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Reinforcement learning techniques have successfully been applied to solve challenging problems. Among the more famous examples are playing games such as Go and real-time computer games such as StarCraft II. In addition, reinforcement learning has successfully been deployed in cyber-physical systems such as robots playing a curling-based game. These are all important and significant achievements indicating that the techniques can be of value for the aerospace industry. However, to use these techniques in the aerospace industry, very high requirements on verification and validation must be met. In this position paper, we outline four key problems for verification and validation of reinforcement learning techniques. Solving these are an important step towards enabling reinforcement learning techniques to be used in safety critical domains such as the aerospace industry., WASP

The new generation laser-based FLASH 3D imaging sensors enable data collection at video rate. This opens up for realtime data analysis but also set demands on the signal processing. In this paper the possibilities and challenges with this new data type are discussed. The commonly used focal plane array based detectors produce range estimates that vary with the target's surface reflectance and target range, and our experience is that the built-in signal processing may not compensate fully for that. We propose a simple adjustment that can be used even if some sensor parameters are not known. The cost for the instantaneous image collection is, compared to scanning laser radar systems, lower range accuracy. By gathering range information from several frames the geometrical information of the target can be obtained. We also present an approach of how range data can be used to remove foreground clutter in front of a target. Further, we illustrate how range data enables target classification in near real-time and that the results can be improved if several frames are co-registered. Examples using data from forest and maritime scenes are shown.

Identification of nonlinear systems is a problem with many facets and roots in several diverse fields. It is not possible to survey the area in a short text. The current presentation gives a subjective view on some essential features in the area. These concern a classification of methods, the use of physical insight in models, and some overall issues like bias-variance trade-off. It is also discussed how the methods can be made available in software packages.

Point-to-point MIMO and massive MIMO techniques have played significantroles in the success of 4G and 5G radio networks, and in 6G we believethat distributed MIMO will play a similar critical role. The performanceof downlink phase coherent distributed MIMO transmission relies on tightphase alignment between the serving access points (APs) in the system.In realistic scenarios, there will always be some level of phasemisalignment between APs due to e.g., differences in the local clocksof the APs, which can severely degrade the performance. One main contribution of this paper is that we propose the use of aLinear Quadratic Regulator (LQR) based solution for calculating downlinkprecoding weights in D-MIMO systems. The optimal LQR based precodingsolution is numerically stable and computationally efficient, and it caneasily utilise parallel computing in distributed or centralised hardwareprocessors. Furthermore, we also show how the LQR based solution can bemodified to include differently sized subsets of serving APs for each UE,which enables a scalable tradeoff between performance and complexity. Another main contribution of the paper is that we identify a new phasemisalignment problem in D-MIMO. The proposed LQR-based precoding methodis the first solution that takes not only the channel estimation phaseerrors, but also the relative phase errors between serving APs intoaccount when designing the downlink D-MIMO transmission precoder. By this,some of the performance lost due to different causes of phase misalignmentcan be regained. In the scenarios studied in this paper we observe 20-70%performance increase of the proposed method compared to a reference casewhere residual phase errors are ignored when determining the downlinkprecoding weights., REINDEER project of the European Union's Horizon 2020 research and innovation programme under gran agreement no. 101013425

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small.

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper considers fusion of dimension-reduced estimates in a decentralized sensor network. The benefits of a decentralized sensor network include modularity, robustness and flexibility. Moreover, since preprocessed data is exchanged between the agents it allows for reduced communication. Nevertheless, in certain applications the communication load is required to be reduced even further. One way to decrease the communication load is to exchange dimension-reduced estimates instead of full estimates. Previous work on this topic assumes global availability of covariance matrices, an assumption which is not realistic in decentralized applications. Hence, in this paper we consider the problem of deriving dimension-reduced estimates using only local information. The proposed solution is based on an estimate of the information common to the network. This common information estimate is computed locally at each agent by fusion of all information that is either received or transmitted by that agent. It is shown how the common information estimate is utilized for fusion of dimension-reduced estimates using two well-known fusion methods: the Kalman fuser which is optimal under the assumption of uncorrelated estimates, and covariance intersection. One main theoretical result is that the common information estimate allows for a decorrelation procedure such that uncorrelated estimates can be maintained. This property is crucial to be able to use the Kalman fuser without double counting of information. A numerical comparison suggests that the performance degradation of using the common information estimate, compared to having local access to the actual covariance matrices computed by other agents, is relatively small., Funding: Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab AB

