-Time Image Processing, 2017
Article in conference proceedings
Distributed Kalman Filtering With Reduced Transmission Rate
Dormann, Katharina; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), 2017
Article in conference proceedings
Event-Based Estimation in a Feedback Loop Anticipating on Imperfect Communication
Sijs, Joris; Noack, Benjamin
In: In: Proceedings of the 20th IFAC World Congress (IFAC 2017), 2017
Article in conference proceedings
Optimal Distributed Combined Stochastic and Set-Membership State Estimation
Pfaff, Florian; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 20th International Conference on Information Fusion (Fusion 2017), 2017
Article in conference proceedings
Improving Multitarget Tracking Using Orientation Estimates for Sorting Bulk Materials
Pfaff, Florian; Kurz, Gerhard; Pieper, Christoph; Maier, Georg; Noack, Benjamin; Kruggel-Emden, Harald; Gruna, Robin; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Längle, Thomas; Beyerer, Jürgen
In: In: Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), 2017
Article in conference proceedings
State Estimation in Networked Control Systems With Delayed And Lossy Acknowledgments
Rosenthal, Florian; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), 2017
Article in conference proceedings
Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information
Maier, Georg; Pfaff, Florian; Becker, Florian; Pieper, Christoph; Gruna, Robin; Noack, Benjamin; Kruggel-Emden, Harald; Längle, Thomas; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Beyerer, Jürgen
In: In: Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), 2017
Article in conference proceedings
Numerical Modelling of the Separation of Complex Shaped Particles in an Optical Belt Sorter Using a DEM--CFD Approach and Comparison with Experiments
Pieper, Christoph; Maier, Georg; Pfaff, Florian; Kruggel-Emden, Harald; Gruna, Robin; Noack, Benjamin; Wirtz, Siegmar; Scherer, Viktor; Längle, Thomas; Hanebeck, Uwe D.; Beyerer, Jürgen
In: In: V International Conference on Particle-based Methods. Fundamentals and Applications (PARTICLES 2017), 2017
Article in conference proceedings
Inverse Covariance Intersection: New Insights and Properties
Noack, Benjamin; Sijs, Joris; Hanebeck, Uwe D.
In: In: Proceedings of the 20th International Conference on Information Fusion (Fusion 2017), 2017
Article in conference proceedings
Information Form Distributed Kalman Filtering (IDKF) with Explicit Inputs
Pfaff, Florian; Noack, Benjamin; Hanebeck, Uwe D.; Govaers, Felix; Koch, Wolfgang
In: In: Proceedings of the 20th International Conference on Information Fusion (Fusion 2017), 2017
2016
Peer-reviewed journal article
Numerical Modeling of an Automated Optical Belt Sorter using the Discrete Element Method
Pieper, Christoph; Maier, Georg; Pfaff, Florian; Kruggel-Emden, Harald; Wirtz, Siegmar; Gruna, Robin; Noack, Benjamin; Scherer, Viktor; Längle, Thomas; Beyerer, Jürgen; Hanebeck, Uwe D.
In: In: Powder Technology, 2016
Peer-reviewed journal article
Improving Optical Sorting of Bulk Materials Using Sophisticated Motion Models
Pfaff, Florian; Pieper, Christoph; Maier, Georg; Noack, Benjamin; Kruggel-Emden, Harald; Gruna, Robin; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Längle, Thomas; Beyerer, Jürgen
In: In: tm - Technisches Messen, De Gruyter, Bd. 83, 2, S. 77-84, 2016
Article in conference proceedings
Numerical Investigation of Optical Sorting using the Discrete Element Method
Pieper, Christoph; Kruggel-Emden, Harald; Wirtz, Siegmar; Scherer, Viktor; Pfaff, Florian; Noack, Benjamin; Hanebeck, Uwe D.; Maier, Georg; Gruna, Robin; Längle, Thomas; Beyerer, Jürgen
In: In: Proceedings of the 7th International Conference on Discrete Element Methods (DEM7), 2016
Article in conference proceedings
Fast Multitarget Tracking via Strategy Switching for Sensor-Based Sorting
Maier, Georg; Pfaff, Florian; Pieper, Christoph; Gruna, Robin; Noack, Benjamin; Kruggel-Emden, Harald; Längle, Thomas; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Beyerer, Jürgen
In: In: Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), 2016
Article in conference proceedings
State Estimation Considering Negative Information with Switching Kalman and Ellipsoidal Filtering
Noack, Benjamin; Pfaff, Florian; Baum, Marcus; Hanebeck, Uwe D.
