This week, we finished integrating and testing. With the UWB, I was able to overlay the UWB localization with the occupancy matrix and its given dimensions. This involved creating an API to localize the user, calibrating the anchors by scaling the dimensions and distances to map the real-world coordinates to the image coordinates, and then using these scales/offsets to pin our user onto the occupancy grid.
I also wrote the code to collect data from the magnetometer. This combined with the UWB is enough to get the location of our user. Then, as a group we integrated all these metrics with the entire system, so that the data pipeline is complete and the Pi sends/receives the necessary data from the processing unit.
Next week, I want to tune the system for our demo location. This will probably involve recalibrating the anchors and making sure the room environment won’t cause unexpected issues.
One skill was using new libraries such as scipy for UWB triangulation or matplotlib for visualization. Learning methods included watching videos, using AI tools, and reading forums such as Stackoverflow. Another skill was interfacing the hardware, which involved reading datasheets, finding similar projects online, etc.