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.
In range-based localization, the trajectory of a mobile object is estimated based on noisy range measurements between the object and known landmarks. In order to deal with this uncertain information, a Bayesian state estimator is presented, which exploits optimal stochastic linearization. Compared to standard state estimators like the Extended or Unscented Kalman Filter, where a point-based Gaussian...
This contribution introduces a three pillar information storage and management system for modeling the environment of autonomous systems. The main characteristics is the separation of prior knowledge, environment model and sensor information. In the center of the system is the environment model, which provides the autonomous system with information about the current state of the environment. It consists...
In this paper, a framework for nonlinear model predictive control (NMPC) for heavily noise-affected systems is presented. Within this framework, the noise influence, which originates from uncertainties during model identification or measurement, is explicitly considered. This leads to a significant increase in the control quality. One part of the proposed framework is the efficient state prediction,...
For the collaborative control of a team of robots, a set of well-suited high-level control algorithms, especially for path planning and measurement scheduling, is essential. The quality of these control algorithms can be significantly increased by considering uncertainties that arise, e.g. from noisy measurements or system model abstraction, by incorporating stochastic filters into the control. To...
Model identification and measurement acquisition is always to some degree uncertain. Therefore, a framework for nonlinear model predictive control (NMPC) is proposed that explicitly considers the noise influence on nonlinear dynamic systems with continuous state spaces and a finite set of control inputs in order to significantly increase the control quality. Integral parts of NMPC are the prediction...
Extended range telepresence allows a human user to intuitively teleoperate a mobile robot through arbitrarily large remote environments by natural walking. In order to give the user the possibility to navigate the robot through an arbitrarily large remote environments, while his own environment is of limited size, motion compression is used. The motion compression framework provides a nonlinear transformation...
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.