ntnu-arl/unified_autonomy_stack_datasets

Unified Autonomy Stack Datasets

This repository contains data released in relation with the Unified Autonomy Stack. Details can be found here

• Paper: https://arxiv.org/abs/2605.12735
• Code: https://ntnu-arl.github.io/unified_autonomy_stack/

The data was collected using the following platforms in both manually piloted and autonomously operated modes:

• AR-1 (Hornbill): A variant of the RMF-Owl collision-tolerant aerial robot.
• AR-2 (Magpie): A collision-tolerant aerial robot designed to carry the UniPilot module.
• GR-1 (Anymal): An ANYmal D quadruped robot from ANYbotics carrying the UniPilot module.
• UniPilot: A compact hardware-software autonomy payload that can be integrated across diverse robot embodiments to enable autonomous operation in GPS-denied environments. In addition to being carried by AR-2 and GR-1, a handheld (helmet-mounted) variant was used for the campus_fog sequence.

The following table summarizes the platforms used for each dataset:

Name	Location (Norway)	Platform(s)	Notes
basement/nmpc	NTNU Elektro Building basement	AR-2 (Magpie)	Autonomous Full Stack (Navigation mode: NMPC)
basement/rl	NTNU Elektro Building basement	AR-2 (Magpie)	Autonomous Full Stack (Navigation mode: RL)
elektro_hall	NTNU Elektro Building	GR-1 (UniPilot-Anymal)	Autonomous Full Stack
løkken_mine	Løkken mine	AR-2 (Magpie)	Autonomous Full Stack
runehamar_tunnel/magpie	Runehamar tunnel	AR-2 (Magpie)	Autonomous Full Stack
runehamar_tunnel/hornbill	Runehamar tunnel	AR-1 (Hornbill)	Manually Piloted, SLAM Evaluation
frozen_lake	Jonsvatnet Lake	AR-1 (Hornbill)	Manually Piloted, SLAM Evaluation
fyllingsdalen_tunnel	Fyllingsdalen tunnel	AR-1 (Hornbill)	Manually Piloted, SLAM Evaluation
campus_fog	NTNU campus	UniPilot	Helmet-mounted walking, SLAM Evaluation

Sensor Setup

Sensor	AR-1 (Hornbill)	UniPilot (AR-2 / GR-1 / handheld)
LiDAR	Ouster OS0-128 Rev7	RoboSense Airy; Hesai JT-128 on the handheld campus_fog
Camera	FLIR Blackfly S 0.4 MP Color	3× MIPI Vision Components IMX296-C
Radar	TI IWR6843AOP	D3 Embedded RS-6843AOPU FMCW; uRAD Industrial on the handheld campus_fog
IMU	VectorNav VN-100	VectorNav VN-100
Compute	Khadas VIM4	NVIDIA Jetson Orin NX

Data Description

Each sequence is released as a ROS 1 bag named sensors_only.bag containing the raw sensor data collected during the run. The ground truth is provided as a .tum file for the sequences where it is available.

Due to resource constraints on the platforms, the LiDAR is recorded as raw packets instead of the deserialized point clouds. To obtain bags with the point clouds, please view the lidar_packets_to_pointclouds.md.

Topics

The radar, IMU, and static transforms are common to all platforms; only the LiDAR and camera topics differ. Bags may additionally contain: flight-controller telemetry under /mavros/* (including GNSS as sensor_msgs/NavSatFix and mavros_msgs/GPSRAW where a fix was available), hardware time-synchronization triggers and status under /sensor_sync_node/*, further VN-100 streams (temperature, filtered IMU), and per-sensor host-receive timestamps under /<sensor>/ros_time_now.

Common to all platforms

Sensor	Topic	Datatype	Rate
Radar	/radar/cloud	sensor_msgs/PointCloud2	10 Hz
IMU	/vectornav_driver_node/imu/data	sensor_msgs/Imu	200 Hz
Magnetometer	/vectornav_driver_node/imu/mag	sensor_msgs/MagneticField	200 Hz
Barometer	/vectornav_driver_node/pressure	sensor_msgs/FluidPressure	200 Hz
Extrinsics (static transforms)	/tf_static	tf2_msgs/TFMessage	—

LiDAR

Recorded as raw packets corresponding to a 10 Hz point cloud (one LiDAR per platform):

