Probabilistic Fuzzy System for Uncertain Localization and Map Building of Mobile Robots

Precise localization and map building for mobile robots in unknown environments are fundamental and crucial issues in robotics. In this paper, to deal with unavoidable uncertainties in perception and actuation, a probabilistic fuzzy approach is applied to dead-reckoning-based localization and range measurement, respectively. Then, they are adopted to constitute a systematic map-building method. Dead reckoning in autonomous localization allows a mobile robot to determine its present position from a known past position. Unfortunately, pure dead reckoning methods are prone to accumulated errors that grow without bound over time. In addition, various unpredictable errors in distance data are also found in range measurement during exploration and map building. It is analyzed that all these kinds of errors caused by various disturbances can be classified into nonstochastic and stochastic uncertainties. A probabilistic fuzzy system is designed to reduce both of these uncertainties for more precise localization and map building. The experimental results demonstrate the success and robustness of the proposed method for more precise and reliable mobile-robot localization and map building with various unexpected disturbances.