DingoOz

DingoOz / ros2_diag_tui

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Curses-based TUI dashboard for real-time ROS2 robot diagnostics

22
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100% credibility
Found Feb 28, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A terminal-based dashboard for real-time monitoring of ROS2 robot diagnostics, including topic rates, frame trees, navigation states, sensor visualizations, and network status.

How It Works

1
🕵️ Discover the Dashboard

You hear about a handy screen tool that lets you watch your robot's health right in your terminal.

2
🛠️ Add to Your Setup

You place this tool into your robot project folder so it's ready to use.

3
🚀 Launch the Viewer

You start the dashboard and it connects to your robot's live information.

4
👀 See Everything Live

The screen fills with real-time updates on sensor speeds, connections, and robot states, making issues pop right out.

5
🤖 Pick Your Robot

You choose the setup that matches your robot model, like a TurtleBot, for perfect monitoring.

6
🔍 Explore Views

You switch to special views of laser scans or maps, zooming and checking details easily.

7
⚙️ Tweak On the Fly

You adjust settings or check logs directly in the tool to fine-tune what you see.

✅ Robot Runs Smoothly

Now you spot problems early, keep everything connected, and your robot operates perfectly without surprises.

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Star Growth

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AI-Generated Review

What is ros2_diag_tui?

ros2_diag_tui is a Python curses-based TUI dashboard for real-time ROS2 robot diagnostics. It lets you monitor topic rates, TF tree connectivity, Nav2 lifecycle states, LiDAR scans, occupancy grids, network status, and image topics directly in your terminal—no GUI required. Run it via ros2 run diag_tui with YAML configs tailored for robots like TurtleBot3 or TurtleBot4 to spot issues like stale data or failed frames instantly.

Why is it gaining traction?

Its braille-rendered LiDAR and map overlays, plus live message previews and in-app config editing, deliver dense diagnostics without leaving the terminal. Preflight mode with exit codes fits CI pipelines, and adjustable refresh rates keep it snappy on resource-constrained robots. YAML-driven setups make swapping between robot configs dead simple, standing out over scattered ros2 topic tools.

Who should use this?

ROS2 developers debugging Nav2 stacks on TurtleBots or custom diff-drives, especially during field testing or pre-deployment checks. Robot operators needing quick topic health scans without X11 forwarding, or teams scripting robot readiness in launch files. Ideal for those ditching heavy tools like rqt for lightweight terminal diag.

Verdict

Grab it if you're in ROS2 robotics—solid docs, robot-specific configs, and MIT license make it plug-and-play despite 19 stars and 1.0% credibility score signaling early maturity. Test on your setup; lacks broad validation but nails core diagnostics needs.

(198 words)

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