Platform (LiDAR)	Packets	LiDAR IMU	Other
AR-1 (Ouster OS0-128)	/ouster/lidar_packets (ouster_ros/PacketMsg)	/ouster/imu_packets (ouster_ros/PacketMsg, 100 Hz)	/ouster/metadata (std_msgs/String)
UniPilot AR-2 / GR-1 (RoboSense Airy)	/rslidar_packets (rslidar_msg/RslidarPacket)	/rslidar_imu_data (sensor_msgs/Imu, 200 Hz)	—
UniPilot handheld (Hesai JT-128)	/lidar_packets (hesai_ros_driver/UdpFrame)	/lidar_imu (sensor_msgs/Imu)	/lidar_packets_loss (hesai_ros_driver/LossPacket)

Cameras

sensor_msgs/CompressedImage at 20 Hz:

Platform	Topic(s)
AR-1 (Hornbill)	/cam0/cam0/compressed (intrinsics on /cam0/camera_info)
UniPilot (AR-2 / GR-1 / handheld)	/cam_front/image_raw/compressed, /cam_left/image_raw/compressed, /cam_right/image_raw/compressed

On fyllingsdalen_tunnel, the AR-1 camera and radar were recorded at 25 Hz (the radar chirp configuration was changed for high-speed flight).

Calibration

Intrinsics

Camera intrinsics are provided in the calibration folder, with the same intrinsics for all sequences recorded on a given platform.

Extrinsics

The transforms between sensors are provided below. The transform $T_{AB}$ transforms a point from frame $B$ to frame $A$ as $p_A = T_{AB} * p_B$, where the point is represented in homogeneous coordinates. All transforms are provided in the format: x, y, z, qx, qy, qz, qw.

AR-1 (Hornbill):
  T_imu_lidar: [0.0166, 0.02158, 0.03375, 0, 0, 0, 1] 
  T_imu_radar: [0.077, 0.016, -0.063, 0.963, -0.021, -0.265, 0.021]
  T_imu_cam: [0.0725765278611583, 0.018936068067624674, -0.03560091123164558, 0.5543417213240229, -0.5433799916950063, 0.44199772312966146, 0.4495347076402992]

AR-2 / GR-1 (UniPilot):
  T_imu_lidar: [-0.06605, -0.01878, 0.034, 0.707, 0.00, -0.707, 0.00]
  T_imu_radar: [0.07717380907196035, -0.0479741168664902, 0.006770362043579366, 0.01761050968654745, 0.25032180256367187, -0.017699746191127304, 0.9679631109162291]

UniPilot handheld:
  T_imu_lidar: [-0.11484, -0.01878, 0.035, 0.3799282, -0.5963678, -0.3799282, 0.5963678]
  T_imu_radar: [0.08373, 0.0213, 0.02691, 0.6830127, 0.1830128, -0.1830128, 0.6830127]
  T_imu_cam_front: [0.083743715, 0.000235985, 0.005836153, -0.608415182, 0.616574414, -0.353450887, 0.353184694]
  T_imu_cam_left: [-0.021764534, 0.045545798, 0.023474280, -0.706455147, 0.000556152, -0.002366216, 0.707753642]
  T_imu_cam_right: [-0.025516567, -0.089169163, 0.024118153, 0.008477527, 0.715010265, -0.699047196, -0.004633580]

Ground Truth

Where available, ground truth is provided as a TUM-format trajectory file (timestamp tx ty tz qx qy qz qw) alongside the bag.

• Tunnels (fyllingsdalen_tunnel, runehamar_tunnel/hornbill): generated by fusing the tracking of a Leica GRZ101 mini-prism (mounted on AR-1) by a Leica MS60 MultiStation with the onboard IMU, in an offline Levenberg-Marquardt optimization.
• campus_fog and frozen_lake: GNSS was available, so ground truth is created using a GNSS-augmented visual bundle adjustment optimization with Pix4DMatic.

Citation

If you use this data in your research, please cite the following publication:

@misc{dharmadhikari2026unifiedautonomystackblueprint,
      title={The Unified Autonomy Stack: Toward a Blueprint for Generalizable Robot Autonomy}, 
      author={Mihir Dharmadhikari and Nikhil Khedekar and Mihir Kulkarni and Morten Nissov and Martin Jacquet and Angelos Zacharia and Marvin Harms and Albert Gassol Puigjaner and Philipp Weiss and Kostas Alexis},
      year={2026},
      eprint={2605.12735},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2605.12735}, 
}