The objective of the PTTI-ILUV “Intelligent Landing of Unmanned (Aerial) Vehicles” was to assess the applicability of a site selection landing algorithm developed by UNINOVA for ESA spacecraft, and using it for the autonomous landing of a micro-UAV. This algorithm provides Hazard Detection and Avoidance capabilities, using hazard maps such as texture, slope, illumination etc. as decision criteria allowing autonomous landing site selection, applicable in nominal or emergency landing situations.
UNINOVA’s Computational Intelligence Research Group (CA3) teamed up with Spin.Works, a Portuguese SME developing UAV’s (Unmanned Aerial Vehicles) with embedded guidance, navigation and control systems, to perform this feasibility study. The study involved slight adaptations of the space-oriented algorithm to the realities of a UAV. Changes included adapting to a more horizontal landing scenario and considering factors such as wind, with very positive results being successfully demonstrated in the context of this PTTI project.
The use of UAV’s by civil users benefits from increased safety, security and efficiency. Having a mechanism for autonomous landing in emergency situations such as engine failure, minimizes the risks for people or property on the ground, while also maximizing the probability of recovering the aircraft intact, thereby reducing inherent costs. It provides added value to current UAV’s, bringing increased confidence in (semi)autonomous aerial vehicles. From an operational perspective, by having this extra level of autonomy, in particular at the landing phase, it is possible to achieve a reduction in operational costs, since the most significant cost in micro UAV operations is the operator cost.
As a result of the study, we showed that the adaptation of the space-based algorithm provides a clear benefit to the task of UAV landings, with the ILUV project providing a step forward in achieving an autonomous aerial vehicle.