This paper presents a method to certify the computational complexity of a standard Branch and Bound method for solving Mixed-Integer Quadratic Programming (MIQP) problems defined as instances of a multi-parametric MIQP. Beyond previous work, not only the size of the binary search tree is considered, but also the exact complexity of solving the relaxations in the nodes by using recent results from exact complexity certification of active-set QP methods. With the algorithm proposed in this paper, a total worst-case number of QP iterations to be performed in order to solve the MIQP problem can be determined as a function of the parameter in the problem. An important application of the proposed method is Model Predictive Control for hybrid systems, that can be formulated as an MIQP that has to be solved in real-time. The usefulness of the proposed method is successfully illustrated in numerical examples., Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

This paper presents a method to certify the computational complexity of a standard Branch and Bound method for solving Mixed-Integer Quadratic Programming (MIQP) problems defined as instances of a multi-parametric MIQP. Beyond previous work, not only the size of the binary search tree is considered, but also the exact complexity of solving the relaxations in the nodes by using recent results from exact complexity certification of active-set QP methods. With the algorithm proposed in this paper, a total worst-case number of QP iterations to be performed in order to solve the MIQP problem can be determined as a function of the parameter in the problem. An important application of the proposed method is Model Predictive Control for hybrid systems, that can be formulated as an MIQP that has to be solved in real-time. The usefulness of the proposed method is successfully illustrated in numerical examples., Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

This paper presents a method to certify the computational complexity of a standard Branch and Bound method for solving Mixed-Integer Quadratic Programming (MIQP) problems defined as instances of a multi-parametric MIQP. Beyond previous work, not only the size of the binary search tree is considered, but also the exact complexity of solving the relaxations in the nodes by using recent results from exact complexity certification of active-set QP methods. With the algorithm proposed in this paper, a total worst-case number of QP iterations to be performed in order to solve the MIQP problem can be determined as a function of the parameter in the problem. An important application of the proposed method is Model Predictive Control for hybrid systems, that can be formulated as an MIQP that has to be solved in real-time. The usefulness of the proposed method is successfully illustrated in numerical examples., Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

This paper presents a method to certify the computational complexity of a standard Branch and Bound method for solving Mixed-Integer Quadratic Programming (MIQP) problems defined as instances of a multi-parametric MIQP. Beyond previous work, not only the size of the binary search tree is considered, but also the exact complexity of solving the relaxations in the nodes by using recent results from exact complexity certification of active-set QP methods. With the algorithm proposed in this paper, a total worst-case number of QP iterations to be performed in order to solve the MIQP problem can be determined as a function of the parameter in the problem. An important application of the proposed method is Model Predictive Control for hybrid systems, that can be formulated as an MIQP that has to be solved in real-time. The usefulness of the proposed method is successfully illustrated in numerical examples., Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

A case study of the use of reflections within the Applied physics and electrical engineering program at Linköping University is presented. Reflections have been used for several years and they are done at four stages in the program, in terms of reflections at the end of the Introductory course in year one, design-implement experiences in year three and five, and a reflection document that is the last component of the Master’s thesis. In the first three stages a project model is used to support the planning and execution of the project, and in the project model the project work ends with a reflection. In the reflection document connected to the Master’s thesis the student reflects upon both the thesis work itself and the entire education program, according to the sections and subsections of the CDIO Syllabus. The paper describes how the reflections are integrated in the program. Experiences from student perspective are collected in a small-scale study via interviews with students from year one and year five.

A case study of the use of reflections within the Applied physics and electrical engineering program at Linköping University is presented. Reflections have been used for several years and they are done at four stages in the program, in terms of reflections at the end of the Introductory course in year one, design-implement experiences in year three and five, and a reflection document that is the last component of the Master’s thesis. In the first three stages a project model is used to support the planning and execution of the project, and in the project model the project work ends with a reflection. In the reflection document connected to the Master’s thesis the student reflects upon both the thesis work itself and the entire education program, according to the sections and subsections of the CDIO Syllabus. The paper describes how the reflections are integrated in the program. Experiences from student perspective are collected in a small-scale study via interviews with students from year one and year five.

