Sequential optimal positioning of mobile sensors using mutual information

Indoor positioning using mobile sensors

Many of these pre-existing solutions, however, rely on WLAN entries, which can hinder their accuracy, due to various environmental factors, such as the exchange and maintenance of WiFi routers position, occlusion generated by walls and even people themselves. This is due to the fact that 2.4GHz, which is the main frequency band for WiFi, is also the resonance frequency of water and human bodies...

Selection of Image Features for Robot Positioning using Mutual Information

The authors previously developed a prototype f o r visual robot positioning, based o n global image descriptors and neural networks [15]. Now, a procedure to automatically select subsets of image features most relevant to determine pose variations along each of the six degrees of freedom (dof’s) has been incorporated into the prototype. This procedure is based o n a statistical measure of varia...

Searching optimal feature subset using mutual information

A novel feature selection methodology is proposed with the concept of mutual information. The proposed methodology effectively circumvents two major problems in feature selection process: to identify the irrelevancy and redundancy in the feature set, and to estimate the optimal feature subset for classification task.

Mobile Robot Positioning: Sensors and Techniques

Mobile robot positioning: Sensors and techniques

Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In search for a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This paper provides a review of relevant mobile robot positioning technologies. The paper defines seven categories for positioning systems: 1. Odometry; 2...