In: In: Proceedings of the 19th International Conference on Information Fusion (Fusion 2016), 2016
Article in conference proceedings
Algebraic Analysis of Data Fusion with Ellipsoidal Intersection
Noack, Benjamin; Sijs, Joris; Hanebeck, Uwe D.
In: In: Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), 2016
Article in conference proceedings
Simulation-based Evaluation of Predictive Tracking for Sorting Bulk Materials
Pfaff, Florian; Pieper, Christoph; Maier, Georg; Noack, Benjamin; Kruggel-Emden, Harald; Gruna, Robin; Hanebeck, Uwe D.; Wirtz, Siegmar; Scherer, Viktor; Längle, Thomas; Beyerer, Jürgen
In: In: Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), 2016
Article in conference proceedings
Optimal Sample-Based Fusion for Distributed State Estimation
Steinbring, Jannik; Noack, Benjamin; Reinhardt, Marc; Hanebeck, Uwe D.
In: In: Proceedings of the 19th International Conference on Information Fusion (Fusion 2016), 2016
Article in conference proceedings
Camera- and IMU-based Pose Tracking for Augmented Reality
Faion, Florian; Zea, Antonio; Noack, Benjamin; Steinbring, Jannik; Hanebeck, Uwe D.
In: In: Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), 2016
2015
Book chapter
Treatment of Dependent Information in Multisensor Kalman Filtering and Data Fusion
Noack, Benjamin; Sijs, Joris; Reinhardt, Marc; Hanebeck, Uwe D.
In: In: Multisensor Data Fusion: From Algorithms and Architectural Design to Applications, CRC Press, S. 169-192, 2015
Book chapter
Time-Periodic State Estimation with Event-Based Measurement Updates
Sijs, Joris; Noack, Benjamin; Lazar, Mircea; Hanebeck, Uwe D.
In: In: Event-Based Control and Signal Processing, CRC Press, S. 261-279, 2015
Peer-reviewed journal article
Minimum Covariance Bounds for the Fusion under Unknown Correlations
Reinhardt, Marc; Noack, Benjamin; Arambel, Pablo O.; Hanebeck, Uwe D.
In: In: IEEE Signal Processing Letters, Bd. 22, 9, S. 1210 - 1214, 2015
Article in conference proceedings
TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials
Pfaff, Florian; Baum, Marcus; Noack, Benjamin; Hanebeck, Uwe D.; Gruna, Robin; Längle, Thomas; Beyerer, Jürgen
In: In: Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Information Integration (MFI 2015), 2015
Article in conference proceedings
Kalman Filter-based SLAM with Unknown Data Association using Symmetric Measurement Equations
Baum, Marcus; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), 2015
Article in conference proceedings
Treatment of Biased and Dependent Sensor Data in Graph-based SLAM
Noack, Benjamin; Julier, Simon J.; Hanebeck, Uwe D.
In: In: Proceedings of the 18th International Conference on Information Fusion (Fusion 2015), 2015
Article in conference proceedings
State Estimation for Ellipsoidally Constrained Dynamic Systems with Set-membership Pseudo Measurements
Noack, Benjamin; Baum, Marcus; Hanebeck, Uwe D.