Underwater surveillance using passive sonar and track-before-detect technology requires accurate models of the tracked signal and the background noise. However, in an underwater environment, the signal channel is time-varying and prior knowledge about the spatial distribution of the background noise is unavailable. In this paper, an autoregressive model that captures a time-varying signal level caused by multi-path propagation is presented. In addition, a multi-source model is proposed to describe spatially distributed background noise. The models are used in a Bernoulli filter track-before-detect framework and evaluated using both simulated and sea trial data. The simulations demonstrate clear improvements in terms of target loss and improved ability to discern the target from the noisy background. An evaluation of the track-before-detect algorithm on the sea trial data indicates a performance gain when incorporating the proposed models in underwater surveillance and tracking problems.

A case study of the use of reflections within the Applied physics and electrical engineering program at Linköping University is presented. Reflections have been used for several years and they are done at four stages in the program, in terms of reflections at the end of the Introductory course in year one, design-implement experiences in year three and five, and a reflection document that is the last component of the Master’s thesis. In the first three stages a project model is used to support the planning and execution of the project, and in the project model the project work ends with a reflection. In the reflection document connected to the Master’s thesis the student reflects upon both the thesis work itself and the entire education program, according to the sections and subsections of the CDIO Syllabus. The paper describes how the reflections are integrated in the program. Experiences from student perspective are collected in a small-scale study via interviews with students from year one and year five.

A deep neural classifier trained on an upstream task can be leveraged to boost the performance of another classifier in a related downstream task through the representations learned in hidden layers. However, presence of shortcuts (easy-to-learn features) in the upstream task can considerably impair the versatility of intermediate representations and, in turn, the downstream performance. In this paper, we propose a method to improve the representations learned by deep neural image classifiers in spite of a shortcut in upstream data. In our method, the upstream classification objective is augmented with a type of adversarial training where an auxiliary network, so called lens, fools the classifier by exploiting the shortcut in reconstructing images. Empirical comparisons in self-supervised and transfer learning problems with three shortcut-biased datasets suggest the advantages of our method in terms of downstream performance and/or training time.

In this paper, we present a study on using weightedtotal least squares method for parameter estimation of errorsin-variables models with quadratic regressors. The statistics oferror is analyzed to fill in the gap between basic assumptions inweighted total least squares and our case. A modified Cram´er-Rao lower bound is introduced for error quantification in theproposed method. We perform evaluations based on simulationswith comparisons to standard least squares and generalized totalleast squares. Numerical results show that the proposed methodoutperforms the others in terms of estimation accuracy

This paper proposes the modeling and analysis of multi-energy systems as multilayer networks. The aim is to assess the interdependence between different energy infrastructures. Multilayer network modeling enhances the one-dimensional graph-based approach employed to study the vulnerability and the topological characteristics of power grids. The centrality indices defined for one-dimensional networks are extended to multilayer networks, highlighting the differences emerging when interdependence is considered. The proposed multilayer framework is demonstrated on the 24-bus IEEE power grid coupled with a gas network with 7 nodes.

Hegselmann-Krause (HK) models exhibit complex behaviors which are not easily tractable through mathematical analysis. In this paper, a characterization of the steady-state behaviors of homogeneous HK models and sensitivity to confidence thresholds is discussed by commenting on existing and new numerical results. The typical decreasing of number of clusters and convergence time by increasing the confidence thresholds are discussed and motivations for the behavior of some counterexamples are provided. A tighter upper bound for the dependence of the number of clusters with respect to the confidence thresholds is proposed. Differences and analogies between the opinions evolution for symmetric and asymmetric HK models are commented.

Recent studies of selective auditory attention have demonstrated that neural responses recorded with electroencephalogram (EEG) can be decoded to classify the attended talker in everyday multitalker cocktail-party environments. This is generally referred to as the auditory attention decoding (AAD) and could lead to a breakthrough for the next-generation of hearing aids (HAs) to have the ability to be cognitively controlled. The aim of this paper is to investigate whether cepstral analysis can be used as a more robust mapping between speech and EEG. Our preliminary analysis revealed an average AAD accuracy of 96%. Moreover, we observed a significant increase in auditory attention classification accuracies with our approach over the use of traditional AAD methods (7% absolute increase). Overall, our exploratory study could open a new avenue for developing new AAD methods to further advance hearing technology. We recognize that additional research is needed to elucidate the full potential of cepstral analysis for AAD.

