A “zero-sum game” is a game in which a participant’s gain or loss is balanced against the gains or losses of the other participants. Thus, if all gains are added and all losses are subtracted, the result is always zero. Typical examples of this include chess, poker, bingo, lotteries, basketball, football and, in general, all games where one player takes what the other players lose, or where one party is required to lose for the other to win.
The design of an UAS must be fully focused on a specific mission to ensure the viability of the missions it carries out.
Similarly, situations where the same zero-sum principles occur can also be considered zero-sum systems; that is, situations where all gains introduced into one part of the system must be automatically translated into losses in another part of the system.
UAVs/RPAS/drones are perfect examples of zero-sum systems. In other words, any improvement that we try to introduce into a closed aeronautical system will generate a negative or unwanted trade-off elsewhere in the system.
The reason an UAS is automatically a zero-sum system is because it is critically immersed under the permanent influence of Earth´s attraction. This is critical because in order to operate while under the influence of gravity, the UAS must constantly overcome it —or at least neutralise it. The moment it ceases to do so, the system collapses, and it is inevitably dragged down by gravity, until its structure and the surface of the planet come together at some point in a more or less violent manner.
To illustrate this, let us look at some examples:
To improve an RPA by increasing its load capacity, we would usually have to either increase its wing surface area or increase the power of its engines. Both changes have adverse consequences. Increasing the wing area has several negative side effects, such as increasing the aircraft’s weight (due to increasing the size of the structure) and drag (due to an increased surface area). On the other hand, an increase in engine power means an increase in fuel consumption and, therefore, requires more weight to be added in fuel or batteries during take-off which result in a reduction of flight time.
If we want to improve an RPA by making it faster, we must increase the power of its engines (with the same negative effects seen above). In the case of a fixed-wing aircraft, the wing aerofoil can also be reduced in thickness to reduce drag, but this increases its stall speed, and therefore also the landing and take-off speed. This will make its manoeuvres more complicated, its flight envelope more critical, etc.
This zero-sum situation in UAS, where everything that is improved on the one side has negative effects elsewhere, has a direct consequence: when designing an UAS, it must be completely focused on a specific type of mission. Otherwise, we will end up with a system with so many negative effects that its viability to carry out a mission will be seriously compromised. A more concrete and closed design will result in a better performance of the mission.
Thus, we can conclude that all UAS must be designed with a specific task in mind (with limitations imposed by the resources and technologies available at that time).
In general, there is no UAS that is good for multiple different tasks. Either it is very good at doing a specific task (because it was specifically designed for that task) or it is mediocre at performing various tasks.
When someone talks of a “multi-purpose” RPA or when an RPA is described as being “versatile”, it is simply a commercial or communication strategy. A “versatile” system is nothing more than a compromise between the technical and economic sides of an RPAS. Thus, savings made in the design of a single system translate into a mediocre performance in several different applications, none of which was the focus of its design. However, this “versatility” is acceptable in cases where the economic savings made in its acquisition offset and compensate for a mediocre performance in several different types of mission. This becomes increasingly acceptable as the overall cost of the system increases. In other words, the more expensive the system, the more it pays off to have a design that is not specifically adapted to one mission, in exchange for the possibility of using it in a wider variety of missions. This aspect is not unique to RPAS, as it is also demonstrated when designing high-cost commercial and military manned aircraft, where there can be desperate attempts to ensure that all programmes have a wide range of users, even if this means that they are mediocre in the performance of some of their intended missions. Clearly, and by extrapolation, it is also the case that the lower the relative cost of the UAS, the more important it becomes for it to be designed specifically for a mission. For example, a small RPAS designed for agriculture will unsurprisingly perform poorly in other tasks such as surveillance. Furthermore, because of its lower cost, it is worth having an aircraft dedicated exclusively to each type of mission.
Lastly, because as a general rule the cost of an UAS usually has a fairly direct relationship with the size or weight of its RPA, we can also conclude that the smaller an RPA is, the more specific and focused its design should be, as the costs of designing it for a specific type of mission are less valuable than its performance during that mission.
Note:
UAS: Unmanned Aerial System
RPA: Remotely Piloted Aircraft
RPAS: Remotely Piloted Aerial System
