Title :
Multiscan-based map optimizer for RFID map-building with low-accuracy measurements
Author_Institution :
Kyushu Univ., Japan
Abstract :
This paper studies the problem of mobile robot map-building using a low-accuracy RFID sensor. In recent years, there has been increasing number of mobile robot systems using RFID landmarks. A difficulty arises from the fact that the characteristics of RFID sensors are quite electrically-sensitive, which makes the map-building process difficult to converge. Our solution is to integrate a robust multiscan-based online sensor model within an SGD framework of map-optimization, which significantly improves the convergence and accuracy.
Keywords :
gradient methods; intelligent robots; mobile robots; optimisation; radiofrequency identification; robust control; sensor fusion; stochastic processes; unsupervised learning; RFID sensor; data association; low-accuracy measurement; mobile robot map-building; multiscan-based map optimizer; optimization; robust control; stochastic gradient descent framework; unsupervised learning; Convergence; Detectors; Educational technology; Mobile robots; Particle filters; Particle measurements; Radiofrequency identification; Robot sensing systems; Robustness; Sensor phenomena and characterization;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761035