Hi there FlytBase community, we’re building a drone and using a mmWave sensor as a radar to capture the environment as a point cloud, and use it to help the drone in object avoidance. It’s a 2D sensor, but we’ve mounted it on a swivelling servo to capture a 3D point cloud. We can publish this on ROS and visualise it. The points are captured in Cartesian coordinates. We want to use this
However, we are a bit stuck as to how we can proceed. Ideally, all we want to do is avoid collisions with objects based on our point cloud scan, and so we expect to do some path-planning by generating some velocity vectors, and feeding it into our PX4 flight control board. After some reading, I believe we will need to first figure out a way to do a ‘tf-transform’ of our static map as the drone moves around, and then figure out how to output values (velocity vectors) to the drone. The part where we are stuck, is what kind of navigation algorithms can we use in the first place? Do we require SLAM in 3D for this? We don’t really have a direction here.
We are using a PX4. Do you know how one might be able to achieve this with FlytOS? Are there any pre-built APIs or functions we can use that can help us? Thank you! I have attached a photo of our point cloud, visualised on ROS’ RVIZ.
Hoping if anyone has had any experience in this and could offer or lend some insight or advice.