As part of our Managed Services Contract we started to develop more advanced flight planning functionality for Skippy Scout that would be computed in the cloud pre-flight.
Having an accurate, efficient, and safe flight plan is the core of this project. For the drones to autonomously visit the scout points marked in the field, they need to determine the best path between sequential points, working out a route that minimises travel time. This is especially important as drones have a limited battery life of around 30 minutes and some fields can be very large.
To do this, we split the space into flyable and non-flyable areas in 3D space. Then a route-finding algorithm was employed to determine the most efficient order in which the drone should visit the scout points before a pathfinding algorithm determined which cubes the drone should pass through whilst moving between the scout points.
Flight and trajectory planning between the scout points gives smooth arcs of flight. An efficient, well planned route, especially for surveying large fields, means that the drone can complete all inspection points without having to return for time-consuming recharging.
As well as developing and testing the new flight planning methods, we continue to make many enhancements to Skippy Scout as part of our Managed Services Contract (many of which we can’t reveal here), including:
- AI analysis on the images taken by the drone to measure leaf count and stone coverage and to gauge the health of crops
- Integration of additional third-party providers, including satellite imagery to give readings on the Normalized Difference Vegetation Index (NDVI) for the crops and prove richer overlays on the field reports
Looking ahead, there are also numerous new and exciting improvements to come.