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Paper WeA205.5

Lee, Gim Hee (ETH Zurich), Fraundorfer, Friedrich (ETH Zurich), Pollefeys, Marc (ETH Zurich)

MAV Visual SLAM with Plane Constraint

Scheduled for presentation during the Regular Sessions "SLAM II" (WeA205), Wednesday, May 11, 2011, 11:05−11:20, Room 3G

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on December 8, 2019

Keywords SLAM, Computer Vision for Robotics and Automation, Aerial Robotics

Abstract

Bundle adjustment (BA) which produces highly accurate results for visual Simultaneous Localization and Mapping (SLAM) could not be used for Micro-Aerial Vehicles (MAVs) with limited processing power because of its O(N3) complexity. We observed that a consistent ground plane often exists for MAVs flying in both the indoor and outdoor urban environments. Therefore, in this paper, we propose a visual SLAM algorithm that make use of the plane constraint to reduce the complexity of BA. The reduction of complexity is achieved by refining only the current camera pose and most recent map points with BA that minimizes the reprojection errors and perpendicular distances between the most recent map points and the best fit plane with all the pre-existing map points. As a result, our algorithm is approximately constant time since the number of current camera pose and most recent map points remain approximately constant. In addition, the minimization of the perpendicular distances between the plane and map points would enforce consistency between the reconstructed map points and the actual ground plane.

 

 

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