Agilex_Split_Aloha_take_out_the_bread

# Agilex_Split_Aloha_take_out_the_bread ## Dataset Description This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot. ## Task Preview <video src="videos/chunk-000/observation.images.cam_front_rgb/episode_000000.mp4" controls width="640"></video> [View Video Directly](videos/chunk-000/observation.images.cam_front_rgb/episode_000000.mp4) ### Overview - **Total Episodes:** 588 - **Total Frames:** 333147 - **FPS:** 30 - **Dataset Size:** 15.15 GB - **Robot Name:** `Agilex_Split_Aloha` - **End-Effector Type:** `two_finger_end_effector` - **Teleoperation Type:** `Due to some reasons, this dataset temporarily cannot provide the teleoperation type information.` - **Sensors:** `cam_front_rgb`, `cam_left_wrist_rgb`, `cam_right_wrist_rgb` - **Camera Information:** cam_front_rgb; cam_left_wrist_rgb; cam_right_wrist_rgb - **Scene:** `home` - **Objects:** `table(unknown)`, `bread_machine(unknown)`, `bread(unknown)`, `tablecloth(unknown)`, `plate(unknown)` - **Task Description:** Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the blue coffee table., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the light coffee tablecloth., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the green coffee tablecloth., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the grey coffee table., Pick up the toasted bread from the bread machine with the gripper and place it on the white table, then place it on the plate., Pick up the toasted bread from the bread machine with the gripper and place it on the white checkered table. Place it on the plate with the gripper. ### Primary Task Instruction > Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the blue coffee table., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the light coffee tablecloth., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the green coffee tablecloth., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the grey coffee table., Pick up the toasted bread from the bread machine with the gripper and place it on the white table, then place it on the plate., Pick up the toasted bread from the bread machine with the gripper and place it on the white checkered table. Place it on the plate with the gripper. ### Robot Configuration - **Robot Name:** `Agilex_Split_Aloha` - **Codebase Version:** `v2.1` - **End-Effector Type:** `two_finger_end_effector` - **Teleoperation Type:** `Due to some reasons, this dataset temporarily cannot provide the teleoperation type information.` ## Scene and Objects ### Scene Type - `home` ### Objects - `table(unknown)` - `bread_machine(unknown)` - `bread(unknown)` - `tablecloth(unknown)` - `plate(unknown)` ## Task Descriptions - **Standardized Task Description:** `Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the blue coffee table., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the light coffee tablecloth., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the green coffee tablecloth., Pick up the toasted bread from the bread machine with the gripper and place it on the plate on the grey coffee table., Pick up the toasted bread from the bread machine with the gripper and place it on the white table, then place it on the plate., Pick up the toasted bread from the bread machine with the gripper and place it on the white checkered table. Place it on the plate with the gripper.` - **Operation Type:** `Due to some reasons, this dataset temporarily cannot provide the operation type information.` - **Environment Type:** `Due to some reasons, this dataset temporarily cannot provide the environment type information.` ### Sub-Tasks This dataset includes 5 distinct subtasks: 1. **use the right arm to place a cut of bread into the plate.** (Index: 0) 2. **use the left arm to place a cut of bread into the empty plate.** (Index: 1) 3. **use the left arm to pick up out a cut of bread.** (Index: 2) 4. **use the right arm to pick up out a cut of bread.** (Index: 3) 5. **null.