Experimental Evaluation of Multi- and Single-Drone Systems with 1D LiDAR Sensors for Stockpile Volume Estimation

Alsayed, Ahmad; Bana, Fatemeh; Arvin, Farshad; Quinn, Mark K.; Nabawy, Mostafa R. A.

Abstract

This study examines the application of low-cost 1D LiDAR sensors in drone-based stockpile volume estimation, with a focus on indoor environments. Three approaches were experimentally investigated: (i) a multi-drone system equipped with static, downward-facing 1D LiDAR sensors combined with an adaptive formation control algorithm; (ii) a single drone with a static, downward-facing 1D LiDAR following a zigzag trajectory; and (iii) a single drone with an actuated 1D LiDAR in an oscillatory fashion to enhance scanning coverage while following a shorter trajectory. The adaptive formation control algorithm, newly developed in this study, synchronises the drones’ waypoint arrivals and facilitates smooth transitions between dynamic formation shapes. Real-world experiments conducted in a motion-tracking indoor facility confirmed the effectiveness of all three approaches in accurately completing scanning tasks, as per intended waypoints allocation. A trapezoidal prism stockpile was scanned, and the volume estimation accuracy of each approach was compared. The multi-drone system achieved an average volumetric error of 1.3%, similar to the single drone with a static sensor, but with less than half the flight time. Meanwhile, the actuated LiDAR system required shorter paths but experienced a higher volumetric error of 4.4%, primarily due to surface reconstruction outliers and common LiDAR bias when scanning at non-vertical angles.

Citation

Alsayed, A., Bana, F., Arvin, F., Quinn, M. K., & Nabawy, M. R. A. (2025). Experimental Evaluation of Multi- and Single-Drone Systems with 1D LiDAR Sensors for Stockpile Volume Estimation. Aerospace, 12(3), Article 189. https://doi.org/10.3390/aerospace12030189

• Journal Article Type: Article
• Acceptance Date: Feb 24, 2025
• Online Publication Date: Feb 26, 2025
• Publication Date: Mar 1, 2025
• Deposit Date: Mar 19, 2025
• Publicly Available Date: Mar 19, 2025
• Journal: Aerospace
• Electronic ISSN: 2226-4310
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 3
• Article Number: 189
• DOI: https://doi.org/10.3390/aerospace12030189
• Keywords: drones, volume estimation, 1D LiDAR, formation control, indoor missions, stockpile modelling, swarms, confined spaces
• Public URL: https://durham-repository.worktribe.com/output/3714788