Energy optimal 3D flight path planning for unmanned aerial vehicle in urban environments

Abstract

This paper presents a general approach to compute energy optimal flight paths for unmanned aerial vehicle (UAV) in urban environments. To minimize the energy required, the flight path is optimized by exploiting local wind phenomena, i.e., upwind and tailwind areas from the airflow around buildings. A realistic wind field of a model urban environment typical for continental Europe is generated using PALM, a Large Eddy Simulation tool. The calculated wind field feeds into the flight path planning algorithm to minimize the energy required. A specifically tailored A-Star-Algorithm is used to optimize flight trajectories. The approach is demonstrated on a delivery UAV benchmark scenario. Energy optimal flight paths are compared to shortest way trajectories for 12 different scenarios. It is shown that energy can be saved significantly while flying in a city using knowledge of the current wind field.

A Review of Developments and Challenges of Preflight Preparation for Data Collection of UAV-based Infrastructure Inspection

“…The principles for both methods are almost similar but it's worth noting that in the past years, some research has explored autonomous flight path planning [27,34,76,77]. Obstacle avoidance especially in urban environments, multi-UAV path planning, and coverage path planning in 3D space are some of the challenges related to auto flight and some studies focused on addressing these issues [78][79][80]. Online or real-time path generation is another challenging area where the path is generated dynamically based on the data collected from the sensors and it is hard to ensure a sub-optimal path for this type of path generation.…”