** (Index: 4) ### Atomic Actions - `grasp` - `place` - `pick` ## Hardware and Sensors ### Sensors - `cam_front_rgb` - `cam_left_wrist_rgb` - `cam_right_wrist_rgb` ### Camera Information - `cam_front_rgb`: dtype=video, shape=720x1280x3, resolution=1280x720, codec=av1, pix_fmt=yuv420p - `cam_left_wrist_rgb`: dtype=video, shape=720x1280x3, resolution=1280x720, codec=av1, pix_fmt=yuv420p - `cam_right_wrist_rgb`: dtype=video, shape=720x1280x3, resolution=1280x720, codec=av1, pix_fmt=yuv420p ### Coordinate System - **Definition:** `right-hand-frame` ### Dimensions & Units - **Joint Rotation:** `radian` ## Dataset Statistics | Metric | Value | |--------|-------| | **Total Episodes** | 588 | | **Total Frames** | 333147 | | **Total Tasks** | 5 | | **Total Videos** | 1764 | | **Total Chunks** | 1 | | **Chunk Size** | 1000 | | **FPS** | 30 | | **State Dimensions** | 14 | | **Action Dimensions** | 14 | | **Camera Views** | 3 | | **Dataset Size** | 15.15 GB | ## Data Splits The dataset is organized into the following splits: - **Training**: Episodes 0:587 ## Dataset Structure This dataset follows the LeRobot format and contains the following components: ### Data Files - **Videos**: Compressed video files containing RGB camera observations - **State Data**: Robot joint positions, velocities, and other state information - **Action Data**: Robot action commands and trajectories - **Metadata**: Episode metadata, timestamps, and annotations ### File Organization - **Data Path Pattern**: `data/chunk-{id}/episode_{id}.parquet` - **Video Path Pattern**: `videos/chunk-{id}/observation.images.cam_front_rgb/episode_{id}.mp{id}` - **Chunking**: Data is organized into 1 chunk(s) of size 1000 ### Data Structure (Tree) ``` Cobot_Magic_take_out_the_bread_qced_hardlink/ |-- annotations | |-- eef_acc_mag_annotation.jsonl | |-- eef_direction_annotation.jsonl | |-- eef_velocity_annotation.jsonl | |-- gripper_activity_annotation.jsonl | |-- gripper_mode_annotation.jsonl | |-- scene_annotations.jsonl | `-- subtask_annotations.jsonl |-- data | `-- chunk-000 | |-- episode_000000.parquet | |-- episode_000001.parquet | |-- episode_000002.parquet | |-- episode_000003.parquet | |-- episode_000004.parquet | |-- episode_000005.parquet | |-- episode_000006.parquet | |-- episode_000007.parquet | |-- episode_000008.parquet | |-- episode_000009.parquet | |-- episode_000010.parquet | `-- episode_000011.parquet | `-- ... (576 more entries) |-- meta | |-- episodes.jsonl | |-- episodes_stats.jsonl | |-- info.json | `-- tasks.jsonl |-- videos | `-- chunk-000 | |-- observation.images.cam_front_rgb | |-- observation.images.cam_left_wrist_rgb | `-- observation.images.cam_right_wrist_rgb `-- README.md ``` ## Camera Views This dataset includes 3 camera views: `cam_front_rgb`, `cam_left_wrist_rgb`, `cam_right_wrist_rgb`. ## Features (Full YAML) ```yaml observation.images.cam_front_rgb: dtype: video shape: - 720 - 1280 - 3 names: - height - width - channels info: video.height: 720 video.width: 1280 video.codec: av1 video.pix_fmt: yuv420p video.is_depth_map: false video.fps: 30 video.channels: 3 has_audio: false observation.images.cam_left_wrist_rgb: dtype: video shape: - 720 - 1280 - 3 names: - height - width - channels info: video.height: 720 video.width: 1280 video.codec: av1 video.pix_fmt: yuv420p video.is_depth_map: false video.fps: 30 video.channels: 3 has_audio: false observation.images.cam_right_wrist_rgb: dtype: video shape: - 720 - 1280 - 3 names: - height - width - channels info: video.height: 720 video.width: 1280 video.codec: av1 video.pix_fmt: yuv420p video.is_depth_map: false video.fps: 30 video.channels: 3 has_audio: false observation.state: dtype: float32 shape: - 14 names: - left_arm_joint_1_rad - left_arm_joint_2_rad - left_arm_joint_3_rad - left_arm_joint_4_rad - left_arm_joint_5_rad - left_arm_joint_6_rad - left_gripper_open - right_arm_joint_1_rad - right_arm_joint_2_rad - right_arm_joint_3_rad - right_arm_joint_4_rad - right_arm_joint_5_rad - right_arm_joint_6_rad - right_gripper_open action: dtype: float32 shape: - 14 names: - left_arm_joint_1_rad - left_arm_joint_2_rad - left_arm_joint_3_rad - left_arm_joint_4_rad - left_arm_joint_5_rad - left_arm_joint_6_rad - left_gripper_open - right_arm_joint_1_rad - right_arm_joint_2_rad - right_arm_joint_3_rad - right_arm_joint_4_rad - right_arm_joint_5_rad - right_arm_joint_6_rad - right_gripper_open timestamp: dtype: float32 shape: - 1 names: null frame_index: dtype: int64 shape: - 1 names: null episode_index: dtype: int64 shape: - 1 names: null index: dtype: int64 shape: - 1 names: null task_index: