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Team Status Report for 2/7/26

Currently, the most significant risks we see are the ordering of parts successfully, dealing with delivery time and ensuring that they all work for are desired use case requirements. We would like to finish our research to determine our Bill of Materials so that we can maximize our time we have available with building, testing, and integrating our project. We tried to build slack time into our current schedule to deal with issues as they come up but also creating a list of backup parts/design solutions should ensure that we are able to meet our MVP goals.

From our research, we also definitely noticed a pattern that for the testing of drone related projects, damage occurring to the physical structure or even damage to the hardware of the project is a concern. As we move further into the project we will need to think carefully about our testing processes to minimize the risk of these damages occurring such that we aren’t being constantly set back.

There are no proposed changes as of this point in our research although that could change as we finish up the research process in the coming week. If we find that certain parts of our design are unrealistic due to part availability, price, or other concerns we will definitely update our design.

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Bonnie’s Status Report for 2/7/26

This week I focused on background research to validate the feasibility of the proposed sensing, computation, and communication approach for the Shade.ai system. I reviewed the computer vision software stack to confirm that an OpenCV-based pipeline using lightweight detection models with higher-rate tracking can meet our response-time and accuracy requirements for single-user following. I also researched hardware requirements for CV, including camera modules, CSI connectors, and mounting considerations, confirming that CSI-based cameras are the most suitable option due to their low latency and power efficiency. Additionally, I explored app-level communication options and compared Wi-Fi and Bluetooth for user control, noting that Wi-Fi is better suited for real-time control and status updates.

In parallel, I investigated drone hardware considerations and obstacle avoidance requirements. This included reviewing payload, power, and endurance constraints that support a lightweight, low-power companion computer approach. I also compared 2D versus 3D obstacle sensing and determined that simple ToF-based obstacle detection is sufficient for our low-speed, low-obstacle operating environment, avoiding the complexity and cost of full 3D mapping. Overall, this research supports a Raspberry Pi–based MVP design with lightweight sensors that balances performance, safety, and system simplicity.

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Nicholas’ Status Report for 2/7/26

I met with my team members this week to discuss that remaining research that needed to be done. I was tasked with figuring out what parts were needed for the UWB Tracking, 2D/3D Obstacle Avoidance, and the micro controllers we would need on the drone. Since it was the most new to me I focused most of my time looking into the requirements for generating 3D coordinates using UWB base stations. My initial assumption that it would be possible using trilateration although after further research the amount of base stations required to get accurate data for this may be prohibitive for our project. After we meet again this Sunday, we plan to put in an almost complete order of all the parts we can.

I am currently up to schedule with what I have been assigned so far so there are no worries there currently. After we meek this weekend again we plan to put in order in for parts some of which should arrive this coming week. As soon as I have parts relevant to my assigned tasks I can begin work but if I’m not able to get those parts I will either continue to research any additional parts we didn’t make in the initial order and begin preliminary design in CAD software of the drone assembly.