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The RPi 5 has plenty of compute power for all our computer vision.
LTE stream is never fully reliable. We don’t want autonomy to design around it’s functionality and reliability which has been a downfall in the past resulting in systems that do not function. Airside compute is by far the most reliable approach to autonomy.
An LTE stream for video requires extra weight and power to implement in hardware. Increasing assembly time and decreasing flight time and payload capability. An LTE stream for video is significantly more power and effort than an LTE system that is data only for the Pixhawk as a backup for command and control. See https://uwarg-docs.atlassian.net/wiki/spaces/EL/pages/2701197313/RPi+Interface+Rev+C?search_id=a657dcd7-828f-4350-bc55-00ac02a9ccd3&additional_analytics=queryHash---1c222edcb8ab63d7700c11935d113ab058a8a39e4ea6075d3cf2bf51235d3fe4 for reference.
Debugging can still be done via SSHing into the RPi using it’s onboard wifi network when the drone is in proximity of the ground station. This should not be relied on in the intended system due to range limitation of this debugging solution. This can be used during early stage testing of the autonomy system when there are lots of untested pieces of software being operated.
Challenges We’ll Face Regardless
Integrating your software to run in a real system is hard.
Hardware will need to be upgraded as newer superior hardware is released as time progresses.
Hardware compute limitations will be a limiting factor for more complicated machine learning algorithms.