Cooperative Robotic Exploration of a Planetary Skylight Surface and Lava Cave - Datasets

The dataset contains the logs used to produce the results described in the publication Cooperative Robotic Exploration of a Planetary Skylight Surface and Lava Cave. Raúl Domínguez et. al. 2025 Cooperative Surface Exploration - CoRob_MP1_results.xlsx: Includes the log produced at the commanding station during the Mission Phase 1. It has been used to produce the results evaluation of the MP1. - cmap.ply: Resulting map of the MP1. - ground_truth_transformed_and_downsampled.ply: Ground truth map used for the evaluation of the cooperative map accuracy. Ground Truth Rover Logs The dataset contains the samples used to generate the map provided as ground truth for the cave in the publication Cooperative Robotic Exploration of a Planetary Skylight Surface and Lava Cave. Raúl Domínguez et. al. 2025 The dataset has three parts. Between each of the parts, the data capture had to be interrupted. After each interruption, the position of the rover is not exactly the same as before the interruption. For that reason, it has been quite challenging to generate a full reconstruction using the three parts one after the other. In fact, the last one of the logs has not been filtered, since it was not possible to combine the different parts in a single SLAM reconstruction, the last part was not even pre-processed. Each log contains:- depthmaps, the raw LiDAR data from the Velodyne 32. Format: tiff.- filtered_cloud, the pre-processed LiDAR data from the Velodyne 32. Format: ply.- joint_states, the motor position values. Unfortunately the back axis passive joint is not included. Format: json.- orientation_samples, the orientation as provided by the IMU sensor. Format: json. - asguard_v4.urdf: In addition to the datasets, a geometrical robot model is provided which might be needed for environment reconstruction and pose estimation algorithms. Format: URDF. Folders contents ├── 20211117-1112│ ├── depth│ │ └── depth_1637143958347198│ ├── filtered_cloud│ │ └── cloud_1637143958347198│ ├── joint_states│ │ └── joints_state_1637143957824829│ └── orientation_samples│ └── orientation_sample_1637143958005814├── 20211117-1140│ ├── depth│ │ └── depth_1637145649108790│ ├── filtered_cloud│ │ └── cloud_1637145649108790│ ├── joint_states│ │ └── joints_state_1637145648630977│ └── orientation_samples│ └── orientation_sample_1637145648831795└── 20211117-1205 ├── depth │ └── depth_1637147164030135 ├── filtered_cloud │ └── cloud_1637147164330388 ├── joint_states │ └── joints_state_1637147163501574 └── orientation_samples └── orientation_sample_1637147163655187 Cave reconstruction - first_log_2cm_res_pointcloud-20231222.ply, contains the integrated pointcloud produced from the first of the logs. Coyote 3 Logs The msgpack datasets can be imported using Python with the pocolog2msgpack library The geometrical rover model of Coyote 3 is included in URDF format. It can be used in environment reconstruction algorithms which require the positions of the different sensors. MP3 Includes exports of the log files used to compute the KPIs of the MP3. MP4 These logs were used to obtain the KPI values for