This paper deals with distributed Bayesian stateestimation of generally nonlinear stochastic dynamic systems. In particular, distributed point-mass filter algorithm is developed. It is comprised of a basic part that is accurate but data intense and optional step employing advanced copula theory. The optional step significantly reduces data transfer for the price of a small accuracy decrease. In the end, the developed algorithm is numerically compared to the usually employed distributed extended Kalman filter., Funding: project Improving the Quality of Internal Grant Schemes at the UWB [CZ.02.2.69/0.0/0.0/19 073/0016931, SGS-2022-022]; Industry Excellence Center LINK-SIC - VINNOVA; Saab AB

Underwater surveillance using passive sonar and track-before-detect technology requires accurate models of the tracked signal and the background noise. However, in an underwater environment, the signal channel is time-varying and prior knowledge about the spatial distribution of the background noise is unavailable. In this paper, an autoregressive model that captures a time-varying signal level caused by multi-path propagation is presented. In addition, a multi-source model is proposed to describe spatially distributed background noise. The models are used in a Bernoulli filter track-before-detect framework and evaluated using both simulated and sea trial data. The simulations demonstrate clear improvements in terms of target loss and improved ability to discern the target from the noisy background. An evaluation of the track-before-detect algorithm on the sea trial data indicates a performance gain when incorporating the proposed models in underwater surveillance and tracking problems., Zenith

An autonomous underwater vehicle (AUV) is a crewless robotic vehicle that dives into the water and performs without human assistance. This paper focuses on developing trajectory tracking control for bio-mimetic AUV system under uncertain environments. Therefore, a relatively new control technique called time delay-based estimation control is proposed for trajectory tracking under multiple uncertainties. This algorithm estimates the total disturbance in the system using immediate past information of input and output of feedback state and control variables. The benefit of this scheme is that it avoids assumptions about a priori upper bound information of disturbance. Further, the control structure is simple and does not require any high-frequency switching or high gain to nullify the effects of disturbance. The theoretical analysis of the proposed scheme guarantees the uniformly ultimate bounded stability of the closed-loop system. The numerical analysis is also carried out to validate the control performance of the given algorithm for lemniscate reference path tracking.

A case study of the use of reflections within the Applied physics and electrical engineering program at Linköping University is presented. Reflections have been used for several years and they are done at four stages in the program, in terms of reflections at the end of the Introductory course in year one, design-implement experiences in year three and five, and a reflection document that is the last component of the Master’s thesis. In the first three stages a project model is used to support the planning and execution of the project, and in the project model the project work ends with a reflection. In the reflection document connected to the Master’s thesis the student reflects upon both the thesis work itself and the entire education program, according to the sections and subsections of the CDIO Syllabus. The paper describes how the reflections are integrated in the program. Experiences from student perspective are collected in a small-scale study via interviews with students from year one and year five.

This paper deals with distributed Bayesian stateestimation of generally nonlinear stochastic dynamic systems. In particular, distributed point-mass filter algorithm is developed. It is comprised of a basic part that is accurate but data intense and optional step employing advanced copula theory. The optional step significantly reduces data transfer for the price of a small accuracy decrease. In the end, the developed algorithm is numerically compared to the usually employed distributed extended Kalman filter., Funding: project Improving the Quality of Internal Grant Schemes at the UWB [CZ.02.2.69/0.0/0.0/19 073/0016931, SGS-2022-022]; Industry Excellence Center LINK-SIC - VINNOVA; Saab AB

This paper deals with distributed Bayesian stateestimation of generally nonlinear stochastic dynamic systems. In particular, distributed point-mass filter algorithm is developed. It is comprised of a basic part that is accurate but data intense and optional step employing advanced copula theory. The optional step significantly reduces data transfer for the price of a small accuracy decrease. In the end, the developed algorithm is numerically compared to the usually employed distributed extended Kalman filter., Funding: project Improving the Quality of Internal Grant Schemes at the UWB [CZ.02.2.69/0.0/0.0/19 073/0016931, SGS-2022-022]; Industry Excellence Center LINK-SIC - VINNOVA; Saab AB

