Least-Squares Fitting of Two 3-D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Control of a Quadrotor Helicopter Using Dual Camera Visual Feedback
International Journal of Robotics Research
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance
International Journal of Robotics Research
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Vision-based guidance and control of a hovering vehicle in unknown, GPS-denied environments
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
BRIEF: binary robust independent elementary features
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Combining Stereo Vision and Inertial Navigation System for a Quad-Rotor UAV
Journal of Intelligent and Robotic Systems
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Small Unmanned Aircraft: Theory and Practice
Small Unmanned Aircraft: Theory and Practice
Efficient estimation for autonomous multi-rotor helicopters operating in unknown, indoor environments
Hi-index | 0.00 |
GPS-denied aerial flight is a challenging research problem and requires knowledge of complex elements from several distinct disciplines. Additionally, aerial vehicles can present challenging constraints such as stringent payload limits and fast vehicle dynamics. In this paper we propose a new architecture to simplify some of the challenges that constrain GPS-denied aerial flight. At the core, the approach combines visual graph-SLAM with a multiplicative extended Kalman filter. More importantly, for the front end we depart from the common practice of estimating global states and instead keep the position and yaw states of the MEKF relative to the current node in the map. This relative navigation approach provides simple application of sensor measurement updates, intuitive definition of map edges and covariances, and the flexibility of using a globally consistent map when desired. We verify the approach with hardware flight-test results.