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README.md

Flight Data

Raw data from the three V3 flights reported in the dissertation. Each flight followed an identical four-leg lawn-mower pattern (4 lanes × 25 m, 8 m altitude, ~128 s duration, ~289 m path length) over the same procedurally-generated 97-obstacle orchard world. The only varying parameter was Gazebo scene lighting.

Flight conditions

Flight Directory Sun elevation Label
A flight_A_noon/ 60° Baseline — noon
B flight_B_dusk/ 20° Reduced contrast — dusk
C flight_C_dawn/ 10° Low contrast — dawn

Files per flight

  • gps_trajectory.csv — ground-truth trajectory from PX4 via pymavlink, 20 Hz. Columns: timestamp, N (m), E (m), D (m), velocity components, attitude (roll/pitch/yaw).
  • cloud.pcd — dense RTAB-Map point cloud. Binary PCD format. Can be viewed with PCL tools or CloudCompare.
  • features.png — feature-tracker visualisation showing the KLT-tracked feature points during flight.
  • gazebo_scene.png — screenshot of the Gazebo scene at mission time.
  • rtabmap_cloud.png — rendered view of the dense point cloud in RViz.
  • metrics.json — pipeline throughput statistics (camera Hz, feature tracker Hz, VINS odometry Hz).
  • fly.log — mission execution log from fly_mission.py.
  • summary.json — flight summary (duration, lanes, cruise altitude).
  • best10.mp4 — short video clip of the flight.

Key findings visible in this data

  • Flight A: 6.47 m endpoint drift, 2.18 M RTAB-Map points
  • Flight B: 7.86 m endpoint drift, 2.01 M RTAB-Map points
  • Flight C: 34.45 m endpoint drift, 2.22 M RTAB-Map points

The 5.3× drift amplification (A → C) with near-identical point cloud density confirms the combined-architecture thesis: VINS-Fusion degrades with lighting, RTAB-Map does not.

See ../analysis/ for derived metrics and per-flight plots.