This week, I made considerable progress on the central Pi’s motion control and tracking stack. I built the homography-based motor control foundation early so software development could continue before the final pan motor driver arrives. I implemented the initial camera geometry model, environment-driven motor configuration, live Modbus motor control, and the first complete auto-tracking pipeline. I then refined the homography, camera placement, startup pose, and projection behavior to improve real-world tracking performance and better align the UWB pose stream, image-space projection, and motor commands so subject tracking behaves more reliably during live motion. Furthermore, I expanded the system into a practical manual calibration with jog controls, mark-left, mark-right, and mark-center tools, and various other commands. Additionally, I added a seamless manual-to-auto handoff which allows calibration to automation to be quite smooth. This work brings Autocam closer to the next phase of integration, where the second motor can be brought online for full pan-and-truck tracking once the remaining motor controller arrives. On the hardware side, I completed the physical setup of the motor system, including wiring, power, and bringing the core rail-drive hardware online, which enabled extensive live testing throughout the rest of the week. Those tests drove a long series of fixes and refinements across manual calibration, startup-state handoff, soft-limit behavior, control responsiveness, live status polling, left-right recovery, and safety polling to make the system behave more reliably under real motion. Now lastly, because leaving the central Pi unnecessarily exposed on a public network felt ironic while taking 18-330 Computer Security, I set up firewall protections to reduce unnecessary exposure and restrict access to only needed connections and not everyone at Carnegie Mellon.
To address the final point, I had to learn practical tools and concepts like Modbus/RS485 motor control, re learn homography and camera geometry which was a nice refresher on Computer Vision, firewall hardening for the central Pi. I learned them through documentation, hardware testing, debugging logs, and a lot of iterative trial and error on the rail system in lab.
Please check out the github for all the progress!
https://github.com/ahmadmla/autocam