Title :
A relative map filter using linear invariant measurements
Author :
Sun, Rongchuan ; Ma, Shugen ; Li, Bin ; Wang, Yuechao
Author_Institution :
Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang
Abstract :
In this paper, a new relative map algorithm is presented. The algorithm extracts linear invariant measurements from original laser scan data and uses an information filter to update the absolute map. The algorithm avoids the procedure of building the relative map, which is a basic procedure in other relative map algorithms. This improvement makes the new algorithm avoid the problem of inconsistency, which is inherent in other relative map algorithms. The requirements of computation and memory of this algorithm are linear over the size of the map, which are the same as RMGF. However, our algorithm has a simpler structure and performs faster. Experimental result on a simulated map demonstrates the advantages of our algorithm.
Keywords :
Kalman filters; SLAM (robots); nonlinear filters; SLAM robot; extended Kalman filter; information filter; laser scan data; linear invariant measurement; relative map filter; Biomimetics; Convergence; Information filtering; Information filters; Laboratories; Nonlinear filters; Robot sensing systems; Robotics and automation; Simultaneous localization and mapping; Size measurement; AMF; Consistency; Linear Invariant Measurement; RMF; Relative Map; SLAM;
Conference_Titel :
Robotics and Biomimetics, 2007. ROBIO 2007. IEEE International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-1761-2
Electronic_ISBN :
978-1-4244-1758-2
DOI :
10.1109/ROBIO.2007.4522410