This paper investigates the impact of addition/removal/reweighting of edges in a complex networked linear control system. For networks of positive edge weights, we show that when adding edges leads to the creation of new cycles, these in turn may lead to instabilities. Dynamically, these cycles correspond to positive feedback loops. Conditions are provided under which the modified network is guaranteed to be stable. These conditions are related to the steady state value of the transfer function matrix of the newly created positive feedbacks. The tools we develop in the paper can be used to investigate the fragility of a network, i.e., its robustness to structured perturbations.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., Funding Agencies|Swedish Research Council [2020-03701]

This paper deals with distributed Bayesian stateestimation of generally nonlinear stochastic dynamic systems. In particular, distributed point-mass filter algorithm is developed. It is comprised of a basic part that is accurate but data intense and optional step employing advanced copula theory. The optional step significantly reduces data transfer for the price of a small accuracy decrease. In the end, the developed algorithm is numerically compared to the usually employed distributed extended Kalman filter., Funding: project Improving the Quality of Internal Grant Schemes at the UWB [CZ.02.2.69/0.0/0.0/19 073/0016931, SGS-2022-022]; Industry Excellence Center LINK-SIC - VINNOVA; Saab AB

This paper deals with distributed Bayesian stateestimation of generally nonlinear stochastic dynamic systems. In particular, distributed point-mass filter algorithm is developed. It is comprised of a basic part that is accurate but data intense and optional step employing advanced copula theory. The optional step significantly reduces data transfer for the price of a small accuracy decrease. In the end, the developed algorithm is numerically compared to the usually employed distributed extended Kalman filter., Funding: project Improving the Quality of Internal Grant Schemes at the UWB [CZ.02.2.69/0.0/0.0/19 073/0016931, SGS-2022-022]; Industry Excellence Center LINK-SIC - VINNOVA; Saab AB

This paper investigates the impact of addition/removal/reweighting of edges in a complex networked linear control system. For networks of positive edge weights, we show that when adding edges leads to the creation of new cycles, these in turn may lead to instabilities. Dynamically, these cycles correspond to positive feedback loops. Conditions are provided under which the modified network is guaranteed to be stable. These conditions are related to the steady state value of the transfer function matrix of the newly created positive feedbacks. The tools we develop in the paper can be used to investigate the fragility of a network, i.e., its robustness to structured perturbations.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., Funding Agencies|Swedish Research Council [2020-03701]

This paper investigates the impact of addition/removal/reweighting of edges in a complex networked linear control system. For networks of positive edge weights, we show that when adding edges leads to the creation of new cycles, these in turn may lead to instabilities. Dynamically, these cycles correspond to positive feedback loops. Conditions are provided under which the modified network is guaranteed to be stable. These conditions are related to the steady state value of the transfer function matrix of the newly created positive feedbacks. The tools we develop in the paper can be used to investigate the fragility of a network, i.e., its robustness to structured perturbations.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., Funding Agencies|Swedish Research Council [2020-03701]

The increase in perception capabilities of connected mobile sensor platforms (e.g., self-driving vehicles, drones, and robots) leads to an extensive surge of sensed features at various temporal and spatial scales. Beyond their traditional use for safe operation, available observations could enable to see how and where people move on sidewalks and cycle paths, to eventually obtain a complete microscopic and macroscopic picture of the traffic flows in a larger area. This paper proposes a new method for advanced traffic applications, tracking an unknown and varying number of moving targets (e.g., pedestrians or cyclists) constrained by a road network, using mobile (e.g., vehicles) spatially distributed sensor platforms. The key contribution in this paper is to introduce the concept of network bound targets into the multi-target tracking problem, and hence to derive a network-constrained multi-hypotheses tracker (NC-MHT) to fully utilize the available road information. This is done by introducing a target representation, comprising a traditional target tracking representation and a discrete component placing the target on a given segment in the network. A simulation study shows that the method performs well in comparison to the standard MHT filter in free space. Results particularly highlight network-constraint effects for more efficient target predictions over extended periods of time, and in the simplification of the measurement association process, as compared to not utilizing a network structure. This theoretical work also directs attention to latent privacy concerns for potential applications., Funding Agencies|European Research Council; Amsterdam Institute for Advanced Metropolitan Solutions through the ALLEGRO [669792]; Center for Industrial Information Technology at Linkoeping University (CENIIT) [17.12]

