On your TOF Sensor page, you have two demo videos. I'm interested in reproducing that result.
What SLAM algorithm are you using? (I have used a few different SLAM algorithm in the past, but those were processor intensive, and I suspect I'll need something a little more lightweight to run on the VOXL.)
From the videos, it looks like you are using ROS and rviz. Is that correct? If so, I presume you are using mpa_to_ros to publish the TOF data on a topic in ROS...and then use the SLAM algorithm to ingest that data and produce the map in the videos. Is that correct? Are there any other sensors' data that the SLAM algortihm is ingesting (e.g., IMU)?
Our current SLAM project that we've been working on for the past few months uses ETH Zurich's voxblox algorithm. Our demos for this have been using ros for visualization (but with all the actual mapping running on-board), but we are nearing (next month or two) an initial ros-free release that will use voxl-portal for visualization in a web browser. This mapping system uses voxl-qvio-server for localization (with optional help from voxl-vision-px4 if using apriltags/other fiducial markers) and the tof sensor for actual mapping. Additionally, we have done a small amount of mapping with depth from stereo cameras, but as this has generally been designed as an indoor tool (where the tof sensor thrives) we primarily use tof.
@Alex-Gardner Sounds good. We'll look into it. Thanks!