The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Agile robots, such as small Unmanned Aerial Vehicles (UAVs) can have a great impact on the automation of tasks, such as industrial inspection and maintenance or crop monitoring and fertilization in agriculture. Their deploy-ability, however, relies on the UAV's ability to self-localize with precision and exhibit robustness to common sources of uncertainty in real missions. Here, we propose a new system...
Marine robots and unmanned surface vehicles will increasingly be deployed in rivers and riverine environments. The structure produced by flowing waters may be exploited for purposes of estimation, planning, and control. This paper adopts a widely acknowledged model for the geometry of watercourse channels, namely sine-generated curves, as a basis for estimators that predict the shape of the yet unseen...
Real-time monocular SLAM is increasingly mature and entering commercial products. However, there is a divide between two techniques providing similar performance. Despite the rise of ‘dense’ and ‘semi-dense’ methods which use large proportions of the pixels in a video stream to estimate motion and structure via alternating estimation, they have not eradicated feature-based methods which use a significantly...
This paper deals with the problem of active sensing control for nonlinear differentially flat systems. The objective is to improve the estimation accuracy of an observer by determining the inputs of the system that maximise the amount of information gathered by the outputs over a time horizon. In particular, we use the Observability Gramian (OG) to quantify the richness of the acquired information...
Stochastic gradient algorithms are the main focus of large-scale optimization problems and led to important successes in the recent advancement of the deep learning algorithms. The convergence of SGD depends on the careful choice of learning rate and the amount of the noise in stochastic estimates of the gradients. In this paper, we propose an adaptive learning rate algorithm, which utilizes stochastic...
The most prominent criterion for learning of manipulation skills is the optimization of task success, modeled as expected reward or probability of success. This is sensible if we only want to optimize a single controller. But if learned manipulation primitives are used as modules in a larger system, then it is also important that their generated sensor traces facilitate recognition of action-outcomes...
System condition is an important characteristic in the stage of operation and maintenance during a life cycle. The system condition in respective time periods usually correlates to system time deterioration. Since the degradation may lead to both soft and hard failure, reliability characteristics might be needed to describe each type of such failure. We concentrate on selected oil characteristics...
This paper evaluates the use of a Photo Voltaic (PV) parameter estimation method based on implicit optimization algorithms and its use in power controller strategies by explicit model representation obtained with First and Second Order Approximation Models (FOAM, SOAM). An explicit function linking voltage, current and power of PV) cells is presented using the parameters obtained during the implicit...
Solutions to real world robotic tasks often require complex behaviors in high dimensional continuous state and action spaces. Reinforcement Learning (RL) is aimed at learning such behaviors but often fails for lack of scalability. To address this issue, Hierarchical RL (HRL) algorithms leverage hierarchical policies to exploit the structure of a task. However, many HRL algorithms rely on task specific...
Automated driving has become an important research trend in the field of cooperative intelligent transportation systems and their applications in smart cities. Automated driving both increases road capacity and eliminates human errors, one of the most common reason of traffic accidents. Both these aspects influence significantly the quality of life, which is a major goal of smart city initiatives...
There are examples of systems in which equilibria is Lyapunov-unstable, but is located on a boundary of a forward-invariant set. For initial conditions in this set corresponding solutions remains bounded and the equilibrium in some case is a weak attractor. The goal of this paper is to find an algorithm for estimating for-ward invariant set for a class of unstable systems. The proposed algorithm is...
Approaches to decision-making in self-adaptive systems are increasingly becoming more effective at managing the target system by taking into account more elements of the decision problem that were previously ignored. These approaches have to solve complex optimization problems at run time, and even though they have been shown to be suitable for different kinds of systems, their time complexity can...
We consider two close ways of linearization for sublinear operator that takes compact convex values. The first way consists in a representation of given multioperator by the family of so called basis selectors that are single-valued linear bounded operators. The second way consists in linear extension of given multioperator from its values on some Hamel basis. Every of the ways above leads to its...
The lack of digital floor plans in most buildings has become a huge obstacle to pervasive indoor location based services (LBS). Recently there has been quite some research that leverages various sensing data such as inertial, WiFi and images from ubiquitous mobile devices (e.g., smartphones) to construct floor plans at large scale and low costs. Although great efforts are made to improve the accuracy...
The SLAM problem is known to have a special property that when robot orientation is known, estimating the history of robot poses and feature locations can be posed as a standard linear least squares problem. In this work, we develop a SLAM framework that uses relative feature-to-feature measurements to exploit this structural property of SLAM. Relative feature measurements are used to pose a linear...
Simultaneous Localisation and Mapping (SLAM) systems that recover the trajectory of a robot or mobile device are characterised by a front-end and back-end. The front-end uses sensor observations to identify loop closures; the back-end optimises the estimated trajectory to be consistent with these closures. The GraphSLAM framework formulates the back-end problem as a graph-based optimisation on a pose...
Pose-graph optimization is becoming popular as a tool for solving position and attitude determination problems, especially in the context of Visual Simultaneous Localization and Mapping (V-SLAM). Recently proprioceptive information sources are appearing in this context, such as inertial measurement units and kinematic/dynamic models. These models require other quantities to be estimated along with...
This paper presents the temporal enhancement of the graph-based depth estimation method, designed for multiview systems with arbitrarily located cameras. The primary goal of the proposed enhancement is to increase the quality of estimated depth maps and simultaneously decrease the time of estimation. The method consists of two stages: the temporal enhancement of segmentation required in used depth...
In applications such as home air conditioners and building chillers, optimizing a vapor compression system's energy consumption may lead to significant operational cost savings for the entire HVAC system. Model-free extremum seeking has recently been investigated as a means of real-time nonlinear programming for HVAC equipment. For mass produced vapor compression systems, gradient descent extremum...
A computational approach for system identification for the attitude dynamics of a rigid body is proposed. The estimation and system identification for the rigid body are particularly challenging as they evolve on the compact nonlinear manifold, referred to as the special orthogonal group. The current methods based on local parameterizations or quaternions suffer from the inherent singularities or...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.