Journal of Field Robotics · 2011 · 17 citations · 9 references
EngineeringAutonomous SystemsRobotics Engineering3D ModelingMobile RoboticsRobotics3D ReconstructionAutonomous ExplorationEnvironment RepresentationMappingPoint Cloud Processing3D MappingExpected Information GainExplorationExploration In Unknown EnvironmentsInformation GainInformation-gain MaximizationRobotic Space ExplorationTrajectory Estimation
Abstract In this paper, a method for robotic exploration oriented to the automatic three‐dimensional (3D) reconstruction of outdoor scenes is presented. The proposed algorithm focuses on optimizing the exploration process by maximizing map quality, while reducing the number of scans required to create a good‐quality 3D model of the environment. This is done by using expected information gain, expected model quality, and trajectory cost estimation as criteria for view planning. The method has been tested with an all‐terrain mobile robot, which is also described in the paper. This robot is equipped with a SICK LMS 111 laser scanner attached to a spinning turret, which performs quick and complete all‐around scans. Different experiments of autonomous 3D exploration show the suitable performance of the proposed exploration algorithm. © 2011 Wiley Periodicals, Inc.
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6D SLAM—3D mapping outdoor environments
Andreas Nüchter, Kai Lingemann, Joachim Hertzberg et al. · Journal of Field Robotics · 2007 · 446 citations · Full text