Guide To Levels Of Drone Autonomy 2022

Want to know the guide to levels of drone autonomy and find out which one is right for you. Read on to find out more about the advantages and features of each level.

Drones, technically described as unmanned aircraft systems (UAS) have phenomenally impacted our society in several ways.

Especially, some profound technical innovations in the drone sector like the integration of computer vision, machine learning and artificial intelligence with drones have significantly expanded their capabilities.

Drones have become versatile in their applications since they are able to meet the robust needs of several industries like real estate, construction, surveying, agriculture, site selection, indoor and outdoor inspection, and delivery of consumer goods and medical supplies.

With the addition of AI to drones, they can now interact with perilous surroundings with ease in an intelligent way often achieving missions that is impossible or time-consuming for humans.

For example, computer vision technology and AI-enabled sensors in drones make it possible to apply drones across industries like energy, oil and gas, and mining.

Insurance companies have started using drones for advanced inspections and surveys without having to touch the target objects or entities.

Surveys and inspections using drones happen much faster and also ensure the safety of employees. Therefore, several industries find it easier to comply with industry standards. 

Adding AI to drones is a sure way to expand their capabilities, stretch their applications, lower operational and maintenance costs, and increase revenues.

Drone autonomy is a very useful and trending topic that will certainly interest drone enthusiasts. Here is a short guide to understanding different levels of drone autonomy.

Guide To Levels Of Drone Autonomy

Drone Automation And Drone Autonomy – How Do They Differ?

The terms automation and autonomy are often confused especially in the drone ecosystem.

Though these two terms are used interchangeably, it is very important to understand the crucial difference between these two terms when we seek to expand drone operations by adding some levels of autonomy.   

What Is Drone Automation?

Drone automation is a very common topic. In a number of scenarios, drone processes are seen as automated today.

For instance, drone operators or drone pilots may program a flight path with the help of some conventional automation tools like waypoints, geo-fencing or beacons while trying to direct a drone from Point A to Point B.

If this is done, the drone can fly automatically using motors, timers, sensors and other components. This process can move on without any more user input.

Guide To Levels Of Drone Autonomy

However, the user is free to intervene at any point and tweak the mission to his choice or cancel it fully.

What Is Drone Autonomy?

Autonomous drone functions are quite different from automation in the sense that autonomous drones are capable of making some decisions without any input from the user.

This is achieved with the help of A|I systems that are programmed to gather data from satellites, sensors, cameras and videos. The data collected thus is used in turn to make decisions.

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A highly interesting thing to note here is that how a drone makes decisions is not confined to any algorithm.

On the other hand, an autonomous drone is highly capable of learning from its environment and making the necessary adaptations in response to changing situations. 

mission level autonomy

The majority of drones work with a combination of autonomous and automated features. Recently, there has been an increased focus on developing safer and more reliable landing technologies that can make drones safe to detect, safely avoid, safely navigate, and emergency land.   

A number of such AI applications in drone making help avoid collisions to a great extent and locate the areas for a safe landing in real time.

Such additions in drones can also help ensure compliance with FAA regulations and can help scale up the possibilities of Beyond Visual Line of Sight (BVLOS) flights.

For instance, Sharper Shape has employed automation and autonomous features in combination to offer a comprehensive asset intelligence solution.

Such initiatives have helped extend the scope of drone operation, drone reliability, and the safety of critical infrastructure.

A combination of automated flight paths and autonomous features aided by LiDAR and other advanced sensors can make data collection faster, safer, cost-effective, and more accurate.

Different Levels Of Drone Autonomy

There is an already established system of classifying the different levels of autonomy in the case of autonomous vehicles.

In similar lines, efforts are underway on part of industrial, customer and academic communities to define a useful approach to define the different levels of drone autonomy too.

drones

Several more autonomous features are being quickly added to new generation drones. Therefore, an acceptable kind of classification is yet to be put in place for wider use.

Here I have proposed a rough framework to fit in the different levels of drone autonomy. Let us say these levels correspond to the complete absence of autonomous features in the lower end and full autonomy at the higher end of autonomous drone models we can find in the market today.

The purpose of this framework is to be able to identify the different levels of autonomy in the concept and operational levels and understand how they are implemented in the drone making industry.  

  • No Autonomy Drones

Drones that do not have any kind of autonomous features need a pilot to control them all the time. Without the control of the pilot, the drone is sure to crash.

This type of drone never has the ability to understand or respond to any obstacles. These are mainly recreational kinds of drones. One of the principal applications of such drones are fun racing. 

  • Low Autonomy Drones

Drones of this category operate with the lowest levels of autonomy. These drones are mainly targeted to be used within enclosed spaces for safety reasons.

