Update README.md

README.md

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 ---
 license: apache-2.0
+tags:
+- '- spacecraft'
+- '- obstacle-avoidance'
+- '- world-models'
+- '- isaac-sim'
+- '- trajectory-prediction'
+pretty_name: Orbit-Planner Orbital Evasion Dataset
 ---
+---
+pretty_name: Orbit-Planner Orbital Evasion Dataset
+task_categories:
+  - robotics
+  - reinforcement-learning
+tags:
+  - spacecraft
+  - obstacle-avoidance
+  - world-models
+  - multimodal
+  - trajectory-prediction
+  - isaac-sim
+  - hdf5
+---
+
+# Orbit-Planner Orbital Evasion Dataset
+
+<p align="center">
+  <a href="https://arxiv.org/abs/0000.00000"><img src="https://img.shields.io/badge/arXiv-Paper-B31B1B?logo=arxiv&logoColor=white" alt="ArXiv Paper"></a>
+  <a href="https://github.com/ZhijianLi2003/Orbit_Planner"><img src="https://img.shields.io/badge/GitHub-Code-181717?logo=github&logoColor=white" alt="GitHub Code"></a>
+  <a href="https://zhijianli2003.github.io/Orbit_Planner/"><img src="https://img.shields.io/badge/Project-Page-0A7EA4?logo=googlechrome&logoColor=white" alt="Project Page"></a>
+</p>
+
+Orbit-Planner is a simulated multimodal trajectory dataset for vision-based
+spacecraft navigation and obstacle avoidance. It contains synchronized
+first-person RGB images, depth maps, spacecraft states, thruster commands, and
+event labels collected in the Orbital Evasion task from Space Robotics Bench
+and NVIDIA Isaac Sim.
+
+The dataset is intended for learning latent world models, spacecraft dynamics,
+visual representations, imitation policies, and collision-aware planning. Its
+trajectories cover successful obstacle avoidance, direct high-risk flight, and
+open-loop exploration, providing both task-oriented behavior and diverse
+spacecraft dynamics.
+
+## Dataset at a Glance
+
+| Property | Value |
+| --- | ---: |
+| Number of trajectories | 8,000 |
+| Total time steps | 2,114,895 |
+| Time between consecutive frames | 0.04 s (25 Hz) |
+| Average steps per trajectory | 264.36 |
+| Trajectories with success events | 3,437 |
+| Trajectories with collision events | 1,530 |
+| State dimension | 16 |
+| Action dimension | 8 |
+| Event dimension | 2 |
+| RGB resolution | 224 x 224 x 3 |
+| Depth resolution | 224 x 224 |
+
+The dataset contains the following collection strategies:
+
+| Strategy | Trajectories | Description |
+| --- | ---: | --- |
+| `expert` | 5,601 | RRT* obstacle-avoiding path planning followed by path smoothing and PD tracking. |
+| `risky` | 1,578 | Direct flight toward the target without obstacle-avoiding path planning. |
+| `explore` | 821 | Segmented near-open-loop force, torque, combined-control, and coasting behavior. |
+
+## Data Generation
+
+Each episode starts with the spacecraft at the local origin with identity
+orientation and zero velocity. The target and 14 obstacles are randomized for
+each trajectory. In the released configuration, obstacles are placed around
+the start-to-target corridor and may drift during an episode. The onboard
+camera follows the spacecraft attitude and looks along the body-frame `-Z`
+axis.
+
+Expert trajectories use RRT* with a 1.2 m planning clearance, shortcut-based
+path smoothing, waypoint resampling, and closed-loop PD path tracking. Risky
+trajectories fly directly toward the target. Exploration trajectories use
+near-open-loop control segments to increase translational and rotational
+dynamics diversity.
+
+The maximum episode length is 300 steps. A successful episode passes the
+target's z-plane while remaining within the configured lateral tolerance.
