Data Association for Mobile Robot Navigation: A Graph Theoretic Approach

Data association is the process of relating features observed in the environment to features viewed previously or to features in a map. Correct feature association is essential for mobile robot navigation as it allows the robot to determine its location relative to the features it observes. This paper presents a graph theoretic method that is applicable to data association problems where the features are observed via a batch process. Batch observations (e.g., scanning laser, radar, video) detect a set of features simultaneously or with sufficiently small temporal difference that, with motion compensation, the features can be represented with precise relative coordinates. This data association method is described in the context of two possible navigation applications: metric map building with simultaneous localisation, and topological map based localisation. Experimental results are presented using an indoor mobile robot with a 2D scanning laser sensor. Given two scans from different u...

• Type: Conference
• Year: 2000
• Where: ICRA
• Authors: Tim Bailey, Eduardo Mario Nebot, Julio Rosenblatt, Hugh F. Durrant-Whyte
• Keywords: Data Association, ICRA 2000, Mobile Robot, Robotics, Scanning Laser