In this year's SLAM challenge, for the first time, we provide a dataset which was recorded with a robot. In the following, you find an overview about the system.
The robot used to record the datasets is a minimalistic version of the Hilti JaiBot. We have equipped the system with a XSens MTi-600 IMU, a Robosense Bpearl LiDAR and four OAK-D Pro PoE cameras. An overview of the coordinate systems can be seen in the following images:
All sensors (except for track odometry) are hardware synchronized. A PTP master is running on the NIC of the main PC. The LiDAR sensor is synchronized directly to the master via PTP. The clock of the IMU is synchronized via a PTP-to-trigger conversion board. The same board also triggers the cameras start-of-exposure. All cameras start their exposure simultaneously, but every stereo camera pair runs its own auto-exposure algorithm. Each stereo camera pair uses the same exposure. The timestamp of the image messages corresponds to the center-of-exposure.
The clocks of the IMU and the LiDAR are expected to be synchronized within 1ms accuracy. The clocks of the IMU and the cameras are expected to be synchronized within 2ms accuracy.
We used kalibr for the intrinsic calibration of the cameras, imu_utils for the intrinsic calibration of the IMU and an adapted variant of MultiCal for the extrinsic calibration of IMU, cameras and LiDAR. A calibration (together with a dataset for running a new calibration) is made available on the Challenge Website.
In total, we provide three robotic datasets which were recorded on a construction site of a parking garage.
| Dataset | Description |
|---|---|
| site2_robot_1.bag | A long dataset with the robot driving through all three parking garage levels. |
| site2_robot_2.bag | A dataset of a large room with the robot driving through the center. |
| site2_robot_3.bag | A dataset of a (different) large room with the robot driving through the center at night. |
The IMU topic of type sensor_msgs/Imu provides accelerometer and gyroscope measurements at a rate of 200Hz. The frame ID of the measurements is xsens_imu_link.
The LiDAR topic of type sensor_msgs/PointCloud2 provides the sensor readings of the hemispherical LiDAR mounted to the front of the system at 10Hz. The header timestamp corresponds to the last (latest) point in the message. The fields are as follows
| Field | Type | Description |
|---|---|---|
| x,y,z | float32 | Measured point in Cartesian coordinates |
| intensity | float32 | The intensity of the measurement, 0 to 254. We know that uint8 would have been smarter |
| ring | uint16 | The index of the laser diode which captured the point, 0 to 31 |
| timestamp | float64 | The absolute timestamp of the point |
Note that unlike the images might suggest, when recording the datasets, we removed the robot arm. Therefore, it is possible to use the full pointcloud without running a self-filter. The frame ID of the LiDAR measurements is rslidar.
The track odometry topic of type nav_msgs/Odometry provides a 2D estimate of the linear and angular velocity and an integrated 2D position of the system given the track velocities at 100Hz. Note that this sensor is only software-synchronized (we do not expect this to be significantly more accurate than 10ms). The frame ID of the odometry reference frame is odom and the child frame is base_link.
The camera topics of type sensor_msgs/Image provide the image data for the sensors at 10Hz. The image dimensions are 1280x800. The header timestamp corresponds to the center-of-exposure of the image. The <STEREO_DIRECTION> refers to where the stereo camera is pointing (front, left, rear, right) and the <SUB_CAMERA> selects the actual camera on the stereo camera system (left, right). The frames are named as follows
| Stereo Direction | Sub-camera | Topic | Frame ID |
|---|---|---|---|
| front | left | /oak_cam_front/left/image_raw | oak_cam_front_left_camera_optical_frame |
| right | /oak_cam_front/right/image_raw | oak_cam_front_right_camera_optical_frame | |
| left | left | /oak_cam_left/left/image_raw | oak_cam_left_left_camera_optical_frame |
| right | /oak_cam_left/right/image_raw | oak_cam_left_right_camera_optical_frame | |
| rear | left | /oak_cam_rear/left/image_raw | oak_cam_rear_left_camera_optical_frame |
| right | /oak_cam_rear/right/image_raw | oak_cam_rear_right_camera_optical_frame | |
| right | left | /oak_cam_right/left/image_raw | oak_cam_right_left_camera_optical_frame |
| right | /oak_cam_right/right/image_raw | oak_cam_right_right_camera_optical_frame |
The exposure info topics of type hilti_slam_challenge_msgs/ExposureInfo provide additional information for the images. The header of these messages is equivalent to the corresponding image message. The message contains the fields start_of_frame corresponding to the absolute start of exposure (this is synchronized across all cameras), the exposure_time corresponding to the exposure time in microseconds, and the iso corresponding to the sensor sensitivity reported by the camera auto-exposure algorithm.
Absolutely, see trailblazer_description.