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This thesis presents models and methods for feedback-based resource management for cyber-physical systems. Common for the scenarios considered are severe resource constraints, uncertain and time-varying conditions and the goal of enabling flexibility in systems design rather than restricting it. A brief survey on reservation-based scheduling, an important enabling technology for this thesis, is pr
This paper explores a formally grounded ap- proach to solve the problem of dynamic binding in service- oriented software architecture. Dynamic binding is a widely adopted mean to automatically bind exposed software interfaces to actual implementations. The execution of an operation on one or another implementation, though providing the same result, could turn out in different quality of service, e
Based on previous results on linear predictors and Kalman filter, this paper will formulate multi-step-ahead multi-variate predictors for application in multi-step-ahead predictive control.
This thesis explores methods for solving the structure-and-motion problem in computer vision, the recovery of three-dimensional data from a series of two-dimensional image projections. The first paper investigates an alternative state space parametrization for use with the Kalman filter approach to simultaneous localization and mapping, and shows it has superior convergence properties compared wit
We consider the problem of localizing a novel image in a large 3D model. In principle, this is just an instance of camera pose estimation, but the scale introduces some challenging problems. For one, it makes the correspondence problem very difficult and it is likely that there will be a significant rate of outliers to handle. In this paper we use recent theoretical as well as technical advances t
Embedded systems often operate in so variable con- ditions that design can only be carried out for some worst-case scenario. This leads to over-provisioned resources, and undue power consumption. Feedback control is an effective (and not yet fully explored) way to tailor resource usage online, thereby making the system behave and consume as if it was optimized for each specific utilization case. A
This report addresses the related problems of trajectory generation and time-optimal path tracking with online obstacle avoidance. We consider the class of four-wheeled vehicles with independent steering and driving on each wheel, also referred to as pseudo-omnidirectional vehicles. Appropriate approximations of the dynamic model enable a convex reformulation of the path-tracking problem. Using th
There is currently a strongly growing interest in obtaining optimal control solutions for vehicle maneuvers, both in order to understand optimal vehicle behavior and to devise improved safety systems, either by direct deployment of the solutions or by including mimicked driving techniques of professional drivers. However, it is nontrivial to find the right mix of models, formulations, and optimiza
In this paper the impact of different meals and rapid insulin were estimated as Finite Impulse Response Models from a data set of 18 patients. Based on these models short-term individualized predictors were tested for 20 and 60 minute prediction. The predictors were evaluated using Clarke Grid Analysis and had on average more than 94 % and 75 % in the A zone and less than 1 % and 3 % in the erroro
A novel integrated approach to high-accuracy machining with industrial robots is presented in this paper. By combining a conventional industrial robot with an external compensation mechanism, a significantly higher bandwidth of the control of the relative position between the tool and the workpiece can be achieved. A model-based feedback controller for the compensation mechanism, as well as a mid-
Recently, the emergence of Kinect systems has demonstrated the benefits of predicting an intermediate body part labeling for 3D human pose estimation, in conjunction with RGB-D imagery. The availability of depth information plays a critical role, so an important question is whether a similar representation can be developed with sufficient robustness in order to estimate 3D pose from RGB images. Th
Constraining the temperature of computing systems has become a dominant design aspect. The supply voltage decrease has lost its pace even though the feature size is shrinking constantly. This results in an increased number of transistors per unit of area and hence a growing power density. Researchers started investigating dynamic thermal management techniques to trade-off performance for energy co
This paper deals with the problem of synchronization in networks of heterogeneous agents with common nominal behavior. The agents are modeled as (possibly nonlinear) perturbed versions of a common SISO nominal LTI operator, and they are interconnected via a sparse memoryless interconnection operator, coherent with the communication graph underlying the network. The network is said to synchronize i
In this paper, we address distributed convergence to fair allocations of CPU resources for time-sensitive applications. We propose a novel resource management framework where a centralized objective for fair allocations is decomposed into a pair of performance-driven recursive processes for updating: (a) the allocation of computing bandwidth to the applications (resource adaptation), executed by t
