Unmanned aircraft or drones as they are sometimes called are continuing to become part of more real-life applications. The integration of unmanned aerial vehicles in public airspace is becoming an important issue that should be addressed. As the number of unmanned aerial vehicles and their applications are largely increasing, air traffic with more unmanned aircraft has to be given more attention to prevent collisions and maintain safe skies. Unmanned aerial vehicle air traffic integration and regulation has become a priority to different regulatory agencies and has become of greater interest for many researchers all around the world. In this research, a sampling-based air traffic integration, path planning, and collision avoidance approach is presented. The proposed algorithm expands an existing 2D sampling-based approach. The original 2D approach deals with only two unmanned aircraft. Each of the two aircraft shares location information with a ground-based path planner computer, which would send back the avoidance waypoints after performing the 2D sampling. The algorithm proposed in this article can handle any number of drones in the 3D space by performing either 2D or 3D sampling. The proposed work shows a 10-fold enhancement in terms of the number of unmanned aerial vehicle collisions. The presented results also contribute to enabling a better understanding of what is expected of integrating more drones in dense skies.

One of the most significant disadvantages of electric multirotor unmanned aerial vehicles is their short flight time compared to fuel-powered unmanned aerial vehicles. This is mainly due to the low energy density of electric batteries. Fuel has much more energy density when compared to batteries. Electric-powered motors in multirotor unmanned aerial vehicles cannot be replaced with fuel-based engines because the stability and control of multirotor unmanned aerial vehicles rely on the high response rates of electric motors. One of the possible solutions to overcome this problem of short endurance times is by using hybrid thrusting systems that combine the advantages of both fuel and electrical propulsion systems, where high maneuverability and long endurance flight time could be achieved. In this work, hybrid thrusting and power systems for multirotor unmanned aerial vehicles are studied. Targeted hybrid thrusting systems consist of combustion engines, electric motors, and their power sources. Then a hybrid thrusting system-based quadrotor unmanned aerial vehicle model is developed. The article presents the altitude and attitude control systems of the developed hybrid thrusting system-based unmanned aerial vehicle. The presented hybrid quadcopter model comprises four electric motors and one fuel engine. The fuel engine used in this work is a 4.07 cc internal combustion engine targeting 2–3 kg unmanned aerial vehicles with up to 5 kg maximum takeoff weight. The developed hybrid quadrotor unmanned aerial vehicle achieved a 139% improvement in flight time when compared with traditional electric-based quadrotor unmanned aerial vehicles. The article also reports on other flight time-related issues such as the optimal fuel mass to battery size ratio to maximize the endurance time of the quadrotor unmanned aerial vehicles.