A Discussion of Simultaneous Localization and Mapping
Autonomous Robots
Vision-Based SLAM in Real-Time
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Learning gas distribution models using sparse Gaussian process mixtures
Autonomous Robots
Metric-topological maps from laser scans adjusted with incremental tree network optimizer
Robotics and Autonomous Systems
On measuring the accuracy of SLAM algorithms
Autonomous Robots
Nonlinear constraint network optimization for efficient map learning
IEEE Transactions on Intelligent Transportation Systems
Real-time hierarchical outdoor SLAM based on stereovision and GPS fusion
IEEE Transactions on Intelligent Transportation Systems
Real-time hierarchical GPS aided visual SLAM on urban environments
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
CI-graph: an efficient approach for large scale SLAM
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Automatically and efficiently inferring the hierarchical structure of visual maps
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Finding good cycle constraints for large scale multi-robot SLAM
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
CI-graph: an efficient approach for large scale SLAM
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Consistent cooperative localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
SLAM in O(log n) with the combined Kalman - information filter
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A parallel maximum likelihood algorithm for robot mapping
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Event-driven loop closure in multi-robot mapping
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
SLAM in O(logn) with the Combined Kalman-Information Filter
Robotics and Autonomous Systems
Power-SLAM: a linear-complexity, anytime algorithm for SLAM
International Journal of Robotics Research
Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain
Robotics and Autonomous Systems
A probabilistic framework for learning kinematic models of articulated objects
Journal of Artificial Intelligence Research
Linear-time robot localization and pose tracking using matching signatures
Robotics and Autonomous Systems
iSAM2: Incremental smoothing and mapping using the Bayes tree
International Journal of Robotics Research
Laser and Radar Based Robotic Perception
Foundations and Trends in Robotics
A model for WLAN signal attenuation of the human body
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Bubble space and place representation in topological maps
International Journal of Robotics Research
Hi-index | 0.00 |
This article presents a very efficient SLAM algorithm that works by hierarchically dividing a map into local regions and subregions. At each level of the hierarchy each region stores a matrix representing some of the landmarks contained in this region. To keep those matrices small, only those landmarks are represented that are observable from outside the region.A measurement is integrated into a local subregion using O(k2) computation time for k landmarks in a subregion. When the robot moves to a different subregion a full least-square estimate for that region is computed in only O(k3 log n) computation time for n landmarks. A global least square estimate needs O(kn) computation time with a very small constant (12.37 ms for n = 11300).The algorithm is evaluated for map quality, storage space and computation time using simulated and real experiments in an office environment.