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Geometric reconstruction from image collections is a classical computer vision problem. The problem essentially consists of two steps; First, the identification of matches and assembling of point tracks, and second, multiple view geometry computations. In this paper we address the problem of constructing point tracks using graph theoretical algorithms. From standard descriptor matches between all
We propose a distributed learning algorithm for fair scheduling in common-pool games. Common-pool games are strategic-form games where multiple agents compete over utilizing a limited common resource. A characteristic example is the medium access control problem in wireless communications, where multiple users need to decide how to share a single communication channel so that there are no collisio
This note studies lumped-delay approximations of distributed-delay elements arising in various problems involving delay compensation or preview utilization. Several approaches to reduce implementation complexity, understood as the number of delays required to attain a required accuracy level, are put forward. First, we derive the H2-optimal coefficients for a given delay pattern. This can be seen
In a dispatchable wind power plant, turbines are free to continuously vary their power production as long as the sum of their productions meets the total power demand. Previous research has shown that this freedom can be used to reduce structural loads by allowing turbines in the plant to coordinate their power. This paper explains the mechanisms that make power coordination useful for reducing st
Cloud applications are often subject to unexpected events like flash crowds and hardware failures. Without a predictable behaviour, users may abandon an unresponsive application. This problem has been partially solved on two separate fronts: first, by adding a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience, and, second, by intr
This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method admits general process descriptions in terms of frequency response data and it can cope with many different constraints. Examples are presented and some pitfalls in optimization are discussed.
This article presents a linear, iterative method to solve the eye-to-hand calibration problem between a wrist-mounted laser scanner and the tool flange of a robot. Measurement data are acquired from a set of non parallel planes whereafter the plane equations and desired rigid transformation matrix are found in a two-step, iterative fashion. The method is shown to handle large error in the initial
We investigate the out-of-sequence measurements particle filtering problem for a set of conditionally linear Gaussian state-space models, known as mixed linear/nonlinear state-space models. Two different algorithms are proposed, which both exploit the conditionally linear substructure. The first approach is based on storing only a subset of the particles and their weights, which implies low memory
In control theory there exist two convenient representations of a model, which are transfer functions and state-space matrices. However, structure in the transfer functions is not clearly seen in the state-space form, and on the other hand structure in the state-space form is not clearly seen in the transfer functions. The main reason for this is that Laplace transformation destroys most types of
We consider distributed model predictive control (DMPC) where a sparse centralized optimization problem without a terminal cost or a terminal constraint set is solved in distributed fashion. Distribution of the optimization algorithm is enabled by dual decomposition. Gradient methods are usually used to solve the dual problem resulting from dual decomposition. However, gradient methods are known f
We consider the classical 3-state Moore-Greitzer model, which is commonly used for approximating dynamics of deviations of flow and pressure variables in an axial compressor from their nominal steady-state values. The linearization of the nonlinear system is not controllable and, therefore, even local asymptotic stability cannot be achieved using methods of linear control theory. We propose a fami
Industrial robots are important when the degree of automation in industry is increased. To enable the use of robots also when the products change rapidly, the programming must be quick and easy to perform. One way to accomplish this is to use lead-through programming, i.e., the user manually guides the robot. This paper presents a sensorless approach, and thus avoids the need for a typically expen
Abstract in UndeterminedStabilization and optimal control is studied for state space systems with nonnegative coefficients (positive systems). In particular, we show that a stabilizing distributed feedback controller, when it exists, can be computed using linear programming. The same methods are also used to minimize the closed loop input-output gain. An example devoted to distributed control of a
To the purpose of marine seismic acquisition, new acoustic sources have been developed to reduce the environmental impact. The use of marine vibrators makes it possible to define emission frequency ranges, consequently allowing limitation of the frequencies that disturb marine animal life. Constructing marine vibrators with high efficiency and linear dynamics is however difficult, and the vibrator
A particle filter based solution to the out-of-sequence measurement (OOSM) problem is proposed. The solution is storage efficient, while being computationally fast. The filter approaches the multi-OOSM problem by not only updating the estimate at the most recent time, but also for all times between the OOSM time and the most recent time. This is done by exploiting the complete in-sequence informat
The simultaneous localization and mapping problem is approached by using an ultrasound sensor and wheel encoders. To be able to account for the low precision inherent in ultrasound sensors, the occupancy grid notion is extended. The extension takes into consideration with which angle the sensor is pointing, to compensate for the issue that an object is not necessarily detectable from all position
Distributed Decision Making and Control is a mathematical treatment of relevant problems in distributed control, decision and multi-agent systems, The research reported was prompted by the recent rapid development in large-scale networked and embedded systems and communications. One of the main reasons for the growing complexity in such systems is the dynamics introduced by computation and communi
The strong process forces arising during high-speed machining operations, combined with the limited stiffness of industrial robots, have hampered the usage of industrial robots in high-end milling tasks. However, since such manipulators may offer flexible and cost-effective machining solutions, a three-dimensional piezo-actuated compensation mechanism, which aims to compensate for the positioning
