docs/foxglove_visualization.md

Foxglove Visualization

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This guide shows how to inspect the dataset in Foxglove with ToF heatmaps, RGB images, LiDAR point clouds, MAVROS IMU curves, and 3D odometry.

The raw rosbag remains the source data. The Foxglove bag is a visualization artifact generated with scripts/foxglove_visual.py.

Ready-To-Open Example

The Hugging Face dataset includes a Foxglove example:

examples/foxglove/visual_demo.bag

It is generated from session:

raw/sessions/2026-05-20_030414_odom_run029/bag.bag

Open the example bag in Foxglove, then create the panels below.

Recommended Layout

Panel	Topic / setting
Image	/foxglove/tof/overview/compressed
Image	/camera/color/image_raw
3D	Fixed frame = odom, Display frame = odom
3D point cloud	/foxglove/livox/points
3D path	/foxglove/odom/path
3D odometry	/fusion_odometry/lazy_point_odom or /ekf_quat/ekf_odom
Plot	/mavros/imu/data_raw.angular_velocity.{x,y,z}
Plot	/mavros/imu/data_raw.linear_acceleration.{x,y,z}

For this dataset, set both 3D frame fields to:

Fixed frame:   odom
Display frame: odom

The visualization bag provides this TF chain:

odom -> base_link -> livox_frame
base_link -> base_link_frd
odom -> odom_ned

Use odom for the main 3D view. odom_ned and base_link_frd are auxiliary frames for NED/FRD conventions.

Topic Guide

Topic	Type	What it shows
/foxglove/tof/overview/compressed	sensor_msgs/CompressedImage	Six-node Nooploop TOFSense-M 8x8 cascade heatmap
/nlink_tofsensem_cascade	nlink_parser/TofsenseMCascade	Original ToF numeric data
/camera/color/image_raw	sensor_msgs/Image	Intel RealSense D435i RGB stream
/camera/color/camera_info	sensor_msgs/CameraInfo	RGB camera intrinsics
/livox/lidar	livox_ros_driver2/CustomMsg	Original Livox MID360s packet topic
/foxglove/livox/points	sensor_msgs/PointCloud2	Foxglove-ready LiDAR point cloud
/foxglove/odom/path	nav_msgs/Path	Accumulated odometry trajectory for 3D display
/mavros/imu/data	sensor_msgs/Imu	Filtered flight-controller IMU
/mavros/imu/data_raw	sensor_msgs/Imu	Raw flight-controller IMU
/fusion_odometry/lazy_point_odom	nav_msgs/Odometry	Main odometry for 3D trajectory
/ekf_quat/ekf_odom	nav_msgs/Odometry	EKF odometry, when present
/tf	tf2_msgs/TFMessage	Dynamic odometry transform
/tf_static	tf2_msgs/TFMessage	Static camera, LiDAR, and frame transforms

Foxglove does not reliably render Livox custom messages directly. Use /foxglove/livox/points for the 3D point cloud.

ToF Panel

Add an Image panel and select:

/foxglove/tof/overview/compressed

The overview image contains six TOFSense-M nodes. Each node shows:

Field	Meaning
dis	distance in millimeters
dis_status	per-pixel distance status
signal_strength	per-pixel return strength

Valid pixels are colorized by distance. Invalid or missing pixels are drawn in gray.

LiDAR Panel

Add a 3D panel and select:

/foxglove/livox/points

Recommended point-cloud settings:

Setting	Value
Point size	1.0 to 1.5
Point shape	Circle
Color mode	Color map
Color field	intensity
Stixel view	Off

If Stixel view is enabled, Foxglove draws pillar-like vertical structures. That is useful for obstacle-style views, but it is not the best mode for checking the raw point cloud.

