A modern robotics visualization tool built in Rust, combining Makepad UI, Rerun 3D visualization, and Zenoh distributed networking for debugging robots and autonomous systems.

• Distributed-first architecture: Debug robots remotely over LAN using Zenoh auto-discovery
• Dora dataflow integration: Visualize sensor pipelines and node activity
• Rerun 3D visualization: Point clouds, transforms, markers, robot models
• ROS bag playback: Multi-sensor support (LiDAR, IMU, GPS, TF)
• URDF robot models: Load and visualize robot meshes

# Rust (nightly required for Makepad) curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh rustup install nightly rustup default nightly # Dora CLI cargo install dora-cli # Python dependencies (for example dataflows) pip install dora-rs pyyaml numpy pyarrow

git clone https://github.com/bobd988/dviz.git cd dviz cargo build --release

This builds:

• dviz - Main visualization shell
• dviz-dora-bridge - Dora node that publishes data via Zenoh

# Terminal 1: Start Dora daemon dora up # Terminal 2: Run a dataflow dora start dataflow.yml --name dviz # Terminal 3: Run DViz cargo run -p dviz-shell --release

In the DViz UI:

1. Click Spawn Rerun to open the 3D viewer
2. Zenoh auto-connects on startup (status shows "Zenoh: Connected")
3. View vehicle simulation data in Rerun

This example runs a vehicle path-following simulation with:

• bicycle_model - Vehicle physics simulator
• simple_planner - Pure pursuit path following
• imu_synthesizer - Synthetic IMU generation
• dviz_bridge - Publishes data via Zenoh

# Terminal 1 dora up # Terminal 2 dora start examples/dataflow-path-following.yml --name pathfollow # Terminal 3 cargo run -p dviz-shell --release

The visualization shows:

• Vehicle pose: Arrow showing position and heading
• Waypoints: Line strip showing planned path
• Target point: Current pursuit target
• IMU data: Acceleration/gyroscope scalars

This example runs a vehicle mapping pipeline that builds a 3D map from point cloud data using ICP odometry.

# Additional Python dependencies pip install open3d # Clone dora-examples (contains the mapping operators) git clone https://github.com/dora-rs/dora-examples.git ~/dora-examples

# Terminal 1: Start Dora daemon dora up # Terminal 2: Run the mapping dataflow dora start examples/dataflow-mapping.yml --name mapping # Terminal 3: Run DViz cargo run -p dviz-shell --release

In the DViz UI:

1. Click Spawn Rerun to open the 3D viewer
2. Zenoh auto-connects and receives mapping data

The visualization shows:

• Point clouds: LiDAR scans from PCD files
• Odometry pose: Vehicle position estimated by ICP
• Trajectory: Path traveled by the vehicle

DViz can play back ROS1 bag files with multi-sensor visualization support.

• PointCloud2: LiDAR point clouds (e.g., Velodyne)
• Imu: Accelerometer and gyroscope data
• NMEA Sentence: GPS position from NMEA messages
• TimeReference: GPS time synchronization
• Temperature: Temperature sensor readings

# Terminal 1: Run DViz cargo run -p dviz-shell --release

In the DViz UI:

1. Click Spawn Rerun to open the 3D viewer
2. Click File → Open Bag (or use the File button)
3. Select the bag file: examples/hdl_400.bag
4. Click Play to start playback

• Play/Pause: Toggle playback
• Stop: Reset to beginning
• Seek: Jump to specific time in the bag

The hdl_400.bag example displays:

• world/lidar: Velodyne point cloud (height-colored)
• world/imu/accel_arrow: Acceleration vector (cyan)
• world/imu/gyro_arrow: Angular velocity vector (orange)
• world/imu/accel_x,y,z: Acceleration scalars
• world/imu/gyro_x,y,z: Gyroscope scalars
• world/gps/position: GPS position (green point)
• world/gps/latitude,longitude,altitude: GPS scalars
• world/temperature/celsius: Temperature reading

DViz is designed for remote debugging where:

• Robot runs the dataflow headlessly (no display)
• Debug PC runs DViz to visualize robot data over LAN