This paper investigates the impact of addition/removal/reweighting of edges in a complex networked linear control system. For networks of positive edge weights, we show that when adding edges leads to the creation of new cycles, these in turn may lead to instabilities. Dynamically, these cycles correspond to positive feedback loops. Conditions are provided under which the modified network is guaranteed to be stable. These conditions are related to the steady state value of the transfer function matrix of the newly created positive feedbacks. The tools we develop in the paper can be used to investigate the fragility of a network, i.e., its robustness to structured perturbations.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., Funding Agencies|Swedish Research Council [2020-03701]

The increase in perception capabilities of connected mobile sensor platforms (e.g., self-driving vehicles, drones, and robots) leads to an extensive surge of sensed features at various temporal and spatial scales. Beyond their traditional use for safe operation, available observations could enable to see how and where people move on sidewalks and cycle paths, to eventually obtain a complete microscopic and macroscopic picture of the traffic flows in a larger area. This paper proposes a new method for advanced traffic applications, tracking an unknown and varying number of moving targets (e.g., pedestrians or cyclists) constrained by a road network, using mobile (e.g., vehicles) spatially distributed sensor platforms. The key contribution in this paper is to introduce the concept of network bound targets into the multi-target tracking problem, and hence to derive a network-constrained multi-hypotheses tracker (NC-MHT) to fully utilize the available road information. This is done by introducing a target representation, comprising a traditional target tracking representation and a discrete component placing the target on a given segment in the network. A simulation study shows that the method performs well in comparison to the standard MHT filter in free space. Results particularly highlight network-constraint effects for more efficient target predictions over extended periods of time, and in the simplification of the measurement association process, as compared to not utilizing a network structure. This theoretical work also directs attention to latent privacy concerns for potential applications., Funding Agencies|European Research Council; Amsterdam Institute for Advanced Metropolitan Solutions through the ALLEGRO [669792]; Center for Industrial Information Technology at Linkoeping University (CENIIT) [17.12]

This paper investigates the impact of addition/removal/reweighting of edges in a complex networked linear control system. For networks of positive edge weights, we show that when adding edges leads to the creation of new cycles, these in turn may lead to instabilities. Dynamically, these cycles correspond to positive feedback loops. Conditions are provided under which the modified network is guaranteed to be stable. These conditions are related to the steady state value of the transfer function matrix of the newly created positive feedbacks. The tools we develop in the paper can be used to investigate the fragility of a network, i.e., its robustness to structured perturbations.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)., Funding Agencies|Swedish Research Council [2020-03701]

The increase in perception capabilities of connected mobile sensor platforms (e.g., self-driving vehicles, drones, and robots) leads to an extensive surge of sensed features at various temporal and spatial scales. Beyond their traditional use for safe operation, available observations could enable to see how and where people move on sidewalks and cycle paths, to eventually obtain a complete microscopic and macroscopic picture of the traffic flows in a larger area. This paper proposes a new method for advanced traffic applications, tracking an unknown and varying number of moving targets (e.g., pedestrians or cyclists) constrained by a road network, using mobile (e.g., vehicles) spatially distributed sensor platforms. The key contribution in this paper is to introduce the concept of network bound targets into the multi-target tracking problem, and hence to derive a network-constrained multi-hypotheses tracker (NC-MHT) to fully utilize the available road information. This is done by introducing a target representation, comprising a traditional target tracking representation and a discrete component placing the target on a given segment in the network. A simulation study shows that the method performs well in comparison to the standard MHT filter in free space. Results particularly highlight network-constraint effects for more efficient target predictions over extended periods of time, and in the simplification of the measurement association process, as compared to not utilizing a network structure. This theoretical work also directs attention to latent privacy concerns for potential applications., Funding Agencies|European Research Council; Amsterdam Institute for Advanced Metropolitan Solutions through the ALLEGRO [669792]; Center for Industrial Information Technology at Linkoeping University (CENIIT) [17.12]

