What are the most significant risks that could jeopardize the success of the project? How are these risks being managed? What contingency plans are ready?
The major risks remain the same as previous weeks: the weight of the device, the PCB connection between Jetson and peripherals, the identification of partial frames of objects, and the OR model version.
Another risk is the accuracy of the DE feature. Because it uses a reference image and known size to estimate the distance of an identified object, if the model misidentifies a certain obstacle, it will produce an incorrect distance and lead to an incorrect nearest distance. Then, the system will output a wrong obstacle to the user. This risk will be mitigated by raising the accuracy of the model with a better training method. Few adjustments with epochs and image resolutions will be made to output the greatest precision.
Were any changes made to the existing design of the system (requirements, block diagram, system spec, etc)? Why was this change necessary, what costs does the change incur, and how will these costs be mitigated going forward?
The only potential change that can be made to the design of the system is that if the pre-trained model identifies a batch of test objects better than the trained model with our own dataset, the pre-trained Yolov9-e.pt will be used for the weight of the OR model.
Provide an updated schedule if changes have occurred.
Since we are still waiting for our order of transistors for the PCB, and have not yet ordered the audio converter, the hardware development schedule has been pushed back slightly:
Another update to the schedule is that the integration of the DE feature has been pushed back for another week due to its unexpected complexity and learning curve.
