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## 1. Overview
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This project is a feasibility study of Visual SLAM for terrain reconstruction on an unmanned aerial vehicle. The goal is to use an existing SLAM algorithm to create a 3D map of an unknown environment by a quadrocopter in remote-controlled or autonomous flight. Optimally the algorithm will run on the vehicle itself, but if that is not practical a remote machine will be used.
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This project is a feasibility study of Visual SLAM for terrain reconstruction on an unmanned aerial vehicle. The goal is to use an existing SLAM algorithm to create a 3D map of an unknown environment by a quadcopter in remote-controlled or autonomous flight. Optimally the algorithm will run on the vehicle itself, but if that is not practical a remote machine will be used.
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### Motivation
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The main motivation behind this project is the approach by two Innsbrucker companys: Laserdata and Grid-IT. They are using LiDAR devices mounted on UAVs to build comprehensive geographic information maps. But the resulting point clouds contain errors due to unstable flight. The integrated IMUs are not fast/accurate enough to compensate for the drift. They are now searching for methods to complement their existing technique.
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A Raspberry Pi and a camera will be mounted to the platform. The Raspberry Pi will be responsible for transmitting a video stream to a remote machine which then processes the data.
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### 5.2. Visual SLAM Algorithm
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TBA
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Best possible pose estimation using only a monocular camera. Different algorithm are to be evaluated and most suitable algorithm will be chosen.
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### 5.3. Sensor Fusion (optional)
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Fusion of Visual SLAM, IMU and possible other sensors to provide a more accurate pose estimation.
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### 5.3. Autonomous exploration
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### 5.4. Autonomous exploration
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TBA
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## 6. Change log
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