The increase in perception capabilities of connected mobile sensor platforms (e.g., self-driving vehicles, drones, and robots) leads to an extensive surge of sensed features at various temporal and spatial scales. Beyond their traditional use for safe operation, available observations could enable to see how and where people move on sidewalks and cycle paths, to eventually obtain a complete microscopic and macroscopic picture of the traffic flows in a larger area. This paper proposes a new method for advanced traffic applications, tracking an unknown and varying number of moving targets (e.g., pedestrians or cyclists) constrained by a road network, using mobile (e.g., vehicles) spatially distributed sensor platforms. The key contribution in this paper is to introduce the concept of network bound targets into the multi-target tracking problem, and hence to derive a network-constrained multi-hypotheses tracker (NC-MHT) to fully utilize the available road information. This is done by introducing a target representation, comprising a traditional target tracking representation and a discrete component placing the target on a given segment in the network. A simulation study shows that the method performs well in comparison to the standard MHT filter in free space. Results particularly highlight network-constraint effects for more efficient target predictions over extended periods of time, and in the simplification of the measurement association process, as compared to not utilizing a network structure. This theoretical work also directs attention to latent privacy concerns for potential applications., Funding Agencies|European Research Council; Amsterdam Institute for Advanced Metropolitan Solutions through the ALLEGRO [669792]; Center for Industrial Information Technology at Linkoeping University (CENIIT) [17.12]

The increase in perception capabilities of connected mobile sensor platforms (e.g., self-driving vehicles, drones, and robots) leads to an extensive surge of sensed features at various temporal and spatial scales. Beyond their traditional use for safe operation, available observations could enable to see how and where people move on sidewalks and cycle paths, to eventually obtain a complete microscopic and macroscopic picture of the traffic flows in a larger area. This paper proposes a new method for advanced traffic applications, tracking an unknown and varying number of moving targets (e.g., pedestrians or cyclists) constrained by a road network, using mobile (e.g., vehicles) spatially distributed sensor platforms. The key contribution in this paper is to introduce the concept of network bound targets into the multi-target tracking problem, and hence to derive a network-constrained multi-hypotheses tracker (NC-MHT) to fully utilize the available road information. This is done by introducing a target representation, comprising a traditional target tracking representation and a discrete component placing the target on a given segment in the network. A simulation study shows that the method performs well in comparison to the standard MHT filter in free space. Results particularly highlight network-constraint effects for more efficient target predictions over extended periods of time, and in the simplification of the measurement association process, as compared to not utilizing a network structure. This theoretical work also directs attention to latent privacy concerns for potential applications., Funding Agencies|European Research Council; Amsterdam Institute for Advanced Metropolitan Solutions through the ALLEGRO [669792]; Center for Industrial Information Technology at Linkoeping University (CENIIT) [17.12]

The use of the CDIO framework in the development of the ECIU University is presented. The paper discusses the relatively moderate adaptations and modifications of the CDIO Syllabus and Standards that are necessary to make the documents applicable also in this context. Since challenge-based learning (CBL) is central learning format in the ECIU University, special attention is given to the connections between CBL method, the conceive-design-implement-operate sequence and project-based learning, which is central in the CDIO framework. The paper presents both general aspects and examples of the applications and activities within ECIU University and Linköping University (LiU). The main messages of the paper are that the development of the ECIU University will benefit from applying the CDIO framework since it offers references for what an education should give, in terms of knowledge and skills, and how an education program should be designed. In addition, the components of the CDIO framework require a moderate amount of adaptation to be directly applicable. Examples of the ongoing implementation activities at LiU.

The use of the CDIO framework in the development of the ECIU University is presented. The paper discusses the relatively moderate adaptations and modifications of the CDIO Syllabus and Standards that are necessary to make the documents applicable also in this context. Since challenge-based learning (CBL) is central learning format in the ECIU University, special attention is given to the connections between CBL method, the conceive-design-implement-operate sequence and project-based learning, which is central in the CDIO framework. The paper presents both general aspects and examples of the applications and activities within ECIU University and Linköping University (LiU). The main messages of the paper are that the development of the ECIU University will benefit from applying the CDIO framework since it offers references for what an education should give, in terms of knowledge and skills, and how an education program should be designed. In addition, the components of the CDIO framework require a moderate amount of adaptation to be directly applicable. Examples of the ongoing implementation activities at LiU.

The use of the CDIO framework in the development of the ECIU University is presented. The paper discusses the relatively moderate adaptations and modifications of the CDIO Syllabus and Standards that are necessary to make the documents applicable also in this context. Since challenge-based learning (CBL) is central learning format in the ECIU University, special attention is given to the connections between CBL method, the conceive-design-implement-operate sequence and project-based learning, which is central in the CDIO framework. The paper presents both general aspects and examples of the applications and activities within ECIU University and Linköping University (LiU). The main messages of the paper are that the development of the ECIU University will benefit from applying the CDIO framework since it offers references for what an education should give, in terms of knowledge and skills, and how an education program should be designed. In addition, the components of the CDIO framework require a moderate amount of adaptation to be directly applicable. Examples of the ongoing implementation activities at LiU.

