Intelligent Ground Vehicle Competition (IGVC) Dashboard

Team Members

Ajay, Donte, Eric, Shreyaa

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Summary

Live telemetry and analysis for the car: sensor streams (with filtering), derived run metrics, a telemetry sidebar, and a browser-based replay mode for uploaded telemetry exports.

Sensor views

• Speed time series, live, and max value
• Power time series (calculated from current and voltage data)
• GPS location display with Google Maps
• Live Steering angle, Brake pressure, Throttle, and RPM on all wheels
• Timestamps and stopwatch for lap and race timing

Replay tools

• Upload a telemetry CSV export and replay it directly in the dashboard UI
• Scrub through samples with a timeline slider or play/pause the run at multiple playback speeds
• Reuse the same dashboard widgets in Replay mode to inspect historical data sample-by-sample

Derived metrics

• Distance calculated from aggregating GPS data
• Energy Use calculated from power
• Efficiency instantaneous and average over a run

Getting Started

1. Running the Project

   Create a .env file in the the root directory (not under /backend or /frontend). See .env.example for more info.

   Make sure Docker containers and volumes for this project are not running already. Then, run docker compose up --build to get all containers running.

   Compose variants:

   • docker compose -f docker-compose.dev.yml up --build for local development and mock camera testing
   • RUN_MOCK_CAMERA=true docker compose -f docker-compose.dev.yml up --build to enable the mock camera
   • docker compose -f docker-compose.prod.yml up --build for the real ROS LAN setup

   The frontend client UI should be running on port 3000.
   The backend healthcheck endpoint is on the root of port 8000.

2. Frontend Testing

   Refer to frontend/README.md for more information.
   Bun Installation: The frontend uses Bun instead of NodeJS as a package manager and runtime. The installation is linked here. Then, run the following commands in the terminal to test/run the frontend in isolation.
   This will start the frontend development environment with HMR and Vite at port 5173.

   cd frontend
   bun dev

   Google Maps: To get location data and Google Maps properly displaying while running only the frontend with bun dev, create a .env file in the /frontend directory. Follow the .env.example in the /frontend and create the environment variables below.

   VITE_GOOGLE_MAPS_API_KEY=<Your Google Maps API Key here>
   VITE_GOOGLE_MAP_ID=<Your Google Maps Map ID from Google Cloud console>

   Instructions for getting your own API_KEY and MAP_ID are in frontend/README.md.

3. Backend Troubleshooting

   Refer to backend/README.md.

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ROS Subscriber Data

For the ROS 2 subscriber over LAN, connect the laptop and Jetson to the same router network and set the Jetson's LAN IP in .env:

JETSON_LAN_IP=192.168.1.2

Use DISCOVERY_SERVER_IP only if the Fast DDS discovery server is on a different LAN address than JETSON_LAN_IP.

Replay Mode

The frontend includes a dedicated Replay page alongside the live Data view. Use it to inspect telemetry exports without needing a live ROS2 stream.

Current capabilities

• Upload a .csv telemetry file from the Replay page
• Upload a rosbag2 SQLite .db3 file from the Replay page
• Play, pause, reset, and scrub through the uploaded run
• Change playback speed from 0.5x up to 100x
• Render replayed samples through the same dashboard layout used for live telemetry

CSV expectations

CSV replay is parsed entirely in the frontend and is intentionally flexible about column names. Headers are normalized by lowercasing and removing punctuation, so both flat and dotted names are accepted.

Examples of supported fields include:

• speed, speed_mps, gps.speed, velocity
• filtered.speed
• gps.lat, gps.long, latitude, longitude
• power.current, power.voltage
• steering.turn_angle, steering.brake_pressure
• motor.rpm, motor.duty_cycle
• rpm_front.left, rpm_front.right, rpm_back.left, rpm_back.right
• global_ts, timestamp, time, or a row index fallback when timestamps are missing

If a speed column name includes mph, the replay parser converts it to meters per second before rendering. If GPS coordinates are missing, the dashboard falls back to default coordinates and shows a warning after upload.

ROSBag expectations

ROS bag replay currently supports rosbag2 SQLite .db3 files and converts them through the backend into flattened CSV-style telemetry rows before rendering. Replayable messages should contain JSON payloads, like the example bag files under frontend/data. Messages that cannot be converted into telemetry rows are skipped during import.

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System Overview

ROS2 Sensors → Backend (Python + ROS2) → WebSocket Stream → Frontend (React + TypeScript + Bun)

Uploaded CSV → Frontend Replay Parser → Replay Timeline → Shared Dashboard Widgets
Uploaded ROS bag `.db3` → Backend Bag Parser → Replay Timeline → Shared Dashboard Widgets

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ROSbag + Remote Data Handling

• The frontend can trigger ROSbag recording via /bag endpoints
• The backend publishes rosbag recording state on dashboard_control/bag_recording
• ROSbag recording consumers should subscribe to that control topic and start on 1, stop on 0
• Local dashboard replay supports uploaded CSV telemetry exports and rosbag2 SQLite .db3 files