Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil.
Department of Electronics Engineering, Federal Center for Technological Education of Rio de Janeiro, Rio de Janeiro 20271-110, Brazil.
Sensors (Basel). 2021 Feb 5;21(4):1108. doi: 10.3390/s21041108.
Path planning is one of the most important issues in the robotics field, being applied in many domains ranging from aerospace technology and military tasks to manufacturing and agriculture. Path planning is a branch of autonomous navigation. In autonomous navigation, dynamic decisions about the path have to be taken while the robot moves towards its goal. Among the navigation area, an important class of problems is Coverage Path Planning (CPP). The CPP technique is associated with determining a collision-free path that passes through all viewpoints in a specific area. This paper presents a method to perform CPP in 3D environment for Unmanned Aerial Vehicles (UAVs) applications, namely 3D dynamic for CPP applications (3DD-CPP). The proposed method can be deployed in an unknown environment through a combination of linear optimization and heuristics. A model to estimate cost matrices accounting for UAV power usage is proposed and evaluated for a few different flight speeds. As linear optimization methods can be computationally demanding to be used on-board a UAV, this work also proposes a distributed execution of the algorithm through fog-edge computing. Results showed that 3DD-CPP had a good performance in both local execution and fog-edge for different simulated scenarios. The proposed heuristic is capable of re-optimization, enabling execution in environments with local knowledge of the environments.
路径规划是机器人学领域最重要的问题之一，广泛应用于从航空航天技术和军事任务到制造和农业等多个领域。路径规划是自主导航的一个分支。在自主导航中，机器人向其目标移动时，必须对路径做出动态决策。在导航领域中，一个重要的问题类别是覆盖路径规划 (CPP)。CPP 技术与确定无碰撞路径相关，该路径要通过特定区域中的所有视点。本文提出了一种在 3D 环境中为无人机 (UAV) 应用执行 CPP 的方法，即用于 CPP 应用的 3D 动态 (3DD-CPP)。该方法可以通过线性优化和启发式算法的组合在未知环境中部署。本文还提出了一种用于估计考虑无人机功耗的成本矩阵的模型，并针对几种不同的飞行速度进行了评估。由于线性优化方法在计算上可能难以在无人机上使用，因此这项工作还通过雾边缘计算提出了算法的分布式执行。结果表明，3DD-CPP 在不同模拟场景的本地执行和雾边缘计算中都具有良好的性能。所提出的启发式方法能够进行重新优化，从而能够在具有环境局部知识的环境中执行。
