ROS already comes with a fantastic built-in visualization tool called rviz, so why would you want to use anything else? At Southwest Research Institute, Jerry Towler explains how they’ve created a new visualization tool called Mapviz that’s specifically designed for the kind of large-scale outdoor environments necessary for autonomous vehicle development. Specifically, Mapviz is able to integrate all of the sensor data that you need on top of a variety of two-dimensional maps, such as road maps or satellite imagery.
As an autonomous vehicle visualization tool, Mapviz works just like you’d expect that it would, which Jerry demonstrated with several demos at ROSCon. Mapviz shows you a top-down view of where your vehicle is, and tracks it across a basemap that seamlessly pulls image tiles at multiple resolutions from a wide variety of local or networked map servers, including Open MapQuest and Bing Maps. Mapviz is, of course, very plugin-friendly. You can add things like stereo disparity feeds, GPS fixes, odometry, grids, pathing data, image overlays, projected laser scans, markers (including textured markers) from most sensor types, and more. It can’t really handle three dimensional data (although it’ll do two-and-a-half dimensions via color gradients), but for interactive tracking of your vehicle’s navigation and path planning behavior, Mapviz should offer most of what you need.
For a variety of non-technical reasons, SwRI hasn’t been able to release all of its tools and plugins as open source quite yet, but they’re working on getting approval as fast as they can. They’re also in the process of developing even more enhancements for Mapviz, and you can keep up to date with the latest version of the software on GitHub.
Next up: Matt Vollrath & Wojciech Ziniewicz (End Point)