| 1. |
- Adib Yaghmaie, Farnaz, et al.
(author)
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Using Reinforcement Learning for Model-free Linear Quadratic Control with Process and Measurement Noises
- 2019
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In: 2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 9781728113982 - 9781728113999 ; , s. 6510-6517
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Conference paper (peer-reviewed)abstract
- In this paper, we analyze a Linear Quadratic (LQ) control problem in terms of the average cost and the structure of the value function. We develop a completely model-free reinforcement learning algorithm to solve the LQ problem. Our algorithm is an off-policy routine where each policy is greedy with respect to all previous value functions. We prove that the algorithm produces stable policies given that the estimation errors remain small. Empirically, our algorithm outperforms the classical Q and off-policy learning routines.
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| 2. |
- Alickovic, Emina, et al.
(author)
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A System Identification Approach to Determining Listening Attention from EEG Signals
- 2016
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In: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO). - : IEEE. - 9780992862657 - 9781509018918 ; , s. 31-35
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Conference paper (peer-reviewed)abstract
- We still have very little knowledge about how ourbrains decouple different sound sources, which is known assolving the cocktail party problem. Several approaches; includingERP, time-frequency analysis and, more recently, regression andstimulus reconstruction approaches; have been suggested forsolving this problem. In this work, we study the problem ofcorrelating of EEG signals to different sets of sound sources withthe goal of identifying the single source to which the listener isattending. Here, we propose a method for finding the number ofparameters needed in a regression model to avoid overlearning,which is necessary for determining the attended sound sourcewith high confidence in order to solve the cocktail party problem.
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| 3. |
- Ancuti, Codruta O., et al.
(author)
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NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report
- 2023
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In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). - Vancover : Institute of Electrical and Electronics Engineers (IEEE).
-
Conference paper (peer-reviewed)abstract
- This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams that competed in the final testing phase, and the proposed solutions demonstrated the cutting-edge in image dehazing technology.
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| 4. |
- Ardeshiri, Tohid, et al.
(author)
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Bicycle Tracking Using Ellipse Extraction
- 2011
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In: Proceedings of the 14thInternational Conference on Information Fusion, 2011. - : IEEE. - 9781457702679 ; , s. 1-8
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Conference paper (peer-reviewed)abstract
- A new approach to track bicycles from imagery sensor data is proposed. It is based on detecting ellipsoids in the images, and treat these pair-wise using a dynamic bicycle model. One important application area is in automotive collision avoidance systems, where no dedicated systems for bicyclists yet exist and where very few theoretical studies have been published. Possible conflicts can be predicted from the position and velocity state in the model, but also from the steering wheel articulation and roll angle that indicate yaw changes before the velocity vector changes. An algorithm is proposed which consists of an ellipsoid detection and estimation algorithm and a particle filter. A simulation study of three critical single target scenarios is presented, and the algorithm is shown to produce excellent state estimates. An experiment using a stationary camera and the particle filter for state estimation is performed and has shown encouraging results.
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| 5. |
- Axelsson, Patrik, 1985-, et al.
(author)
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Extended Kalman Filter Applied to Industrial Manipulators
- 2010
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In: Proceedings of Reglermöte 2010.
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Conference paper (other academic/artistic)abstract
- This paper summarizes previous work on tool position estimation on industrial manipulators, and emphasize the problems that must be taken care of in order to get a satisfied result. The acceleration of the robot tool, measured by an accelerometer, together with measurements of motor angles are used. The states are estimated with an extended Kalman filter. A method for tuning the covariance matrices for the noise, used in the observer, is suggested. The work has been focused on a robot with two degrees of freedom.
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| 6. |
- Axelsson, Patrik, 1985-, et al.
(author)
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ML Estimation of Process Noise Variance in Dynamic Systems
- 2011
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In: Proceedings of the 18th IFAC World Congress. - 9783902661937 ; , s. 5609-5614
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Conference paper (peer-reviewed)abstract
- The performance of a non-linear filter hinges in the end on the accuracy of the assumed non-linear model of the process. In particular, the process noise covariance Q is hard to get by physical modeling and dedicated system identification experiments. We propose a variant of the expectation maximization (EM) algorithm which iteratively estimates the unobserved state sequence and Q based on the observations of the process. The extended Kalman smoother (EKS) is the instrument to find the unobserved state sequence. Our contribution fills a gap in literature, where previously only the linear Kalman smoother and particle smoother have been applied. The algorithm will be important for future industrial robots with more flexible structures, where the particle smoother cannot be applied due to the high state dimension. The proposed method is compared to two alternative methods on a simulated robot.
