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.
This paper presents a method for SLAM in Robot and Wireless Sensor Network (WSN) System using Bayes framework. A mobile robot equipped with sensor measuring the range to WSN nodes by Received Signal Strength Indicator (RSSI) can simultaneously localize itself as well as locate the sensor nodes of WSN. We adopted an algorithm based Rao-Blackwellized Particle Filter (RBPF) to integrate measurements...
This paper presents a new method of localization and map building of mobile robot based on mixed map model using LRF (Laser Range Finder). The mixed model composed of occupancy grids and line character maps is utilized to represent the environment map. Firstly, the LRF models and Bayes rules are used to construct a local occupancy grid map. Then, we extract obstacles points to get a precise geometry...
A hybrid Bayesian/ frequentist approach is presented for the simultaneous localization and mapping problem (SLAM). A frequentist approach is proposed for mapping with time varying robotic poses and is generalized to the case when the robotic pose is both time varying and uncertain. The SLAM problem is then solved in two steps: 1) the robot is localized with respect to a sparse set of landmarks in...
Our sensor selection algorithm targets the problem of global self-localization of multi-sensor mobile robots. The algorithm builds on the probabilistic reasoning using Bayes filters to estimate sensor measurement uncertainty and sensor validity in robot localization. For quantifying measurement uncertainty we score the Bayesian belief probability density using a model selection criterion, and for...
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.