the MP4. It is composed of the following archives:- log_coyote_02-03-2023_13-22_01-exp3.zip- log_coyote_02-03-2023_13-22_01-exp4.zip- log_coyote_02-09-2023_19-14_18_demo_skylight.zip- log_coyote_02-09-2023_19-14_20_demo_teleop.zip- coyote3_odometry_20230209-154158.0003_msgpacks.tar.gz- coyote3_odometry_20230203-125251.0819_msgpacks.tar.gz Cave PLYs Two integrated pointclouds and one trajectory produced from logs captured by Coyote 3 inside the cave:- Skylight_subsampled_mesh.ply- teleop_tunnel_pointcloud.ply- traj.ply Example scripts to load the datasets The repository https://github.com/Rauldg/corobx_dataset_scripts contains some example scripts which load some of the datasets.本数据集包含用于生成论文《Cooperative Robotic Exploration of a Planetary Skylight Surface and Lava Cave》（Raúl Domínguez等，2025年）中所述结果的日志文件。 ### 协同地表探索 1. `CoRob_MP1_results.xlsx`：包含任务阶段1（Mission Phase 1，MP1）指挥站生成的日志，用于生成MP1的结果评估报告。 2. `cmap.ply`：MP1生成的建图结果。 3. `ground_truth_transformed_and_downsampled.ply`：用于评估协同建图精度的地面真值地图。 ### 地面真值漫游车日志 本数据集包含用于生成论文《Cooperative Robotic Exploration of a Planetary Skylight Surface and Lava Cave》中所述洞穴地面真值地图的样本数据。 本数据集分为三个部分，各部分之间的数据采集过程均存在中断。每次中断后，漫游车的位置与中断前不完全一致，因此难以将三个部分的日志依次拼接以完成完整的同步定位与建图（Simultaneous Localization and Mapping, SLAM）重建。实际上，第三段日志未经过滤波处理，且由于无法将三个部分的日志整合为单次SLAM重建结果，甚至未对第三段日志进行预处理。 每条日志包含以下内容： - **depthmaps**：Velodyne 32激光雷达（LiDAR）的原始数据，格式为tiff。 - **filtered_cloud**：Velodyne 32激光雷达的预处理点云数据，格式为ply。 - **joint_states**：电机位置值。遗憾的是，未包含后轴被动关节的数据，格式为json。 - **orientation_samples**：惯性测量单元（Inertial Measurement Unit, IMU）采集的姿态数据，格式为json。 此外，本数据集还提供了几何机器人模型`asguard_v4.urdf`（统一机器人描述格式，Unified Robot Description Format, URDF），可用于场景重建与位姿估计算法。 ### 文件夹内容 ├── 20211117-1112 │ ├── depth │ │ └── depth_1637143958347198 │ ├── filtered_cloud │ │ └── cloud_1637143958347198 │ ├── joint_states │ │ └── joints_state_1637143957824829 │ └── orientation_samples │ └── orientation_sample_1637143958005814 ├── 20211117-1140 │ ├── depth │ │ └── depth_1637145649108790 │ ├── filtered_cloud │ │ └── cloud_1637145649108790 │ ├── joint_states │ │ └── joints_state_1637145648630977 │ └── orientation_samples │ └── orientation_sample_1637145648831795 └── 20211117-1205 ├── depth │ └── depth_1637147164030135 ├── filtered_cloud │ └── cloud_1637147164330388 ├── joint_states │ └── joints_state_1637147163501574 └── orientation_samples └── orientation_sample_1637147163655187 ### 洞穴重建 `first_log_2cm_res_pointcloud-20231222.ply`：包含从第一段日志整合得到的点云数据。 ### Coyote 3 日志 本数据集的msgpack格式文件可通过Python结合`pocolog2msgpack`库导入。 Coyote 3的几何机器人模型以统一机器人描述格式（URDF）提供，可用于需要搭载各传感器位置信息的场景重建算法。 ### MP3 包含用于计算MP3关键绩效指标（Key Performance Indicator, KPI）的日志文件导出数据。 ### MP4 本部分日志用于获取MP4的关键绩效指标值，包含以下归档文件： - `log_coyote_02-03-2023_13-22_01-exp3.zip` - `log_coyote_02-03-2023_13-22_01-exp4.zip` - `log_coyote_02-09-2023_19-14_18_demo_skylight.zip` - `log_coyote_02-09-2023_19-14_20_demo_teleop.zip` - `coyote3_odometry_20230209-154158.0003_msgpacks.tar.gz` - `coyote3_odometry_20230203-125251.0819_msgpacks.tar.gz` ### 洞穴PLY文件 包含三个由Coyote 3在洞穴内采集的日志生成的整合点云与轨迹文件： - `Skylight_subsampled_mesh.ply` - `teleop_tunnel_pointcloud.ply` - `traj.ply` ### 数据集加载示例脚本 仓库`https://github.com/Rauldg/corobx_dataset_scripts`包含部分用于加载本数据集的示例脚本。