┌─────────────────────┐ Zenoh (LAN) ┌─────────────────────┐ │ ROBOT │ ─────────────────────────── │ DEBUG PC │ │ (192.168.1.10) │ UDP Multicast │ (192.168.1.20) │ │ │ 224.0.0.225:7446 │ │ │ dora up │ │ cargo run -p │ │ dora start │ │ dviz-shell │ │ dataflow-robot │ ────────────> │ │ │ .yml │ sensor data │ Rerun 3D viewer │ └─────────────────────┘ └─────────────────────┘ 

SSH into the robot and run:

cd /path/to/dviz # Build the bridge (first time only) cargo build --release -p dviz-rerun-bridge # Start Dora daemon dora up # Run the robot dataflow dora start examples/dataflow-robot.yml --name robot

The robot will publish data to Zenoh topics:

• dviz/pose - Vehicle position
• dviz/state - Vehicle state
• dviz/imu - IMU readings
• dviz/waypoints - Planned path

cd /path/to/dviz # Run DViz cargo run -p dviz-shell --release

DViz auto-connects via Zenoh multicast scouting. Both machines must be on the same LAN subnet.

Zenoh uses multicast scouting by default:

• UDP multicast on 224.0.0.225:7446
• Works automatically on the same LAN subnet
• No configuration needed

If machines are on different subnets or multicast is blocked:

Set environment variable on the subscriber (debug PC):

ZENOH_CONNECT=tcp/192.168.1.10:7447 cargo run -p dviz-shell

Or in the dataflow YAML on the robot:

nodes: - id: dviz_bridge path: target/release/dviz-dora-bridge env: ZENOH_CONNECT: tcp/192.168.1.20:7447 # Debug PC address

Run a Zenoh router as a central hub:

# On any machine accessible by both robot and PC zenohd

Then configure both sides to connect:

# Robot ZENOH_CONNECT=tcp/router-ip:7447 dora start dataflow-robot.yml # PC ZENOH_CONNECT=tcp/router-ip:7447 cargo run -p dviz-shell

1. Find new robot IP: ip addr or hostname -I
2. If using direct connection, update debug PC:

   ZENOH_CONNECT=tcp/<new-robot-ip>:7447 cargo run -p dviz-shell

3. If using auto-discovery, no changes needed (same subnet)

1. If robot is configured to connect to PC:

   # Update dataflow-robot.yml env: ZENOH_CONNECT: tcp/<new-pc-ip>:7447

2. Restart the dataflow:

   dora stop robot dora start examples/dataflow-robot.yml --name robot

Use a Zenoh router with a static IP that both can reach:

# Router machine (e.g., 192.168.1.1) zenohd --listen tcp/0.0.0.0:7447 # Robot (any subnet) ZENOH_CONNECT=tcp/192.168.1.1:7447 dora start ... # PC (any subnet) ZENOH_CONNECT=tcp/192.168.1.1:7447 cargo run -p dviz-shell

# Linux (robot and PC) sudo ufw allow 7446/udp # Zenoh scouting sudo ufw allow 7447/tcp # Zenoh data # Or disable firewall for testing sudo ufw disable

dviz/ ├── dviz-core/ # Core types (Transform, PointCloud, Marker) ├── dviz-transform/ # Coordinate frame system ├── dviz-displays/ # Display plugins (Grid, TF, PointCloud, etc.) ├── dviz-urdf/ # URDF parsing and robot models ├── dviz-shell/ # Main application (Makepad UI) ├── dviz-widgets/ # Reusable UI components ├── dviz-rerun-bridge/ # Dora-to-Zenoh bridge node ├── dviz-rosbag/ # ROS bag playback ├── examples/ # Dataflow configurations └── docs/ # Design documentation 

DViz uses a universal JSON protocol that any application can publish:

{ "type": "points3d", "timestamp": 1.5, "data": { "positions": [[0, 0, 0], [1, 1, 1]], "color": [255, 0, 0, 255] } }

Supported types: points3d, arrows3d, linestrips3d, boxes3d, transform3d, scalar, image, log

Topic format: {prefix}/{entity_path} (e.g., dviz/world/vehicle/lidar)

Apache-2.0