license: mit
task_categories:
- robotics
tags:
- drone
- ballistics
- ball-drop
- simulation
- domain-randomization
pretty_name: HoverDrop Ballistic Drop Dataset
size_categories:
- 1K<n<10K
HoverDrop Ballistic Drop Dataset
Simulated point-mass ball drops for the ballistics half of LeDrone Track B (hoverdrop). Each record is one drop: the conditions a release is solved from, the resulting landing, and a top-down camera frame rendered at the release pose.
- 5,000 drops total — Train: 4,000 (16 shards) · Val: 500 (2) · Test: 500 (2)
- Frames:
128x128x3uint8, one per drop.
How it was generated
A point mass with quadratic air drag in wind-relative air is integrated
(semi-implicit Euler, 200 Hz) from a release state down to a flat ground plane.
Conditions are randomized per drop: altitude AGL U[5,40] m; 40% exact hover and
the rest moving (U[0.5,12] m/s horizontal at a random heading + U[-2,2] m/s
vertical); wind U[0,8] m/s horizontal at a random heading + U[-0.5,0.5]
vertical. The ball's mass (±10%) and drag coefficient (±20%) are randomized but
not recorded in the model inputs — this unobserved variation sets the
irreducible landing-error floor. The top-down frame is a nadir pinhole render
over a procedural trajplanner terrain map (seed varies per drop). Sim only; no
real flight data.
Schema
Compressed .npz shards {split}_{id}.npz, one row per drop, deterministic
80/10/10 split by shard id:
| array | shape | dtype | meaning |
|---|---|---|---|
inputs |
(n, 7) |
float32 | [altitude_agl, vx,vy,vz, wx,wy,wz] (DropNet inputs) |
label |
(n, 3) |
float32 | [dx, dy, fall_time] landing offset + fall time |
traj |
(n, L, 3) |
float32 | 20 Hz ball trajectory (padded) |
traj_len |
(n,) |
int32 | valid trajectory length |
ball |
(n, 3) |
float32 | TRUE ball params [mass, cd, radius] (unobserved) |
drone_state |
(n, 18) |
float32 | release pose the frame is rendered from |
target_xyz |
(n, 3) |
float32 | true landing point (drawn disc) |
map_seed |
(n,) |
int32 | synthetic terrain seed |
frames |
(n, 128, 128, 3) |
uint8 | top-down render at release |
Usage
pip install "hoverdrop[hf] @ git+https://github.com/edgarmoreaualix/LeDrone.git#subdirectory=hoverdrop"
python scripts/download_dataset_hf.py --repo-id Ethgar/hoverdrop-drops-5k --out-dir data/drops5k
from hoverdrop.drops import DropDataset
ds = DropDataset("data/drops5k", split="train", load_frames=False) # DropNet training
x, y = ds[0] # inputs (7,), label (3,)
rec = DropDataset("data/drops5k", "test", load_frames=True).record(0) # + frame
License
MIT. Independent clean-room simulation; not affiliated with any third party.