Towards Robust Place Recognition for Robot Localization
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Visual behavior recognition is currently a highly active research area. This is due both to the scientific challenge posed by the complexity of the task, and to the growing interest in its applications, such as automated visual surveillance, human-computer ...
The purpose of this article is to identify possible scenarios for the evolution of the European water supply and sanitation sectors (WSS) in the next 15 years, on the basis of empirical knowledge of its dynamics. These are: tendered market, tendered market ...
Contemporary society is based on a perpetual evolution of personal opinions and likings. The transmission of knowledge is questioned, but if the education and teaching about a critical vision is considered an essential instrument, so the schools and the ma ...
An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Recent advances in vision have made this modality a via ...
The capability to learn from experience is a key property for autonomous cognitive systems working in realistic settings. To this end, this paper presents an SVM- -based algorithm, capable of learning model representations incrementally while keeping under ...
An increasing need for healthcare provision and assistive technologies (AT) calls for the development of machine learning techniques able to cope with the variability inherent to real-world deployments. In the particular case of activity recognition applic ...
The Object Constraint Language (OCL) has been for many years formalized both in its syntax and semantics in the language standard. While the official definition of OCL's syntax is already widely accepted and strictly supported by most OCL tools, there is n ...
A mapping system by vision-aided inertial navigation was developed for areas where GNSS signals are unreachable. In this framework, a methodology on the integration of vision and inertial sensors is presented, analysed and tested. The system employs the me ...
This paper presents an SVM-based algorithm for the transfer of knowledge across robot platforms aiming to perform the same task. Our method exploits efficiently the transferred knowledge while updating incrementally the internal representation as new infor ...
The capability to learn from experience is a key property for autonomous cognitive systems working in realistic settings. To this end, this paper presents an SVM-based algorithm, capable of learning model representations incrementally while keeping under c ...