퍼지추론과 상호작용 다중 모델을 이용한 이동로봇의 위치 인식 기법 = Fuzzy-Logie-Assisted Interacting Multiple Model (FLAIMM) for Mobile Robot Localization

다국어 초록 (Multilingual Abstract)

Improvement of dead reckoning accuracy is essential for robotic localization system and has been intensively studied. However, existing solutions cannot provide accurate positioning when a robot suffers from changing dynamics such as wheel slip. In this paper, we propose a fuzzy-logie-assisted interacting multiple model (FLAIMM) framework to detect and compensate for wheel slip. Firstly, two different types of extended Kalman filter (EKF) are designed to consider both no-slip and slip dynamics of mobile robots. Then a fuzzy inference system (FIS) model for slip estimation is constructed using adaptive neuro-fuzzy inference system (ANFIS). The trained model is utilized along with the two EKFs in the FLAIMM framework. The approach is evaluated using real data sets acquired with a robot driven in an indoor environment. The experimental results show that our approach improves position accuracy and works better in slip compensation compared to the conventional approach.

목차 (Table of Contents)

• Abstract
• Ⅰ. 서론
• Ⅱ. 본론
• Ⅲ. 실험
• Ⅵ. 결론
• 참고문헌