In: In: Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), 2015
2014
Article in conference proceedings
On Nonlinear Track-to-track Fusion with Gaussian Mixtures
Noack, Benjamin; Reinhardt, Marc; Hanebeck, Uwe D.
In: In: Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), 2014
Article in conference proceedings
Covariance Intersection in State Estimation of Dynamical Systems
Ajgl, Jií; imandl, Miroslav; Reinhardt, Marc; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), 2014
Article in conference proceedings
Reconstruction of Joint Covariance Matrices in Networked Linear Systems
Reinhardt, Marc; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 48th Annual Conference on Information Sciences and Systems (CISS 2014), 2014
Article in conference proceedings
Distributed Kalman Filtering in the Presence of Packet Delays and Losses
Reinhardt, Marc; Noack, Benjamin; Kulkarni, Sanjeev; Hanebeck, Uwe D.
In: In: Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), 2014
Article in conference proceedings
A Study on Event Triggering Criteria for Estimation
Sijs, Joris; Kester, Leon; Noack, Benjamin
In: In: Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), 2014
Article in conference proceedings
Fusion Strategies for Unequal State Vectors in Distributed Kalman Filtering
Noack, Benjamin; Sijs, Joris; Hanebeck, Uwe D.
In: In: Proceedings of the 19th IFAC World Congress (IFAC 2014), 2014
2013
Dissertation
State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties
Noack, Benjamin
In: 2013
Article in conference proceedings
Data Validation in the Presence of Stochastic and Set-membership Uncertainties
Pfaff, Florian; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), 2013
Article in conference proceedings
An Empirical Method to Fuse Partially Overlapping State Vectors for Distributed State Estimation
Sijs, Joris; Hanebeck, Uwe D.; Noack, Benjamin
In: In: Proceedings of the 2013 European Control Conference (ECC 2013), 2013
Article in conference proceedings
Advances in Hypothesizing Distributed Kalman Filtering
Reinhardt, Marc; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), 2013
Article in conference proceedings
Nonlinear Federated Filtering
Noack, Benjamin; Julier, Simon J.; Reinhardt, Marc; Hanebeck, Uwe D.
In: In: Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), 2013
Article in conference proceedings
Event-based State Estimation with Negative Information
Sijs, Joris; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), 2013
2012
Article in conference proceedings
Closed-form Optimization of Covariance Intersection for Low-dimensional Matrices
Reinhardt, Marc; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), 2012
Article in conference proceedings
Decentralized Control Based on Globally Optimal Estimation
Reinhardt, Marc; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 2012
Article in conference proceedings
On Optimal Distributed Kalman Filtering in Non-ideal Situations
Reinhardt, Marc; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), 2012
Article in conference proceedings
The Hypothesizing Distributed Kalman Filter
Reinhardt, Marc; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2012), 2012
Article in conference proceedings
Pushing Kalman's Idea to the Extremes
Benavoli, Alessio; Noack, Benjamin
In: In: Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), 2012
Article in conference proceedings
Combined Stochastic and Set-membership Information Filtering in Multisensor Systems
Noack, Benjamin; Pfaff, Florian; Hanebeck, Uwe D.
In: In: Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), 2012
Article in conference proceedings
Optimal Kalman Gains for Combined Stochastic and Set-Membership State Estimation
Noack, Benjamin; Pfaff, Florian; Hanebeck, Uwe D.
In: In: Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 2012
2011
Article in conference proceedings
Random Hypersurface Mixture Models for Tracking Multiple Extended Objects
Baum, Marcus; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 50th IEEE Conference on Decision and Control (CDC 2011), 2011
Article in conference proceedings
Nonlinear Information Filtering for Distributed Multisensor Data Fusion
Noack, Benjamin; Lyons, Daniel; Nagel, Matthias; Hanebeck, Uwe D.
