Energy-Aware Spiral Coverage Path Planning for UAV Photogrammetric Applications

Most unmanned aerial vehicles nowadays engage in coverage missions using simple patterns, such as back-and-forth and spiral. However, there is no general agreement about which one is more appropriate. This letter proposes an E-Spiral algorithm for accurate photogrammetry that considers the camera sensor and the flight altitude to apply the overlapping necessary to guarantee the mission success. The algorithm uses an energy model to set different optimal speeds for straight segments of the path, reducing the energy consumption. We also propose an improvement for the energy model to predict the overall energy of the paths. We compare E-Spiral and E-BF algorithms in simulations over more than 3500 polygonal areas with different characteristics, such as vertices, irregularity, and size. Results showed that E-Spiral outperforms E-BF in all the cases, providing an effective energy saving even in the worst scenario with a percentage improvement of <inline-formula><tex-math notation="LaTeX">$10.37\%$</tex-math> </inline-formula> up to the best case with <inline-formula><tex-math notation="LaTeX">$\text{16.1}\%$</tex-math> </inline-formula> of improvement. Real flights performed with a quadrotor state the effectiveness of the E-Spiral over E-BF in two areas, presenting an improvement of <inline-formula><tex-math notation="LaTeX">$\text{9}\%$</tex-math> </inline-formula> in the time and <inline-formula><tex-math notation="LaTeX">$\text{7.7}\%$</tex-math></inline-formula> in the energy. The improved energy model increases the time and the energy estimation precision of <inline-formula> <tex-math notation="LaTeX">$\text{13.24}\%$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX"> $\text{13.41}\%$</tex-math></inline-formula>, respectively.