Minimum Energy Wind Dependent Optimised Path Generation for Multirotors

High wind environments can have a dramatic impact on the battery life of Unmanned Aerial Systems (UAS), particularly on smaller vehicles. Through the use of on-board sensors, the wind speeds experienced throughout flight can be determined, allowing improved flight path planning based on this knowledge. With missions involving higher altitude flight such as meteorological data, and atmospheric gas sampling, greater wind speeds will be experienced than in lower altitude operations, increasing the need for them to be considered when determining flight paths. Previous work focused on wind estimation and optimal path generation to ensure stability in vertical descent. This paper will expand on the previous work by opening up the optimal path generation to other conditions outside of vertical descents. Using the approximations gathered throughout flight we are able to optimise a minimum energy trajectory based on the expected wind conditions. Doing this will improve the mission performance allowing for increased sampling time or range from the home position. It also has the potential to ensure that a vehicle can autonomously return to the home location in case of strong winds where, under current approaches, an autonomous return may be impossible.