MAV Visual SLAM with Plane Constraint
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.
Gim Hee Lee Friedrich Fraundorfer Marc Pollefeys
Computer Vision and Geometry Laboratory,Department of Computer Science,ETH Z¨urich,Switzerland
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
3139-3144
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）