They have severe spatial limitations such as walls and ceilings. Though such type of drones can stay in the air without the pilot’s control, it is highly necessary that they must stay within the operator’s visual line of sight (VLOS).

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The drones in this category are mainly toy drones featuring six-axis gyro sensors that can aid in stabilization. In some cases, these drone models include a ‘return to home’ button on the controller. Upon pressing, this button returns the drone to the launch point.  

  • Partial Autonomy Drones

In this type of drone, the autonomous features are still more advanced. However, the pilot is in full control of the drones. In these drones, we find a combination of sensors, GPS routers, and accelerometers.

However, a pilot is fully needed to operate it, guide its movements, and receive warnings if the drone must approach any obstacle.

Based on these warnings, the drone pilot must steer the drone to safety. While these drones are not capable of detecting, avoiding or navigating, they can only detect and give warnings.

As seen in the case of no autonomy and low autonomy drones, partial autonomy drones must also stay within the pilot’s VLOS. 

  • Conditional Autonomy Drones

This class of autonomous drones are designed with high levels of autonomous features. In these types of drones, the drone pilot is not flying the drone any longer. Instead, stays as a backup to face any emergency situation.

The majority of drone delivery operators we find at present are conditional autonomy drones and pilots are needed only as emergency backups.

Conditional autonomy drones come with the basic detect and avoid systems that employ frequency and radio sensors in order to avoid poles and buildings in their flight path.

This type of drone can also find safe spots to land on their own based on the awareness of its environment.  

Most importantly, you must note that conditional autonomy drones found in the drone delivery market confront regulatory hurdles that the present aviation laws have put in place.

This is because these laws are made with the focus on the drone pilot occupying the cockpit of an aircraft and making the necessary decisions.

Only a few type of commercial delivery drones operate under Part 107 waiver allowed by the FAA. However, there are strict limitations in place when it comes to ensuring safety.

For instance, some of the regulations we can take note under Part 107 drones include the following. These drones must not be allowed to fly beyond the visual line of sight.

They must not fly over roads and people. It is necessary that humans are present on-site. One pilot is allowed to operate only one drone at a given time.

  • High Autonomy Drones

High autonomy drones feature high levels of autonomous features that make use of sophisticated detect and avoid systems. They have detected and navigated systems that do not require the intervention of a pilot.

These drones are capable of exploring environments that do not have access to GPS signals and in locations where GPS is denied.

These drones can operate in harsh conditions and can also identify the people in need without requiring any pilot on the site. Pilots can easily monitor high-autonomy drones from remote locations.

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Following some relaxations in the FAA regulations, one pilot can manage several BVLOS drones simultaneously. In some experimental studies, up to 24 drones of a fleet were managed by a single pilot.

In some setups, unmanned traffic management systems are managing drone operations instead of pilots.  

Exyn’s drones for example work on GPS-free navigation technology for the purpose of exploring complex spaces even without a backup pilot.

These drones create maps of their environment and keep tracking their movement through the surroundings.

Hence we can say these are self-reliant drones that can explore their surroundings without the intervention of a human pilot during their flight.

You must note the fact that while studying human-free environments like caves and mines, drones are not operating above humans or roads. Therefore, they are not governed by strict regulations.

On the other hand, drone delivery operators will have to get BVLOS flight clearance and also need to complete FAA’s Part 135 certification process in order to operate over roads and people.

You will accept that this is not going to be an easy task. Nevertheless, computer vision and AI can provide solutions to these hurdles and give way for predictable and safer drone operations.

  • Full Autonomy Drones

Full autonomy drones mark a significant milestone in the evolution of drones. They are capable of flying in any condition and in any environment.

his class of drones can control themselves under any situation without the need for any kind of human intervention at all.

In order to reach the level of full autonomy classification, the navigation performance of these drones must be comparable to how drones perform while relying on external control systems.

At present, full autonomy drones are not in production since a regulatory base is still developing. There is also a need for sophisticated control systems that can manage different kinds of human-operated and unmanned vehicles in the air at a given time.

At present, we do not have any legwork that can effectively handle the huge volume of data captured by such drones. 

Conclusion

The autonomous drone market is growing at a phenomenal phase. AI companies are facing an unprecedented demand to develop, test and provide solutions that will help make drones more reliable and safer.

When it is the question of drones, errors can never be compromised with since accidents can result in fatal injuries or even death of humans and animals.

In addressing these issues, computer vision and AI can play a big role. When drones are fast scaling up in the lines of becoming more autonomous, it is only a question of time to see them fully safe and compliant with all regulations.

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