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EU Long-term Dataset with Multiple Sensors for Autonomous Driving

Zhi Yan, Li Sun, Tomas Krajnik, and Yassine Ruichek

Build Status

Dataset

https://epan-utbm.github.io/utbm_robocar_dataset/

Baselines

We forked the implementation of the following state-of-the-art methods and experimented (with minor changes) with our dataset:

All users are more than welcome to commit their results.

Ground-truth trajectories recorded by GPS/RTK

hector_pose_estimation (pose estimation)

hector_pose.png

How to play

roslaunch utbm_pose_estimation.launch bag:=path_to_your_rosbag

utbm_pose_estimation.launch is here.

Evaluation

First of all, you should have something like this:

hector_rosgraph.png

Then, /fix/pose(geometry_msgs/PoseStamped) is the estimated robot pose (6DOF) based on the GPS data.

loam_velodyne (lidar odometry)

loam_map.png

How to play

roslaunch loam_velodyne loam_velodyne_utbm.launch bag:=path_to_your_rosbag

loam_velodyne_utbm.launch is here.

Evaluation

First of all, you should have something like this:

loam_rosgraph.png

Then, /aft_mapped_to_init(nav_msgs/Odometry) is the output lidar odometry that needs to be evaluated.

Single Velodyne HDL-32E (left)

loam_velodyne_20180719.png

LeGO-LOAM (lidar odometry)

lego_map.png

How to play

roslaunch lego_loam lego_loam_utbm.launch bag:=path_to_your_rosbag

lego_loam_utbm.launch is here.

Evaluation

First of all, you should have something like this:

lego_rosgraph.png

Then, /aft_mapped_to_init(nav_msgs/Odometry) is the output lidar odometry that needs to be evaluated.

Single Velodyne HDL-32E (left)

lego_loam_20180719.png lego_loam_loop_closure_20180719.png

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EU Long-term Dataset with Multiple Sensors for Autonomous Driving

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