Curves and surfaces in computer aided geometric design
Curves and surfaces in computer aided geometric design
An introduction to NURBS: with historical perspective
An introduction to NURBS: with historical perspective
A Discussion of Simultaneous Localization and Mapping
Autonomous Robots
Extending the limits of feature-based SLAM with B-splines
IEEE Transactions on Robotics
Convergence and Consistency Analysis for Extended Kalman Filter Based SLAM
IEEE Transactions on Robotics
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This paper describes a simultaneous planning localization and mapping methodology, where the robot explores the environment efficiently and also considers the requisites of the SLAM (Simultaneous Localization And Mapping) algorithm. The method is based on the randomized incremental generation of a data structure called Sensor-based Random Tree, which represents a roadmap of the explored area with an associated safe region. A continuous localization procedure based on B-Splines features of the safe region is integrated in the scheme. The approach is evaluated for accuracy and consistency using computer simulations and for effectiveness using experimental data from different real environments.