Adaptive complementary filtering algorithm for mobile robot localization

Armando Alves NetoDouglas Guimarães MacharetVíctor Costa da Silva CamposMario Fernando Montenegro Campos

As a mobile robot navigates through an indoor environment, the condition of the floor is of low (or no) relevance toits decisions. In an outdoor environment, however, terrain characteristics play a major role on the robot's motion. Without anadequate assessment of terrain conditions and irregularities, the robot will be prone to major failures, since the environmentconditions may greatly vary. As such, it may assume any orientation about the three axes of its reference frame, which leads toa full six degrees of freedom configuration. The added three degrees of freedom have a major bearing on position and velocityestimation due to higher time complexity of classical techniques such as Kalman filters and particle filters. This article presentsan algorithm for localization of mobile robots based on the complementary filtering technique to estimate the localizationand orientation, through the fusion of data from IMU, GPS and compass. The main advantages are the low complexity ofimplementation and the high quality of the results for the case of navigation in outdoor environments (uneven terrain). Theresults obtained through this system are compared positively with those obtained using more complex and time consumingclassic techniques.

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