Robust, scalable Simultaneous Localization and Mapping (SLAM) algorithms support the successful deployment of robots in real-world applications. In many cases these platforms deliver vast amounts of sensor data from large scale, unstructured environments. This data may be difficult to interpret by end-users without further processing and suitable visualization tools. We present the results from robust, automated system for large-scale 3D reconstruction and visualization that takes stereo imagery from an Autonomous Underwater Vehicle (AUV) and SLAM-based vehicle poses to deliver detailed 3D models of the seafloor in the form of textured polygonal meshes.
- Generation and Visualization of Large-scale Three-dimensional Reconstructions from Underwater Robotic Surveys, Journal of Field Robotics, 2010.
- Towards Large Scale Optical and Acoustic Sensor Integration for Visualization, IEEE/OES Oceans - Europe, 2009.
- Large Scale 3D Reconstruction and Visualization of Stereo Surveys, Marine Geological and Biological Habitat Mapping (GeoHab) Video Workshop, 2009.
- Efficient View-Based SLAM Using Visual Loop Closures, IEEE Transactions on Robotics 2008.