Electronics: Difference between revisions
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== System Architecture == | == System Architecture == | ||
During testing, it was observed that the Main | During testing, it was observed that the Main Raspi could not reliably handle all ROS launch packages simultaneously. To improve stability and performance, most workloads were therefore moved to the Aux Raspberry Pi. | ||
One likely reason for this difference is the storage medium. The Main Raspberry Pi uses an SD card, while the Aux Raspberry Pi uses an external SSD, which provides significantly faster read/write performance and better handling of high I/O workloads generated by ROS 2 nodes, logging, and vision processing. | One likely reason for this difference is the storage medium. The Main Raspberry Pi uses an SD card, while the Aux Raspberry Pi uses an external SSD, which provides significantly faster read/write performance and better handling of high I/O workloads generated by ROS 2 nodes, logging, and vision processing. | ||
Revision as of 12:27, 27 May 2026
Raspberry Pi
The robot uses two Raspberry Pi 5 units, referred to as the "Main" and "Aux" Raspberry Pi.
The "Main Raspi" is responsible for core robot functionality and launches the odometry, lifecycle management, and bridge-related ROS nodes.
The "Aux Raspi" handles the majority of the remaining ROS launch packages, including the computationally intensive perception and support nodes.
Hardware Specifications
Main Raspberry Pi
- Raspberry Pi 5
- 16 GB RAM
- 60 GB storage (SD card)
Aux Raspberry Pi
- Raspberry Pi 5
- 8 GB RAM
- 512 GB external SSD storage
System Architecture
During testing, it was observed that the Main Raspi could not reliably handle all ROS launch packages simultaneously. To improve stability and performance, most workloads were therefore moved to the Aux Raspberry Pi.
One likely reason for this difference is the storage medium. The Main Raspberry Pi uses an SD card, while the Aux Raspberry Pi uses an external SSD, which provides significantly faster read/write performance and better handling of high I/O workloads generated by ROS 2 nodes, logging, and vision processing.
This split architecture allows the robot to distribute computational load more effectively and improves overall system responsiveness and reliability.
