Bearing-only Landmark Initialization with Unknown Data Association

Albert Costa, George Kantor, Howie Choset

Abstract: It is essential in many applications that mobile robots localize themselves with respect to an unknown environment. This means that the robot must build a map of its environment and then localize using the map. This process is called simultaneous localization and mapping (SLAM). This paper presents an iterative solution to the landmark initialization problem inherent in a bearing-only implementation of SLAM. No prior knowledge of the environment is required, and furthermore, there are no requirements about having the data association problem solved. Once landmarks are initialized, they are inserted into an extended Kalman Filter (EKF) to solve the SLAM problem. Both indoor and outdoor experiments are presented to validate the method.