Reproduced from Medium.com
The industrial drone market is at the cusp of explosion.
This sector is one of the fastest growing of any industry at an annual growth rate of over 100% predicted for the next 5 years: already we’ve seen a 30x increase in FAA 333 exemptions authorizing commercial drone operations over the last 12 months. After the rise of military and consumer applications, the capabilities of drone technology has been proven and can now be used for commercial applications in mining exploration, pipeline inspection, search & rescue, agricultural surveying, package delivery, and much more. These technologies are set to drastically change trillion dollar natural resource sectors through deployment of thousands of drones every day. All these use cases are beyond-line-of-sight, possibly +100km away and while the industry currently possesses the technology in order to fly unmanned aircraft at such long ranges, we do not yet trust drones to do these long flights completely autonomously. This lack of reliability and safety measures for beyond-line-of-sight operations is leading to restrictive regulations, high insurance costs, low industrial uptake of the technology, and is currently the biggest challenge limiting the industry’s growth.
Right now, drones are piloted by trained operators who go out to work sites for individual inspection flights. Drone pilots are skilled aviators but even they struggle to see and avoid obstacles and aircraft when operating drones at extended range, limiting their current operation to closed, line-of-sight environments. Obviously this leads to crashes and limits the scalability of these drone systems. Even if these operators fly the aircraft beyond-line-of-sight they must do so using GPS tracking alone. If there are any obstacles that were not known before the aircraft took off, or obstacles that move during the flight (for example manned aircraft or wildlife), the GPS could guide the drone directly into these obstacles. We’ve seen perfectly executed flights fail because the previously chosen route happened to intersect with some unforeseen buildings, leading to destructive crashes. Additionally, everyone in the aviation industry is worried about “the big one” – that first time that a drone accidentally takes down a manned aircraft.
Even with current autopilot systems in bigger, manned aircraft, the pilot is there to provide situational awareness in case things go wrong or something unexpected pops up during the flight, and that is what allows us to trust these aircraft with our lives. For autonomous industrial drones, it is therefore critical to include situational awareness onboard the aircraft to reduce pilot/operator error, operational risk, and bring with it a trust that allows for scalability and use of truly autonomous drones. Current “bumper solutions” exist for sensing 10-40m around the aircraft, which is useful for consumer and photography applications, but not for industrial drone applications. When travelling at speeds of 30-50m/s and far from home base, safety becomes much more critical and a collision-detection zone of +500m around drones is required. In order to fly safely in shared airspace this situational awareness system not only needs to stay clear of fixed, ground-based obstacles, but also be able to track and avoid anything moving through the air.
Risk reduction and increased trust ultimately leads to safer skies, massive adoption increases of industrial drones, lower insurance costs for operators, and reduced regulatory barriers. Situational awareness and collision avoidance will be the unlocking piece in the market that helps spur the predicted spike in the industrial market reach $23 billion over the next 5 years.
At Iris Automation we are building the collision avoidance and situational awareness systems described above, in order to unlock the entire industrial drone industry.