In: In: Proceedings of the 2011 American Control Conference (ACC 2011), 2011
Article in conference proceedings
Optimal Gaussian Filtering for Polynomial Systems Applied to Association-free Multi-Target Tracking
Baum, Marcus; Noack, Benjamin; Beutler, Frederik; Itte, Dominik; Hanebeck, Uwe D.
In: In: Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), 2011
Article in conference proceedings
An Experimental Evaluation of Position Estimation Methods for Person Localization in Wireless Sensor Networks
Schmid, Johannes; Beutler, Frederik; Noack, Benjamin; Hanebeck, Uwe D.; Müller-Glaser, Klaus D.
In: In: Proceedings of the 8th European Conference on Wireless Sensor Networks (EWSN 2011), Springer, Bd. 6567, S. 147-162, 2011
Article in conference proceedings
Analysis of Set-theoretic and Stochastic Models for Fusion under Unknown Correlations
Reinhardt, Marc; Noack, Benjamin; Baum, Marcus; Hanebeck, Uwe D.
In: In: Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), 2011
Article in conference proceedings
Automatic Exploitation of Independencies for Covariance Bounding in Fully Decentralized Estimation
Noack, Benjamin; Baum, Marcus; Hanebeck, Uwe D.
In: In: Proceedings of the 18th IFAC World Congress (IFAC 2011), 2011
Article in conference proceedings
Covariance Intersection in Nonlinear Estimation Based on Pseudo Gaussian Densities
Noack, Benjamin; Baum, Marcus; Hanebeck, Uwe D.
In: In: Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), 2011
2010
Book chapter
Maße für Wahrscheinlichkeitsdichten in der informationstheoretischen Sensoreinsatzplanung
Lyons, Daniel; Hekler, Achim; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Verteilte Messsysteme, KIT Scientific Publishing, S. 121-132, 2010
Book chapter
Systematische Beschreibung von Unsicherheiten in der Informationsfusion mit Mengen von Wahrscheinlichkeitsdichten
Noack, Benjamin; Klumpp, Vesa; Lyons, Daniel; Hanebeck, Uwe D.
In: In: Verteilte Messsysteme, KIT Scientific Publishing, S. 167-178, 2010
Peer-reviewed journal article
Modellierung von Unsicherheiten und Zustandsschätzung mit Mengen von Wahrscheinlichkeitsdichten
Noack, Benjamin; Klumpp, Vesa; Lyons, Daniel; Hanebeck, Uwe D.
In: In: tm - Technisches Messen, Oldenbourg Verlag, Bd. 77, 10, S. 544-550, 2010
Article in conference proceedings
Reliable Estimation of Heart Surface Motion under Stochastic and Unknown but Bounded Systematic Uncertainties
Bogatyrenko, Evgeniya; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), 2010
Article in conference proceedings
A Log-Ratio Information Measure for Stochastic Sensor Management
Lyons, Daniel; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC 2010), 2010
Article in conference proceedings
Bounding Linearization Errors with Sets of Densities in Approximate Kalman Filtering
Noack, Benjamin; Klumpp, Vesa; Petkov, Nikolay; Hanebeck, Uwe D.
In: In: Proceedings of the 13th International Conference on Information Fusion (Fusion 2010), 2010
Article in conference proceedings
Nonlinear Model Predictive Control Considering Stochastic and Systematic Uncertainties with Sets of Densities
Hekler, Achim; Lyons, Daniel; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the IEEE Multi-Conference on Systems and Control (MSC 2010), 2010
Article in conference proceedings
Combined Set-Theoretic and Stochastic Estimation: A Comparison of the SSI and the CS Filter
Klumpp, Vesa; Noack, Benjamin; Baum, Marcus; Hanebeck, Uwe D.
In: In: Proceedings of the 13th International Conference on Information Fusion (Fusion 2010), 2010
Article in conference proceedings
Extended Object and Group Tracking with Elliptic Random Hypersurface Models
Baum, Marcus; Noack, Benjamin; Hanebeck, Uwe D.
