ICRA'09 Paper Abstract


Paper FrB3.4

Bryson, Mitch (University of Sydney), Johnson-Roberson, Matthew (Australian Centre for Field Robotics), Sukkarieh, Salah (University of Sydney)

Airborne Smoothing and Mapping Using Vision and Inertial Sensors

Scheduled for presentation during the Regular Sessions "Mapping - II" (FrB3), Friday, May 15, 2009, 11:30−11:50, Room: 401

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 24, 2022

Keywords Mapping, Aerial Robotics, Visual Navigation


This paper presents a framework for integrating sensor information from an Inertial Measuring Unit (IMU), Global Positioning System (GPS) receiver and monocular vision camera mounted to a low-flying Unmanned Aerial Vehicle (UAV) for building large-scale terrain reconstructions. Our method seeks to integrate all of the sensor information using a statistically optimal non-linear least squares smoothing algorithm to estimate vehicle poses simultaneously to a dense point feature map of the terrain. A visualisation of the terrain structure is then created by building a textured mesh-surface from the estimated point features. The resulting terrain reconstruction can be used for a range of environmental monitoring missions such as invasive plant detection and biomass mapping.



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