Title :
A simultaneous localization and map building algorithm based on sequential Monte Carlo method
Author :
Kurt, Zeyneb ; Yavuz, Szrma
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Yildiz Teknik Univ., Istanbul
Abstract :
In this study, a statistical estimation algorithm is developed to solve the SLAM (simultaneous localization and map building) problem, by using a robot equipped with only simple and cheap sensors. During map building and simultaneous localization, the robot can sense its environment with infrared sensors and can decide the path to follow by using the developed SLAM algorithm. The most frequent problems in SLAM algorithms are sensorspsila noise and odometry errors. To solve this problem, sequential Monte Carlo (SMC) method which is a well known particle filter application is used and promising results were obtained for the SLAM problem.
Keywords :
Monte Carlo methods; SLAM (robots); image sensors; mobile robots; sequential estimation; SLAM problem; infrared sensors; particle filter; robot sensor; sequential Monte Carlo method; simultaneous localization and map building algorithm; statistical estimation algorithm; Infrared sensors; Kalman filters; Monte Carlo methods; Particle filters; Radio frequency; Robot sensing systems; Simultaneous localization and mapping; Sliding mode control; Sonar; Working environment noise;
Conference_Titel :
Signal Processing, Communication and Applications Conference, 2008. SIU 2008. IEEE 16th
Conference_Location :
Aydin
Print_ISBN :
978-1-4244-1998-2
Electronic_ISBN :
978-1-4244-1999-9
DOI :
10.1109/SIU.2008.4632712
