Abstract. The Scale Invariant Feature Transform (SIFT) has become a popular feature extractor for vision-based applications. It has been successfully applied to metric localization...
— In this paper, we define a mobile self-localization (MSL) problem for sparse mobile sensor networks, and propose an algorithm named Mobility Assisted MDS-MAP(P), based on Mult...
The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot localization. Still, the number of features extracted with this approach is immense, especially...
— This article presents a behavioural architecture, the Survival Kit (SK), which allows behaviours to cast their multivalued output by means of constraints over an ’action feat...
Navigation in unknown or partially unknown environments remains one of the biggest challenges in today's mobile robotics. Environmental modeling, perception, localization and ...