Particle filter is a powerful algorithm to deal with non-linear and non-Gaussian tracking problems. However the algorithm relying only upon one image cue often fails in challengin...
We address the problem of fusing sparse and noisy depth data obtained from a range finder with features obtained from intensity images to estimate ego-motion and refine 3D struct...
State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
— Recently Rao-Blackwellized particle filters have been introduced as effective means to solve the simultaneous localization and mapping (SLAM) problem. This approach uses a par...
Giorgio Grisetti, Cyrill Stachniss, Wolfram Burgar...
— An algorithm for tracking articulating objects from moving camera platforms is presented. Mixtures of mixtures are used to model the appearance of the object and the background...
Wael Abd-Almageed, Mohamed E. Hussein, Larry S. Da...
— In the simultaneous localization and mapping (SLAM) problem, a mobile robot must build a map of its environment while simultaneously determining its location within that map. W...
Localization is one of the important topics in robotics and it is essential to execute a mission. Most problems in the class of localization are due to uncertainties in the modelin...
Young-Joong Kim, Chan-Hee Won, Jung-Min Pak, Myo-T...
— This paper explores the planning and control of a manipulation task accomplished in conditions of high uncertainty. Statistical techniques, like particle filters, provide a fr...
Jiaxin L. Fu, Siddhartha S. Srinivasa, Nancy S. Po...
— Location tracking in wireless networks has many applications, including enhanced network performance. In this work we investigate the experimental use of “particle filter”...
— We introduce a new method for stereo visual SLAM (simultaneous localization and mapping) that works in unstructured, outdoor environments. Unlike other gridbased SLAM algorithm...
Tim K. Marks, Andrew Howard, Max Bajracharya, Garr...