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. Usually localization ...

In this paper we describe the problem of Visual Place Categorization (VPC) for mobile robotics, which involves predicting the semantic category of a place from image measurements acquired from an autonomous platform. ...

Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics ...

The armed forces have a considerable amount of experience in using robots for bomb removal and mine clearing. Emerging technology also enables the targeting of other applications. To evaluate if real deployment of new ...

In this paper, the design of an office-guide robot for social interaction studies is presented. We are interested in studying the impact of passage behaviours in casual encounters. While the system offers assistance in ...

Casual encounters with mobile robots for nonexperts can be a challenge due to lack of an interaction model. The present work is based on the rules from proxemics which are used to design a passing strategy. In narrow ...

Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes can represent a continuous-time trajectory, ...

Scan-matching based on data from a laser scanner is frequently used for mapping and localization. This paper presents an scan-matching approach based instead on visual information from a stereo system. The Scale Invariant ...

Human interaction with a service robot requires a shared representation of the environment for spoken dialogue and task specification where names used for particular locations are depending on personal preferences. A ...

We present incremental smoothing and mapping (iSAM), a novel approach to the simultaneous localization and mapping problem that is based on fast incremental matrix factorization. iSAM provides an efficient and exact ...