Abstract. In this this paper, we present a solution to the simultaneous localization and mapping (SLAM) problem for a robot equipped with a single perspective camera. We track extr...
This paper addresses the problem of exploration and mapping of an unknown environment by multiple robots. The mapping algorithm is an on-line approach to likelihood maximization t...
Reid G. Simmons, David Apfelbaum, Wolfram Burgard,...
Successful approaches to the robot localization problem include Monte Carlo particle filters, which estimate non-parametric localization belief distributions. However, particle ...
— This paper presents the Common State Filter (CSF), a novel and efficient suboptimal Multiple Hypothesis SLAM (MHSLAM) method for Kalman Filter-based SLAM algorithms. Conventio...
In this paper, we present a new multiple hypotheses tracking (MHT) approach. Our tracking method is suitable for online applications, because it labels objects at every frame and ...