In: In: Proceedings of the 13th International Conference on Information Fusion (Fusion 2010), 2010
2009
Article in conference proceedings
State Estimation with Sets of Densities considering Stochastic and Systematic Errors
Noack, Benjamin; Klumpp, Vesa; Hanebeck, Uwe D.
In: In: Proceedings of the 12th International Conference on Information Fusion (Fusion 2009), 2009
2008
Article in conference proceedings
Nonlinear Bayesian Estimation with Convex Sets of Probability Densities
Noack, Benjamin; Klumpp, Vesa; Brunn, Dietrich; Hanebeck, Uwe D.
In: In: Proceedings of the 11th International Conference on Information Fusion (Fusion 2008), S. 1-8, 2008
Multisensor data fusion is the process of combining data streams from multiple – possibly heterogeneous and complementary – sensors. As a result, systems like autonomous mobile robots benefit from increased data quality and reliability, can estimate unmeasured states, and can cover larger areas with their sensors. Our research includes
- Kalman filtering and nonlinear estimation
- Modeling and uncertainty quantification
- Algorithms for localization, tracking, and situational awareness
- Decentralized data fusion in mobile systems and ad-hoc sensor networks
Resource-Efficient Sensor Data Processing
Mobile sensor systems typically have resource constraints in processing capabilities, battery power, and storage space. Also, communication bandwidth is a limiting factor when multiple systems need to exchange sensor data. Multisensor data fusion can address these limitations by different measures. Our research includes
- Reduced-complexity fusion algorithms
- Adaptive sampling rates and asynchronous processing
- Event-based sensor fusion and estimation
- Quantization of sensor data and estimates
Localization with Mutual Dependencies
Precise localization and tracking of vehicles such as drones or cars is essential for their safe autonomous operation, particularly when they operate in constrained shared spaces and must therefore interact with one another. Decentralized methods for combining information distributed across several vehicles and exploiting mutual dependencies are beneficial in such scenarios. Our research includes
- Optimization-based state estimation
- Utilization of mutual dependencies
- Decentralized optimization algorithms
- Spatially distributed measurements
Privacy-Preserving Data Fusion
With the advancements in distributed algorithms and cloud computing, the reliance on public communication channels and untrusted participants has stressed the requirement for data privacy. Privacy-preserving data fusion presents methods for increasing participants' data quality in distributed environments while keeping their sensitive data private. This includes private state estimates, exact measurements and fixed locations. Our research includes
- Privacy-preserving distributed localization
- Homomorphic and functional encrypted cloud data fusion
- Cryptographic privileges in estimation
- Quantifiable data fusion leakage
- CyFace GmbH, Dresden
- DigiPL GmbH, Halle (Saale)
- Endiio Engineering GmbH, Freiburg
- Gesellschaft zur Förderung angewandter Informatik e.V. (GFaI)
- Hochschule Anhalt, Köthen
- Hochschule Merseburg
- Landkreis Nordsachsen
- PTV AG, Karlsruhe
- Technische Universität Bergakademie, Freiberg
- TINK GmbH, Konstanz
- wbk Institut für Produktionstechnik, Karlsruher Institut für Technology (KIT)
Teaching
- Advanced Estimation Methods for Autonomous Robotic Systems ( Link zur LV im LSF )
- AMS Lab Projects ( Link zur LV im LSF )
- Introduction to Distributed Sensor Data Fusion ( Link zur LV im LSF )
- Introduction to Distributed Sensor Data Fusion ( Link zur LV im LSF )
- Navigation and Localization of Hamster Robot ( Link zur LV im LSF )
- Navigation in der Flugrobotik ( Link zur LV im LSF )
- Predictive Maintenance Seminar ( Link zur LV im LSF )
- Project Shape Tracking with Event Cameras ( Link zur LV im LSF )
- Project: UMD Racing Driverless ( Link zur LV im LSF )