Odometry And TF

Add odometry display in the same 3D panel:

/fusion_odometry/lazy_point_odom

For the already-traveled trajectory line, add:

/foxglove/odom/path

If that topic is not available in a selected session, use:

/ekf_quat/ekf_odom

The generated bag injects dynamic TF from odometry, so the 3D view can resolve:

odom -> base_link -> livox_frame

This is the frame path required to show the LiDAR point cloud together with the odometry trajectory.

IMU Plots

Add a Plot panel and select angular velocity:

/mavros/imu/data_raw.angular_velocity.x
/mavros/imu/data_raw.angular_velocity.y
/mavros/imu/data_raw.angular_velocity.z

For acceleration, add:

/mavros/imu/data_raw.linear_acceleration.x
/mavros/imu/data_raw.linear_acceleration.y
/mavros/imu/data_raw.linear_acceleration.z

Use /mavros/imu/data when you want the filtered MAVROS IMU stream, and /mavros/imu/data_raw when you want the raw flight-controller IMU stream.

Generate A Visualization Bag

Build the ROS1 helper image once:

make docker-build

Generate a 30 second all-modality example:

docker/ros1_noetic/run.sh 'python3 scripts/foxglove_visual.py \
  --input-bag raw/sessions/2026-05-20_030414_odom_run029/bag.bag \
  --output-bag outputs_tmp/foxglove_samples/run029_mid30s_all_modalities_foxglove.bag \
  --start-offset-sec 189.891 \
  --duration-sec 30 \
  --copy-mode custom \
  --keep-topics /tf_static,/camera/color/image_raw,/camera/color/camera_info,/livox/lidar,/mavros/imu/data,/mavros/imu/data_raw,/nlink_tofsensem_cascade,/fusion_odometry/lazy_point_odom,/ekf_quat/ekf_odom \
  --tof-rate-hz 15 \
  --tf-rate-hz 30 \
  --tf-parent-frame odom \
  --force'

Generate a ToF + odometry focused bag:

docker/ros1_noetic/run.sh 'python3 scripts/foxglove_visual.py \
  --input-bag raw/sessions/2026-05-20_030414_odom_run029/bag.bag \
  --output-bag outputs_tmp/foxglove_samples/run029_tof_odom_foxglove.bag \
  --copy-mode custom \
  --keep-topics /tf_static,/mavros/imu/data,/mavros/imu/data_raw,/nlink_tofsensem_cascade,/fusion_odometry/lazy_point_odom,/ekf_quat/ekf_odom \
  --tof-rate-hz 15 \
  --tf-rate-hz 30 \
  --tf-parent-frame odom \
  --force'

Useful Options

Option	Purpose
--start-offset-sec	Start from an offset relative to the raw bag start
--duration-sec	Convert only a time window
--copy-mode custom	Keep exactly the original topics listed in --keep-topics
--keep-topics	Original raw topics to copy into the visualization bag
--tof-rate-hz	ToF overview image rate; 15 matches the nominal TOFSense-M 8x8 rate
--tof-image-mode overview	Write only the six-node overview image
--tof-image-mode both	Write overview plus per-node ToF images
--convert-livox-pointcloud2	Convert /livox/lidar to /foxglove/livox/points
--livox-calibration	LiDAR-to-body calibration YAML used for /tf_static
--tf-parent-frame odom	Use odom -> base_link for injected dynamic TF
--bag-compression bz2	Compress the generated bag

Troubleshooting

Symptom	Check
ToF image panel says waiting for messages	Make sure /foxglove/tof/overview/compressed exists in the bag
LiDAR topic has a warning icon	Use /foxglove/livox/points, not raw /livox/lidar
Point cloud does not appear in 3D	Confirm Fixed frame = odom and Display frame = odom
Point cloud looks like vertical pillars	Turn Stixel view off
Odometry and point cloud are not aligned	Confirm /tf and /tf_static are enabled
RGB panel is blank	Use an Image panel for /camera/color/image_raw

To inspect the generated bag before opening it:

docker/ros1_noetic/run.sh 'rosbag info outputs_tmp/foxglove_samples/run029_mid30s_all_modalities_foxglove.bag'