WORK ACCOMPLISHED:
The initial parts required for SkateBack have been procured. Before the break, I picked up key components we ordered from the course inventory, including the Intel RealSense LiDAR Camera L515, Raspberry Pi 4, and the SparkFun GPS-RTK Dead Reckoning Breakout (ZED-F9R).
I began the initial setup for the Raspberry Pi 4. Additionally, I tested the LiDAR sensor on my desktop computer and installed the RealSense software on a Windows device to familiarize myself with its operation. I also explored how to run the Intel-provided SDK in a Linux environment and reviewed sample Python code to understand how to interface the LiDAR with the Raspberry Pi effectively.
Unfortunately, I was unable to test the GPS module as the required antenna and connectors to interface it with the Raspberry Pi or other computers are still pending. However, this hasn’t affected progress, as I have continued studying GPS operation and preparing code frameworks to interface with it once the missing parts arrive.
Additionally, we finalized most of our system design in the design report, which now serves as a critical reference document moving forward. The decisions documented there will guide component integration and help align all team members on the project’s direction.
PROGRESS:
I am currently on track with my tasks for the week, focusing primarily on setting up the Raspberry Pi environment and experimenting with sensor data collection. The initial tests with the LiDAR have provided insights into its data streams and will inform the next phase of development.
Moreover, I received notification that additional parts from our order have been delivered. This will allow us to begin assembling the physical skateboard and integrating components next week. With more hardware in hand, the team can shift attention toward building the board and testing individual subsystems.
NEXT WEEK’S DELIVERABLES:
My deliverables for next week are as follows:
- Test data collection from the sensors (GPS and LiDAR)
- Define a library of motor functions for the motors
- Work on sending object presence to the Raspberry Pi
- Work on the back up algorithm for obstacle avoidance