dtype: int64 shape: - 1 names: null subtask_annotation: names: null dtype: int32 shape: - 5 scene_annotation: names: null dtype: int32 shape: - 1 eef_sim_pose_state: names: - left_eef_pos_x - left_eef_pos_y - left_eef_pos_z - left_eef_ori_x - left_eef_ori_y - left_eef_ori_z - right_eef_pos_x - right_eef_pos_y - right_eef_pos_z - right_eef_ori_x - right_eef_ori_y - right_eef_ori_z dtype: float32 shape: - 12 eef_sim_pose_action: names: - left_eef_pos_x - left_eef_pos_y - left_eef_pos_z - left_eef_ori_x - left_eef_ori_y - left_eef_ori_z - right_eef_pos_x - right_eef_pos_y - right_eef_pos_z - right_eef_ori_x - right_eef_ori_y - right_eef_ori_z dtype: float32 shape: - 12 eef_direction_state: names: - left_eef_direction - right_eef_direction dtype: int32 shape: - 2 eef_direction_action: names: - left_eef_direction - right_eef_direction dtype: int32 shape: - 2 eef_velocity_state: names: - left_eef_velocity - right_eef_velocity dtype: int32 shape: - 2 eef_velocity_action: names: - left_eef_velocity - right_eef_velocity dtype: int32 shape: - 2 eef_acc_mag_state: names: - left_eef_acc_mag - right_eef_acc_mag dtype: int32 shape: - 2 eef_acc_mag_action: names: - left_eef_acc_mag - right_eef_acc_mag dtype: int32 shape: - 2 gripper_open_scale_state: names: - left_gripper_open_scale - right_gripper_open_scale dtype: float32 shape: - 2 gripper_open_scale_action: names: - left_gripper_open_scale - right_gripper_open_scale dtype: float32 shape: - 2 gripper_mode_state: names: - left_gripper_mode - right_gripper_mode dtype: int32 shape: - 2 gripper_mode_action: names: - left_gripper_mode - right_gripper_mode dtype: int32 shape: - 2 gripper_activity_state: names: - left_gripper_activity - right_gripper_activity dtype: int32 shape: - 2 ``` ## Available Annotations This dataset includes rich annotations to support diverse learning approaches: - `eef_acc_mag_annotation.jsonl` - `eef_direction_annotation.jsonl` - `eef_velocity_annotation.jsonl` - `gripper_activity_annotation.jsonl` - `gripper_mode_annotation.jsonl` - `scene_annotations.jsonl` - `subtask_annotations.jsonl` ## Dataset Tags - `RoboCOIN` - `LeRobot` ## Authors ### Contributors This dataset is contributed by:-RoboCOIN Team at Beijing Academy of Artificial Intelligence (BAAI) ### Annotators No annotator information available. ## Links - **Homepage:** [https://flagopen.github.io/RoboCOIN/](https://flagopen.github.io/RoboCOIN/) - **Paper:** [https://arxiv.org/abs/2511.17441](https://arxiv.org/abs/2511.17441) - **Repository:** [https://github.com/FlagOpen/RoboCOIN](https://github.com/FlagOpen/RoboCOIN) ## Contact and Support For questions, issues, or feedback regarding this dataset, please contact us. ### Support For technical support, please open an issue on our GitHub repository. ## License apache-2.0 ## Citation If you use this dataset in your research, please cite: ```bibtex @article{robocoin, title={RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation}, author={Shihan Wu, Xuecheng Liu, Shaoxuan Xie, Pengwei Wang, Xinghang Li, Bowen Yang, Zhe Li, Kai Zhu, Hongyu Wu, Yiheng Liu, Zhaoye Long, Yue Wang, Chong Liu, Dihan Wang, Ziqiang Ni, Xiang Yang, You Liu, Ruoxuan Feng, Runtian Xu, Lei Zhang, Denghang Huang, Chenghao Jin, Anlan Yin, Xinlong Wang, Zhenguo Sun, Junkai Zhao, Mengfei Du, Mingyu Cao, Xiansheng Chen, Hongyang Cheng, Xiaojie Zhang, Yankai Fu, Ning Chen, Cheng Chi, Sixiang Chen, Huaihai Lyu, Xiaoshuai Hao, Yequan Wang, Bo Lei, Dong Liu, Xi Yang, Yance Jiao, Tengfei Pan, Yunyan Zhang, Songjing Wang, Ziqian Zhang, Xu Liu, Ji Zhang, Caowei Meng, Zhizheng Zhang, Jiyang Gao, Song Wang, Xiaokun Leng, Zhiqiang Xie, Zhenzhen Zhou, Peng Huang, Wu Yang, Yandong Guo, Yichao Zhu, Suibing Zheng, Hao Cheng, Xinmin Ding, Yang Yue, Huanqian Wang, Chi Chen, Jingrui Pang, YuXi Qian, Haoran Geng, Lianli Gao, Haiyuan Li, Bin Fang, Gao Huang, Yaodong Yang, Hao Dong, He Wang, Hang Zhao, Yadong Mu, Di Hu, Hao Zhao, Tiejun Huang, Shanghang Zhang, Yonghua Lin, Zhongyuan Wang and Guocai Yao}, journal={arXiv preprint arXiv:2511.17441}, url = {https://arxiv.org/abs/2511.17441}, year={2025}, } ``` ### Additional References If you use this dataset, please also consider citing: LeRobot Framework: https://github.com/huggingface/lerobot ## Version Information Initial Release