Energy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation


This paper presents a new Coverage Path Planning (CPP) method for an aerial imaging mission with multiple Unmanned Aerial Vehicles (UAVs). In order to solve a CPP problem with multicopters, a typical mission profile can be defined with five mission segments: takeoff, cruise, hovering, turning, and landing. The traditional arc-based optimization approaches for the CPP problem cannot accurately estimate actual energy consumption to complete a given mission because they cannot account for turning phases in their model, which may cause non-feasible routes. To solve the limitation of the traditional approaches, this paper introduces a new route-based optimization model with column generation that can trace the amount of energy required for all different mission phases. This paper executes numerical simulations to demonstrate the effectiveness of the proposed method for both a single UAV and multiple UAV scenarios for CPP problems.

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This paper is a major enhancement of the ICUAS 2018 accepted paper.

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Correspondence to Younghoon Choi.

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Choi, Y., Choi, Y., Briceno, S. et al. Energy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation. J Intell Robot Syst 97, 125–139 (2020).

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  • Coverage path planning
  • Multi-UAV missions
  • Column generation
  • Energy-constrained optimization