6D SLAM-3D mapping outdoor environments

Autor(en): Nuechter, Andreas
Lingemann, Kai
Hertzberg, Joachim 
Surmann, Hartmut
Stichwörter: MOBILE ROBOT; REGISTRATION; Robotics; SIMULTANEOUS LOCALIZATION
Erscheinungsdatum: 2007
Herausgeber: WILEY
Journal: JOURNAL OF FIELD ROBOTICS
Volumen: 24
Ausgabe: 8-9
Startseite: 699
Seitenende: 722
Zusammenfassung: 
6D SLAM (simultaneous localization and mapping) or 6D concurrent localization and mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y, and z coordinates and the roll, yaw, and pitch angles. Robot motion and localization on natural surfaces, e.g., driving outdoor with a mobile robot, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Iterative Closest Point scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system. A new strategy for fast data association, cached kd-tree search, leads to feasible computing times. With no ground-truth data available for outdoor environments, point relations in maps are compared to numerical relations in uncalibrated aerial images in order to assess the metric validity of the resulting 3D maps. (c) 2007 wiley Periodicals, Inc.
Beschreibung: 
4th IEEE International Workshop on Safety, Security and Rescue Robots/6th Performance Metrics for Intelligent Systems, Nat Inst Stand Tech, Gaithersburg, MD, AUG, 2006
ISSN: 15564959
DOI: 10.1002/rob.20209

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