The use of the CDIO framework in the development of the ECIU University is presented. The paper discusses the relatively moderate adaptations and modifications of the CDIO Syllabus and Standards that are necessary to make the documents applicable also in this context. Since challenge-based learning (CBL) is central learning format in the ECIU University, special attention is given to the connections between CBL method, the conceive-design-implement-operate sequence and project-based learning, which is central in the CDIO framework. The paper presents both general aspects and examples of the applications and activities within ECIU University and Linköping University (LiU). The main messages of the paper are that the development of the ECIU University will benefit from applying the CDIO framework since it offers references for what an education should give, in terms of knowledge and skills, and how an education program should be designed. In addition, the components of the CDIO framework require a moderate amount of adaptation to be directly applicable. Examples of the ongoing implementation activities at LiU.

The use of the CDIO framework in the development of the ECIU University is presented. The paper discusses the relatively moderate adaptations and modifications of the CDIO Syllabus and Standards that are necessary to make the documents applicable also in this context. Since challenge-based learning (CBL) is central learning format in the ECIU University, special attention is given to the connections between CBL method, the conceive-design-implement-operate sequence and project-based learning, which is central in the CDIO framework. The paper presents both general aspects and examples of the applications and activities within ECIU University and Linköping University (LiU). The main messages of the paper are that the development of the ECIU University will benefit from applying the CDIO framework since it offers references for what an education should give, in terms of knowledge and skills, and how an education program should be designed. In addition, the components of the CDIO framework require a moderate amount of adaptation to be directly applicable. Examples of the ongoing implementation activities at LiU.

Search-And-Rescue (SAR) is one of manyfields with applications benefiting from the increasingavailability of Unmanned Aerial Systems (UASs). Most UAS applications rely on the UAS’s capabilityto carry a camera and stream video data for manualor automated processing. However, this relies onunobstructed views of the target, which limits the applicability of these systems. In this paper, we instead describe the development and initial application testing of a system with a UAS-carried harmonic radar. This sensor is designed to detect the presence of Recco radar reflectors, commonly found integrated into alpine clothes and gear. The reflectors can be detected through vegetation and snow and is independent of many external factors such as lighting conditions. The paper describesthe system design and provides initial real-world results. The initial tests show fruitful results and opens up several avenues of continued research and development., Funding agencies:This project has been performed with support from Sweden's Innovation Agency, project nr. 2018–01762, “Digitalized Search and Rescue”., Digitaliserad skallgång

Search-And-Rescue (SAR) is one of manyfields with applications benefiting from the increasingavailability of Unmanned Aerial Systems (UASs). Most UAS applications rely on the UAS’s capabilityto carry a camera and stream video data for manualor automated processing. However, this relies onunobstructed views of the target, which limits the applicability of these systems. In this paper, we instead describe the development and initial application testing of a system with a UAS-carried harmonic radar. This sensor is designed to detect the presence of Recco radar reflectors, commonly found integrated into alpine clothes and gear. The reflectors can be detected through vegetation and snow and is independent of many external factors such as lighting conditions. The paper describesthe system design and provides initial real-world results. The initial tests show fruitful results and opens up several avenues of continued research and development., Funding agencies:This project has been performed with support from Sweden's Innovation Agency, project nr. 2018–01762, “Digitalized Search and Rescue”., Digitaliserad skallgång

Search-And-Rescue (SAR) is one of manyfields with applications benefiting from the increasingavailability of Unmanned Aerial Systems (UASs). Most UAS applications rely on the UAS’s capabilityto carry a camera and stream video data for manualor automated processing. However, this relies onunobstructed views of the target, which limits the applicability of these systems. In this paper, we instead describe the development and initial application testing of a system with a UAS-carried harmonic radar. This sensor is designed to detect the presence of Recco radar reflectors, commonly found integrated into alpine clothes and gear. The reflectors can be detected through vegetation and snow and is independent of many external factors such as lighting conditions. The paper describesthe system design and provides initial real-world results. The initial tests show fruitful results and opens up several avenues of continued research and development., Funding agencies:This project has been performed with support from Sweden's Innovation Agency, project nr. 2018–01762, “Digitalized Search and Rescue”., Digitaliserad skallgång