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| 7. |
- Axholt, Magnus, et al.
(author)
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Optical See-Through Head Mounted Display : Direct Linear Transformation Calibration Robustness in the Presence of User Alignment Noise
- 2010
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In: Proceedings of the 54th Annual Meeting of the Human Factors and Ergonomics Society. - Linköping : Linköping University Electronic Press. - 9780945289371
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Conference paper (peer-reviewed)abstract
- The correct spatial registration between virtual and real objects in optical see-through augmented reality implies accurate estimates of the user’s eyepoint relative to the location and orientation of the display surface. A common approach is to estimate the display parameters through a calibration procedure involving a subjective alignment exercise. Human postural sway and targeting precision contribute to imprecise alignments, which in turn adversely affect the display parameter estimation resulting in registration errors between virtual and real objects. The technique commonly used has its origin incomputer vision, and calibrates stationary cameras using hundreds of correspondence points collected instantaneously in one video frame where precision is limited only by pixel quantization and image blur. Subsequently the input noise level is several order of magnitudes greater when a human operator manually collects correspondence points one by one. This paper investigates the effect of human alignment noise on view parameter estimation in an optical see-through head mounted display to determine how well astandard camera calibration method performs at greater noise levels than documented in computer vision literature. Through Monte-Carlo simulations we show that it is particularly difficult to estimate the user’s eyepoint in depth, but that a greater distribution of correspondence points in depth help mitigate the effects of human alignment noise.
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| 8. |
- Bergström, Andreas, 1978-, et al.
(author)
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TOA Estimation Improvements in Multipath Environments by Measurement Error Models
- 2017
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In: Proceedings of the 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538635315 - 9781538635308 ; , s. 1-8
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Conference paper (peer-reviewed)abstract
- Many positioning systems rely on accuratetime of arrival measurements. In this paper, we addressnot only the accuracy but also the relevance of Time ofArrival (TOA) measurement error modeling. We discusshow better knowledge of these errors can improve relativedistance estimation, and compare the impact of differentlydetailed measurement error information. These models arecompared in simulations based on models derived froman Ultra Wideband (UWB) measurement campaign. Theconclusion is that significant improvements can be madewithout providing detailed received signal information butwith a generic and relevant measurement error model.
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| 9. |
- Blom, Jonas, et al.
(author)
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Pole Placement Design of Power Control Algorithms
- 1999
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In: Proceedings of the 49th IEEE Vehicular Technology Conference. - Linköping : Linköping University Electronic Press. - 0780355652
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Conference paper (peer-reviewed)abstract
- Time delays reduces the performance of any controlled system. If neglected in the design phase, the system may even become unstable when using the designed controller. Several power control strategies have been proposed in order to improve the capacity of cellular radio systems, but time delays are usually neglected. Here, it is shown that the problems can be handled by considering the time delays in the design phase in order to choose the appropriate parameter values. Most popular algorithms can be seen as special cases of an integrating controller. This structure is extended first to a proportional integrating (PI)-controller and then further on to a general linear controller of higher orders. Corresponding design procedures are outlined based on techniques, such as pole placement, from the field of automatic control. The PI-controller is a very appealing choice of structure, with better performance compared to an I-controller and less complex than a higher order controller. The benefits are further illuminated by network simulations.
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| 10. |
- Braga, André Ribeiro, et al.
(author)
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Cooperative Navigation and Coverage Identification with Random Gossip and Sensor Fusion
- 2016
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In: Proc. IEEE 9th Sensor Array and Multichannel Signal Processing Workshop (SAM). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1-5
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Conference paper (peer-reviewed)abstract
- This paper is concerned with cooperative Terrain Aided Navigation of a network of aircraft using fusion of Radar Altimeter and inter-node range measurements. State inference is performed using a Rao-Blackwellized Particle Filter with online measurement noise statistics estimation. For terrain coverage measurement noise parameter identification, an online Expectation Maximization algorithm is proposed, where local sufficient statistics at each node are calculated in the E-step, which are then distributed to neighboring nodes using a random gossip algorithm to perform the M-step at each node. Simulation results show that improvement on positioning and calibration performance can be achieved compared to a non-cooperative approach.
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