A stochastic map for uncertain spatial relationships
Proceedings of the 4th international symposium on Robotics Research
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Shape registration using optimization for mobile robot navigation
Shape registration using optimization for mobile robot navigation
A Framework for Uncertainty and Validation of 3-D RegistrationMethods Based on Points and Frames
International Journal of Computer Vision
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans
Journal of Intelligent and Robotic Systems
Markov Localization using Correlation
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Simultaneous localization, mapping and moving object tracking
Simultaneous localization, mapping and moving object tracking
Appearance-Based SLAM for Mobile Robots
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
Appearance-Based SLAM for Mobile Robots
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
LSH-RANSAC: an incremental scheme for scalable localization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Learning to detect loop closure from range data
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Trajectory-oriented EKF-SLAM using the fourier-mellin transform applied to microwave radar images
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Loop exploration for slam with fusion of advanced sonar features and laser polar scan matching
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Stereo vision local map alignment for robot environment mapping
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Mapping and Localization for Mobile Robots through Environment Appearance Update
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Learning to close loops from range data
International Journal of Robotics Research
Virtual 3D City Model for Navigation in Urban Areas
Journal of Intelligent and Robotic Systems
Journal of Intelligent and Robotic Systems
Scan matching SLAM in underwater environments
Autonomous Robots
Hi-index | 0.00 |
This paper presents Scan-SLAM, a new generalization of simultaneous localization and mapping (SLAM). SLAM implementations based on extended Kalman filter (EKF) data fusion have traditionally relied on simple geometric models for defining landmarks. This limits EKF-SLAM to environments suited to such models and tends to discard much potentially useful data. The approach presented in this paper is a marriage of EKF-SLAM and scan correlation. Landmarks are no longer defined by analytical models; instead they are defined by templates composed of raw sensed data. These templates can be augmented as more data become available so that the landmark definition improves with time. A new generic observation model is derived that is generated by scan correlation, and this permits stochastic location estimation for landmarks with arbitrary shape within the Kalman filter framework. The statistical advantages of an EKF representation are augmented with the general applicability of scan matching. Scan matching also serves to enhance data association reliability by providing a shape metric for landmark disambiguation. Experimental results in an outdoor environment are presented which validate the algorithm.