Outdoor exploration and SLAM using a compressed filter

Abstract— In this paper we describe the use of automatic exploration for autonomous mapping of outdoor scenes. We describe a real-time SLAM implementation along with an autonomous exploration algorithm. We have implemented SLAM with a compressed extended Kalman filter (CEKF) on an outdoor robot. Our implementation uses walls of buildings as features. The state predictions are made by using a combination of odometry and inertial data. The system was tested on a 200 x 200 m site with 18 buildings on variable terrain. The paper helps explain some of the implementation details of the compressed filter such as, how to organize the map as well as more general issues like, how to include the effects of pitch and roll and efficient feature detection. Keywords— SLAM, simultaneous localization and map building, CEKF, outdoor robotics, autonomous exploration, feature detection, sensor fusion.

• Type: Conference
• Year: 2003
• Where: ICRA
• Authors: John Folkesson, Henrik I. Christensen
• Keywords: Autonomous Exploration, Autonomous Exploration Algorithm, ICRA 2003, Real-time Slam Implementation, Robotics