Constraint propagation with interval labels
Artificial Intelligence
Estimation theory for nonlinear models and set membership uncertainty
Automatica (Journal of IFAC)
Revising hull and box consistency
Proceedings of the 1999 international conference on Logic programming
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Brief paper: Robust set-membership state estimation; application to underwater robotics
Automatica (Journal of IFAC)
Real-time Bounded-error State Estimation for Vehicle Tracking
International Journal of Robotics Research
Consistent outdoor vehicle localization by bounded-error state estimation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Constraints propagation techniques on intervals for a guaranteed localization using redundant data
Automatica (Journal of IFAC)
| Hi-index | 0.00 |
The paper presents an approach for localizing a mobile robot in a feature-based map using a 2D laser rangefinder and wheel odometry. As the presented approach is based on set membership methods, the localization result consists of sets instead of points, and is guaranteed to contain the true robot position as long as the sensor errors are absolutely bounded and a maximum number of measurement outliers can be assumed. It is able to cope with a multitude of measurement per time step compared to previous approaches. Moreover, the approach is capable of identifying and marking outlier points in the laser range scan. A real world experiment, where a mobile robot is moving in a structured indoor environment with previously unmapped static and dynamic obstacles shows the feasibility of the approach. It is shown that the true robot pose is always included in the solution set, which is computed in real time.