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Practical Map Building Method for Service Robot Using EKF Localization Based on Statistical Distribution of Noise Parameters
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- Authors
- Yu Cheol Lee, Won Pil Yu
- Issue Date
- 2009-09
- Citation
- International Symposium on Robot and Human Interactive Communication (RO-MAN) 2009, pp.478-483
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Project Code
- 09MC3200, Hybrid u-Robot Service System Technology Development for u-City, Wonpil Yu
- Abstract
- This paper presents a method to build the large-scale indoor maps by means of extended Kalman filter (EKF) localization which explores the statistical distribution of noise parameters. As typical method in many robot localization applications, EKF localization has shown considerable success history to locate the position of the robot. However, EKF has also lack which can degrade its performance, especially in the real environment due to incompleteness, incorrectness and imprecision of noise parameters. Moreover, although many kinds of sensors are used for EKF localization, it is still difficult to generate an accurate map because of noise parameters. The fundamental solution of this problem should be addressed to the utilization of adequate noise parameters setting. We have developed a new technique for searching the optimal noise parameters setting of EKF localization using a statistical distribution. The experiments carried out on mobile robot have been performed to build accurate maps by using EKF localization relied on statistical distribution of noise parameters. The mapping results show that the method based on statistical distribution can be useful for practical application. © 2009 IEEE.
- KSP Keywords
- Extended kalman fiLTEr, Fundamental solution, Indoor map, Map building, Mobile robots, Optimal noise parameters, Parameters setting, Real environment, Robot localization, Service robots, large-scale