聚焦于能量高效和合作策略的无人机覆盖路径规划方法。

Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles.

机构信息

Department of Computer Science, International Hellenic University, 65404 Kavala, Greece.

Department of Networks and Digital Media, Kingston University, Surrey KT1 2EE, UK.

出版信息

Sensors (Basel). 2022 Feb 6;22(3):1235. doi: 10.3390/s22031235.

DOI:10.3390/s22031235

PMID:35161979

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8839296/

Abstract

The coverage path planning (CPP) algorithms aim to cover the total area of interest with minimum overlapping. The goal of the CPP algorithms is to minimize the total covering path and execution time. Significant research has been done in robotics, particularly for multi-unmanned unmanned aerial vehicles (UAVs) cooperation and energy efficiency in CPP problems. This paper presents a review of the early-stage CPP methods in the robotics field. Furthermore, we discuss multi-UAV CPP strategies and focus on energy-saving CPP algorithms. Likewise, we aim to present a comparison between energy efficient CPP algorithms and directions for future research.

摘要

覆盖路径规划（CPP）算法旨在以最小的重叠覆盖全部感兴趣区域。CPP 算法的目标是最小化总覆盖路径和执行时间。在机器人领域，尤其是在多架无人机（UAV）合作和 CPP 问题中的能量效率方面，已经进行了大量研究。本文回顾了机器人领域早期的 CPP 方法。此外，我们还讨论了多架 UAV 的 CPP 策略，并重点介绍了节能 CPP 算法。同样，我们旨在对节能 CPP 算法进行比较，并为未来的研究指明方向。