Sonar based map building for a mobile robot

This paper describes a mobile robot equipped with a sonar sensor array, Werrimbi, in a guided feature based map building task in an indoor environment. Common indoor landmarks such as planes, corners and edges are located and classified with a multiple transducer sensor array. Accurate odometry information is derived from a pair of narrow unloaded encoder wheels. Discrete sonar observations are incrementally merged into partial planes to produce a realistic representation of environment. Collinearity constraints among features are exploited to enhance state estimation. The map update utilises Julier-Uhlmann Kalman Filter (JUKF) which improves the accuracy of covariance propagation through nonlinear equations and eliminates the need to derive Jacobian matrices. Correlation among map features and robot location are explicitly represented. Partial planes are also used to eliminate phantom targets caused by sonar specular reflection.