+Collision detection uses an impulse-based proxy: a collision is marked when
+the magnitude of the step-to-step change in world-frame linear velocity,
+`||v_t - v_{t-1}||`, exceeds 0.5 m/s. After the first detected collision,
+collection continues for 30 additional closed-loop steps so that post-impact
+dynamics are retained.
+
+## Data Structure
+
+The HDF5 data are organized as one group per trajectory:
+
+```text
+dataset.h5
++-- traj_0000/
+|   +-- states    [T, 16]          float64
+|   +-- actions   [T, 8]           float32
+|   +-- events    [T, 2]           float32
+|   +-- rgb       [T, 224, 224, 3] uint8
+|   +-- depth     [T, 224, 224]    uint8
++-- traj_0001/
+|   +-- ...
++-- ...
+```
+
+All arrays are gzip-compressed in the HDF5 file. The accompanying
+[`meta.json`](./meta.json) contains the full dataset configuration, feature
+definitions, aggregate statistics, and a trajectory-level index.
+
+### State
+
+The state vector is
+
+```text
+s_t = [p_t, v_t, rot6d_t, omega_t, phi_t]
+```
+
+| Slice | Size | Description |
+| --- | ---: | --- |
+| `p_t` (`0:3`) | 3 | Spacecraft displacement from its initial position in the world frame. |
+| `v_t` (`3:6`) | 3 | Linear velocity in the body frame. |
+| `rot6d_t` (`6:12`) | 6 | First two columns of the rotation matrix. |
+| `omega_t` (`12:15`) | 3 | Angular velocity in the body frame. |
+| `phi_t` (`15:16`) | 1 | Remaining fuel fraction in `[0, 1]`. |
+
+### Action
+
+The action vector contains normalized commands for eight spacecraft thrusters:
+
+```text
+a_t = [F1, F2, ..., F8],  a_t in [0, 1]^8
+```
+
+### Events
+
+The event vector is
+
+```text
+e_t = [collision, success]
+```
+
+`collision` is the event label intended for downstream use and marks steps
+where the velocity-based impulse proxy exceeds its configured threshold.
+`success` is retained only as a collection-time bookkeeping field and is not
+used by the current training or evaluation pipeline, so it can be ignored.
+Event values are binary and stored as `float32`.
+
+### Visual Observations
+
+Each step includes a first-person `uint8` RGB frame and a grayscale `uint8`
+depth frame. Depth values use an inverted encoding in which larger values are
+nearer. Convert a stored depth value `d` to meters with:
+
+```text
+depth_m = ((255 - d) / 255.0) * 50.0 + 0.1
+```
+
+The valid clipping range is 0.1 m to 50.1 m, and background space is encoded as
+zero.
+
+### Trajectory Metadata
+
+Each trajectory has an identifier and summary attributes including
+`total_steps`, `has_collision`, `has_success`, `terminated`, `truncated`,
+`target_pos`, `strategy`, and `collision_step`. A `collision_step` value of
+`-1` means that no collision was detected; otherwise, it identifies the first
+collision frame.
+
+## Intended Uses
+
+This dataset is suitable for:
+
+- multimodal and latent spacecraft world models;
+- visual dynamics and future-state prediction;
+- imitation learning and offline reinforcement learning;
+- obstacle-avoidance planning and control;
+- collision prediction and post-impact dynamics modeling;
+- benchmarking state, depth, and action representation learning.
+
+Trajectory-level splits should be used to prevent adjacent frames from the same
+episode from appearing in both training and evaluation sets.
+
+## Limitations
+
+The data are generated entirely in simulation and do not capture every source
+of real spacecraft sensor noise, actuator uncertainty, illumination variation,
+or contact dynamics. Behavior comes from scripted expert, risky, and exploration
+controllers rather than human demonstrations. Collision labels are based on a
+velocity-change threshold, so they should not be treated as direct contact
+sensor measurements. The strategy and outcome distributions are also
+imbalanced and should be considered when constructing evaluation splits.