Weelie’s Status Report for 2/17/2024

What did I do last week?

Since we decided to use UWB instead of WIFI to calculate distance, I looked more into UWB32 Pro, and how it could combine with IMU to provide more precise localization technique. I looked more into the algorithm for the fusion of UWB and IMU. Here are some of the papers I found:

https://iopscience.iop.org/article/10.1088/1742-6596/2369/1/012092

https://ieeexplore.ieee.org/document/8483323

https://www.mdpi.com/1424-8220/23/13/5918

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422251/

https://link.springer.com/chapter/10.1007/978-3-031-34776-4_4

I also looked into how to setup UWB devices based on the following tutorial.

My process is good based on the schedule.

What will I do next week?

Since this week we have already acquired the UWB development kit, I will work on setting the UWB devices up and implementing the localization algorithms.

Ifeanyi’s Status Report for 02/17/2024

This week I did extensive research into optical localization algorithms to consider as an alternative to wireless localization methods. I learned about SIFT, SURF, ORB, and Optical Flow as approaches to tracking the position and orientation of a camera in space from its video feed. I was able to put together such a working demo, placing 3 imaginary points in space that stayed in place in the world as the camera moved. Ultimately, we decided to continue on the path of the Wi-Fi and Ultrawideband-based methods, with a possible use of optical methods as a fallback or for sensor fusion.

My progress is currently ahead of schedule, as I will be working on the hardware of the user’s tag device, the major component of which turned out to  be in the department inventory. So that saved a lot of time against ordering it online and having to wait for it.

In the coming week, I plan to setup the hardware for the user tag and learn how to program and interface with the board. This way, when it comes time to implement the signal-based localization algorithms, I will be familiar with both the software and hardware.

Team Status Report for 02/17/2024

The most significant risks that could jeopardize the success of the project are difficulties in programming the DWM1001-DEV boards, as well as UWB being less robust than we initially assumed. The DWM1001 development boards use the nRF52832 microcontroller, and programming it with the functionality that we want might be more difficult due to possible lack of support in areas such as maintaining a larger network of devices or accurately calibrating for antenna delays. If these aspects seem to interfere with our project, we can either work on implementing some of the capabilities ourselves or try pivoting to using a different microcontroller with the DWM1001 boards, such as the ATMega328p, which could have more library support. Additionally, UWB could be less robust than initially assumed, providing less accurate readings indoors. The possible contingencies we are thinking of right now are to add more sensor fusion from IMUs, or in the worst case pivoting towards using a different technology altogether.

 

This week we finished flushing out a design of the system using UWB instead of Wi-Fi, and we were able to create an updated block diagram that more precisely reflects our understanding of the design. 

 

Last week we said that we were going to include a new schedule, and this week we spent some time developing it. 

18500 Gantt Chart 2-17

 

Goals for the next week

Put in order forms for all the all the components we want. 

Run initial testing DWM-1001 MDEK boards. Try to find distance between an anchor and a tag using to way ranging time on arrival (TOA) and make sure that it is accurate.

Continue working on setting up the webapp. 

 

Status Report Prompt: A was written by Ifeanyi, B was written by Jeff, and C was written by Weelie. 

 

Part A: With regards to health, safety and welfare, our project relieves anxiety related to being lost in unknown parts of campus. This anxiety can be especially severe when one is alone, as there would be nobody to ask for directions. And even in the presence of others, finding somebody willing to lead you all the way to a class can be hard, and time consuming, much like the alternative solution of wandering the building until the desired room is found by trial and error. In general, our project greatly aids the mental well-being of students by providing convenient access to anywhere they need to go, as well as saving students from the stress of arriving to events late by saving them time in the room-finding process.

 

Part B: One way our project could affect social factors is to help students navigate campus better, which could bolster or provide an incentive for students to explore campus. Some students may often feel stressed when they are tasked with going to a new building, and this device may alleviate some of the negative feelings those students may have. Our mapping software could help students save time looking for classrooms or offices, making their schedules more efficient. 

Our device could lead to privacy concerns for students, as it would consist of placing a tracking device on every student. A bad actor would be able to see the locations of students using the device. It would be important to avoid this from occurring by placing safeguards so that the privacy rights of students are respected. The device could also create dependency of students on the navigational technologies, hindering their abilities to navigate among rooms on campus without it. 

 

Part C: We use 12 different UWB devices for anchors, IMU and esp32 for the tag. The tag itself is not expensive, which may only take 15 dollars. However, combining with UWB devices, since each floor probably needs 12 UWB devices, for a whole building, this could be pretty expensive. For a 3 floor building, the total cost could be over 1,000 dollars. For individual users, the tag itself is easy to buy and for distribution. But for all of the anchors, it’s better for a company or the owner of the building to buy the whole system, and provide services for individual users. Since companies can also charge users for buying their services, depending on different companies, this could save their cost. For individual users, their cost will increase if they need to buy the services from companies, but it should not be as expensive as purchasing a single anchor($33). 

