TerraSentia (wheeled robot) navigation trajectories from ROS bags, packaged in a schema mirroring adipotnis/scand-polyline. Each row is one image frame paired with a 60-waypoint future trajectory (next 15 m of EKF odom sampled at 0.25 m steps), projected into the ZED camera as a pixel-space polyline and rendered as an overlay PNG.

Summary

Total samples: 108491
Bags: 22
Frames flagged collision: 57156 (52.7%)
Frames flagged reversing: 28860 (26.6%)
Distinct collision events across all bags: 6057

Schema

Field	Type	Notes
`traj_id`	string	bag stem
`robot`	string	constant `"Wheeled Robot"`
`run_id`	int32	per-bag index
`sub_id`	int32	`0` (schema parity with scand-polyline)
`n_frames`	int32	total frames in this bag
`frame_idx`	int32	per-bag frame index
`prefix`	string	same as `traj_id`
`image`	Image	rectified ZED left frame
`image_overlay`	Image	same frame with projected polyline drawn
`embodiments`	List[string]	`["Wheeled Robot"]`
`polyline_xy`	List[List[float64,2]]	projected pixel polyline (in-image segment)
`traj`	List[List[float64,3]]	up to 60 base-frame waypoints (next 15 m @ 0.25 m)
`ground_truth`	dict	`{"Wheeled Robot": [polyline_xy]}`
`image_width` / `image_height`	int64	rectified frame dims
`collision`	bool	EKF speed drop in next 5 s (and not reversing)
`reversing`	bool	sustained reverse motion in next 5 s

Per-bag top-view maps

Forward motion in green, reverse motion in blue, detected collision events as red dots.

`ts_2023_04_10_20h05m59s_filtered`

frames: 4334 · collision frames: 3089 · reversing frames: 1682 · collision events: 320

`ts_2023_04_10_20h12m46s_filtered`

frames: 4508 · collision frames: 2687 · reversing frames: 1960 · collision events: 316

`ts_2023_04_11_17h47m24s_filtered`

frames: 2276 · collision frames: 1112 · reversing frames: 616 · collision events: 134

`ts_2023_04_11_17h51m03s`

frames: 6077 · collision frames: 3277 · reversing frames: 1130 · collision events: 298

`ts_2023_04_11_17h53m56s_filtered`

frames: 6478 · collision frames: 3325 · reversing frames: 1727 · collision events: 416

`ts_2023_04_11_17h58m32s`

frames: 9979 · collision frames: 4918 · reversing frames: 1840 · collision events: 493

`ts_2023_04_11_18h00m20s`

frames: 7276 · collision frames: 3524 · reversing frames: 1855 · collision events: 338

`ts_2023_04_11_18h02m48s_filtered`

frames: 6799 · collision frames: 3194 · reversing frames: 1951 · collision events: 414

`ts_2023_04_11_18h13m59s`

frames: 2983 · collision frames: 1297 · reversing frames: 537 · collision events: 120

`ts_2023_04_11_19h57m53s`

frames: 3693 · collision frames: 1687 · reversing frames: 950 · collision events: 135

`ts_2023_04_11_20h02m40s`

frames: 2022 · collision frames: 708 · reversing frames: 484 · collision events: 41

`ts_2023_06_25_20h32m20s`

frames: 6417 · collision frames: 3838 · reversing frames: 2181 · collision events: 417

`ts_2023_06_25_23h24m19s`

frames: 5280 · collision frames: 2955 · reversing frames: 1463 · collision events: 360

`ts_2023_06_25_23h34m37s`

frames: 7269 · collision frames: 3477 · reversing frames: 1706 · collision events: 306

`ts_2023_06_25_23h56m10s`

frames: 2050 · collision frames: 1391 · reversing frames: 491 · collision events: 337

`ts_2023_06_25_23h56m47s`

frames: 6002 · collision frames: 2645 · reversing frames: 1528 · collision events: 213

`ts_2023_06_26_00h04m16s`

frames: 973 · collision frames: 437 · reversing frames: 141 · collision events: 44

`ts_2023_06_26_00h05m52s`

frames: 2383 · collision frames: 1319 · reversing frames: 505 · collision events: 153

`ts_2023_06_26_00h05m58s`

frames: 4621 · collision frames: 2681 · reversing frames: 1482 · collision events: 245

`ts_2023_06_26_00h14m59s`

frames: 1989 · collision frames: 1204 · reversing frames: 564 · collision events: 159

`ts_2023_06_26_00h15m21s`

frames: 7259 · collision frames: 3984 · reversing frames: 1992 · collision events: 377

`ts_2023_06_26_00h25m04s`

frames: 7823 · collision frames: 4407 · reversing frames: 2075 · collision events: 421

Detection heuristics

All event detection runs on the EKF stream using msg.header.stamp — the rosbag receipt timestamps for /terrasentia/ekf are batched in microseconds and don't reflect the true ~100 Hz sample times. The window is the 5 s of EKF following the frame.

Currently applied (Option B — sharp-decel collision, both flags independent):

reversing: signed velocity along robot heading is < -0.05 m/s for more than 30 % of segments in the window.
collision: speed transitions from > 0.5 m/s to < 0.1 m/s within 0.3 s anywhere in the window. The two flags are not mutually exclusive — a bump-then-back-up event fires both.

Alternative considered (Option A — strict, with mutual exclusivity):

reversing: same as above.
collision: speed transitions from > 0.5 m/s to < 0.05 m/s within 0.5 s, and stays below 0.05 m/s for at least 1.0 s, and the frame is not also reversing. On TerraSentia teleop this leaves collision=True for the rare truly-stuck events; most bumps were labeled reversing=True only.

Built with datasets/ts_data/bags_to_hf_polyline.py.

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Total file size:

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