The most significant risk that can jeopardize the success of this project is the UWB sensors not working as well as we expected. Our software pipeline is decently robust at this point, however, we are completely relying on the UWB sensors embedded on the user’s belt to determine the user’s location and update it on the D* Path Planning algorithm. The frame captured from the phone camera and the frame calculated from the UWB sensors might also have different dimensions, so the movements of the person may not completely align on the occupancy matrix we run path finding on. This misalignment could cause significant drift as the user moves and makes it difficult to guide him to the target.
These risks are being mitigated by having some of our team members look into libraries that could decrease the fish eye effect on the ends of the image. Since we needed wide lens camera to capture the entire frame, warping on the ends is something that we need to work with. Since our UWB sensors most likely would work uniformly throughout, it would probably be easiest to decrease warping from the CV pipeline.
Another risk is the compass orientation we receive and how we are going to integrate that with the D* path finding algorithm. Since these components take some time to arrive, we can currently work on the software stack right now. However, we are looking into drivers and libraries that could run these hardware components.
There are no changes to our schedule. This week, our main milestones were getting some sort of camera to work and send feed to the computer processing the data. We were also able to select a segmentation model that could classify free spaces and obstacles. Our D* Path Planning algorithm is mostly working, and we will focus on integration next week.