Jeff’s Status Report for 02/17/2024

This week I spent time researching how exactly UWB works, especially focusing on how most devices use it for calculating distances using TDOA and TOA. My findings concluded we would most likely be using TOA with Two Way Ranging to find distances.

https://link.springer.com/article/10.1007/s11277-017-4734-x

I also looked into how much it would cost to develop our own UWB tags using a DWM1000 board with an ATMega328p microcontroller.  Unfortunately or not, it appears it would be cheaper to use the preexisting DWM1001 development boards, as they are $25 apiece as opposed to at least $26.5.

I also briefly setup a Django webserver for the web application. Finally, I worked on several slides of the design presentation and created several figures for it.

My progress is overall on track for what I would have liked to accomplish this week.

Next week I will be presenting the Design presentation. Then, I will work on developing the backend of the Django webapp to include all of the models we would need for the project. I would also work on some front end templates to include a mobile-friendly version of a map.

Ifeanyi’s Status Report for 02/10/2024

This week I reviewed the questions that were raised when I presented the project. I researched solutions to the problems of non-radial Wi-Fi signals, potentially easier solutions to localization involving IMUs, as well as what it would take to make the idea work with CMU’s existing wireless access points, rather than us having to design our own. After meeting as a team, and looking at certain logistical and price challenges associated with us using special WIFI access points, I raised the suggestion of using optical tracking, where a video stream coming in from a camera could be used to estimate both the position and orientation of the user. As we were not yet sure of the feasibility of this as a technical solution, I have since researched a few longstanding approaches in the field of optical localization.

https://x-io.co.uk/oscillatory-motion-tracking-with-x-imu/

https://arxiv.org/pdf/2211.11988.pdf

My progress is currently on schedule as I am still helping design the project and finalize what parts to order.

Next week I plan to make a small demo of optical localization to practically explore its feasibility with regards to the use case and target customer.

Team Status Report for 02/10/2024

This week we spent time researching the various technologies and algorithms that could be useful in indoor localization and navigation. Overall, our findings reveal that high localization accuracy indoors might be able to be achieved in reality.

The project is still in an early planning phase, hence, we have chosen to pivot from using Wi-Fi to using UWB due to the hopes of being able to achieve higher accuracy and precision in localization. Finally, we also discussed the complexity of the project and are possibly investigating methods that could expand the scope of the project. For example, other localization techniques, such as doing computer vision on the surroundings of the user, could also accurately localize the user. Effecting such sensor fusion of UWB and CV could improve the accuracy of localization.

We are still in the midst of discussing how best to go forward and will create an updated schedule for next week.

Jeff’s Status Report for 02/10/2024

This week I researched the various technologies that are typically used in indoor localization. I compared using Wi-Fi, Bluetooth, and UWB, finding that typically UWB has the highest accuracy, most resistance to interference, as well as having decent range, with the cons being that the devices are newer, hence the device prices are relatively higher. Next, I looked into which UWB devices would be a good fit with our project. The Qorvo DW1000 chip seems like the best UWB transceiver option, and there are a few developer boards that incorporate it, such as the ESP32 UWB.

A summary: Design Review_ What is the best indoor localization technology_

My progress is in line with our Gantt chart.

Next week I will be working on the Design presentation, as well as continuing to do research and discussing further with the team of how the project will end up unfolding. I would like to start working on the Django website by setting it up.

Weelie’s Status Report for 02/10/2024

On the proposal, we got a lot of suggestions for our projects. For indoor positioning and navigation, there are a lot of possible solutions and combination of devices. To figure out what combinations fit us most, I researched on the algorithms that can achieve our goal. I mainly read through algorithm papers to prepare for our final decision. I will attach the interesting ones for us.

https://ieeexplore.ieee.org/document/7275538

https://ieeexplore.ieee.org/document/8559721

https://ieeexplore.ieee.org/document/7346754

https://ieeexplore.ieee.org/document/9874146

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610672/

https://link.springer.com/chapter/10.1007/978-3-031-26712-3_6

https://ieeexplore.ieee.org/document/9708854

https://www.mdpi.com/1424-8220/21/4/1114

https://wiki.makerfabs.com/ESP32_UWB.html

Based on the gantt chart, this week is on schedule for me. Since we havn’t get our devices yet, I couldn’t do more than rearch on the algorithms.

Now we have decided to use ESP32_UWB or Computer Vision approach for our projects. For the next week, after we bought all the widgets, I will work on set up these things. If we couldn’t get these devices, I will work on doing more research on UWB and CV indoor navigation.