The Rise Of Fully Autonomous AI Drones

It would be an understatement to say that autonomous drones don’t exist yet. In fact, autonomous drones in the form of AI drones are already being used to certain extent.

For better understanding, let’s assume that the aerospace industry implemented five distinctive levels of autonomy for drones. These may be defined as;

• Level 0: no autonomy
• Level 1: certain level of autonomy including altitude control system; however, the primary control is still with pilots
• Level 2: Multiple autonomous systems onboard and working simultaneously; the control is still with the pilots
• Level 3: Enhanced autonomous systems under specific conditions; however, the pilots are must to monitor the progress of drones
• Level 4: Greater level of autonomy in majority of the situations. However, the pilot can resume control when he thinks it fit
• Level 5: Fully autonomous drones

Everything About The Rise Of Fully Autonomous AI Drones

Now, let’s see how far the Artificial intelligence drone technology has gone thus far. The development of modern AI drones capable of handling most of the tasks in different fields like agriculture, or surveillance means that we are already into advance level 4 stages. AI drones today are fully capable of handling assigned tasks with little to no supervision.

However, we still have to go to the next level, that is the development of fully autonomous drones. But before we can achieve that, the technology would have to overcome some challenges. Interestingly, these challenges are little about technology and more about regulatory compliance and safety. For instance, before we move into the development of Level 5; fully autonomous drones, we have to make sure that such drones are able to comply with the safety regulations, and meet local/international air traffic laws.

Challenges for Level 5 drones that are yet to be overcome includes

• Designing, development, and testing of sensors, and radars to ensure capability of AI drones to withstand any unforeseen obstacle and operate in any environment
• Design and development of software that’s viably safe and secure
• Improving the design and material of drones to enhance the travel distances, as well as, lower the weight

The key to overcoming these challenges lies with simulations, which can assist to optimize individual parts of the AI drones, along with the whole system.

Difference between AI Drones and UAVs?

Drones and UAVs are often used interchangeably. In essence drone isn’t a technical term, rather a general term.

In the world of aerospace, UAVs or Unmanned Aerial Vehicles represent flying machine learning solutions which can be controlled remotely or autonomously. As with many other technology, UAVs trace its origin from the military, where these were used by the military as reconnaissance and surveillance tools to spy on enemies.

Today, Artificial intelligence drones have made their way across many fields and applications including; terrain mapping, livestock management, agriculture, urban planning, forestry, coastal monitoring and much more.

 The Rise Of Fully Autonomous AI Drones

Well, there may be high fantasies about the future of AI drones like; air taxis, air delivery and others. However, before such applications become the norm, there are certain obstacles that need to be overcome.

Honestly, with the current technological advancement, the rise of autonomous AI drones isn’t the matter of “When” but “How” we want these autonomous drones to be.

Technically speaking, it’s easier to design a fully autonomous AI drone that’s capable of flying between two pre-defined points (we already have these drones applied across many fields). However, it’s much harder to come up with a design that enables these flying robots to deliver pizza at doorstep; especially in an urban environment (Amazon is already testing this application though).

In the field of aerospace, the most challenging aspect is to design and control the takeoff and landing approach of any craft. And in case of pizza delivery, the drone would have to accomplish this in an urban environment; avoiding the weather birds, clothes lines, houses, and other objects that pose serious safety risks. So, until the technology is matured enough to take-on these obstacles safely, we may have to be content with the pizza boy and be ready to pay some nice tip to the person.

Looking at the current technology used in the design and development of AI drones, there are certain limitations which have to be overcome. For instance, while AI drones are able to survey vast swaths of agriculture land autonomously, these drones are typically supervised by pilots who are ready to take control in any unforeseen events.

So, to summarize the current state of AI drones we can safely say that the technology still lacks to:

• Manage complex environment or unforeseen situations
• Avoid obstacles in an urban environment
• Handle adverse weather

As mentioned above, we are already into advanced stages of autonomous drones, with AI drones taking over various autonomous roles like remote site inspections, emergency use, vital deliveries to remote areas, and others. In a few years, we may see Artificial intelligence drones taking on even more autonomous roles.

However, before that happens, the technology will have to prove its viability for commercial use. In short, there’s still some time left before we can have a pizzabot bringing our favorite Domino’s Pizza.

Fully Autonomous Drones and Airspace Safety

Airspace safety is a crucial aspect, which requires extensive working before fully autonomous AI drones can take on skies.

The aerospace industry has already been working in this aspect for some years. The problem of airspace safety will require new rules and regulations for air traffic control including predefined routes and use of advanced sensors to avoid deadly incidents.

As a starter, the sensors must have the capability to sense the environments without getting fooled by various obstacles like glare, fog, lighting, etc. Moreover, for fully autonomous AI drones to be commercially viable, such sensors need to be lightweight to maximize the travel distances, improve maneuverability and increase carrying capacity. Also, the sensors must be affordable for commercial uptake of the technology.

Fortunately, we already have the technology like radars and transponders used in airplanes to avoid air traffic conflict. Such technologies can be optimized and integrated into the fully autonomous AI drones to improve its viability.

Next, we need to design and develop robust software and AI systems to receive information from sensors, analyze it and make intelligent decisions. Again, simulations will come invaluable in this case to train Artificial intelligence systems and ensure safe decision-making capacity of AI systems.

Lastly, the rise of fully autonomous AI drones would need more efficient and powerful batteries. This is important because the financial viability or commercial success of these drones will rely on better and lighter batteries.