Ong Jiin Joo, CTO and Co-Founder, Garuda Robotics
First, some acronyms: an unmanned aircraft (UA) a.k.a. a drone is commonly controlled by a pilot via a remote controller (RC) and a ground control station (GCS) with direct visual line of sight (VLOS) communications, such as Wi-Fi.
Around the world, drones are limited to VLOS flights by law. That is set to change. Commercial use cases such as parcel delivery and air taxis are pushing the limits of regulations and technology. The age of internet drones beckons.
At Garuda Robotics (GR), we believe that drones should be natively connected to the cloud based on 5 main drivers:
1. Professional Drone Operations
A professional company managing a fleet of drones needs to track their pilots and drones, ensure that their drones are airworthy, and comply to ever changing regulations. Before deployment, they need real time data on weather, flight restrictions (no-fly zones), as well as perform full risk management, apply permits, and purchase insurance.
Drone fleet management systems
2. UA Traffic Management (UTM)
Commercial operators share the skies with hobbyists flying their drones recreationally. This presents a safety risk, as a rogue pilot flying irresponsibly can cause chaos to other drones or even manned aviation.
Civil Aviation Authorities (CAA) worldwide are trying different ways to identify drone pilots and deconflict the use of airspace. One such way is to require all pilots to register for a remote ID, similar to a car plate. While flying, the drone must let a “traffic police” or UTM know where it is, for the UTM to alert other pilots with drones nearby.
By eventually having all drones connected to the cloud, publishing their whereabouts, the CAA and the public will be in the know about all drones, while commercial operators will be able to take steps to safeguard their operations. We are demonstrating one such possible system in Singapore in partnership with AirMap as part of the FutureFlight Consortium.
3. Beyond-Visual-Line-Of-Sight (BVLOS)
Commercial drones are increasingly used in situation where the pilot will lose sight of the UA, such as delivering emergency medicine, or food.
Pilots must continue to maintain full control of the drone despite the autonomous nature of these BVLOS flights, for liability reasons, similar to that of the watchful human at the driverless car’s driver seat. In high-risk conditions, such as operating in urban Singapore, the system must achieve 10-7/ flight hour safety standards, that is, only 1 catastrophic failure for every 10 million flights.
As such, it is critical to have first-person-view (FPV) video streaming live to a drone operations center (DOC), where drones are operated. To avoid the massive investment in another nationwide RF network for drones, many manufacturers including GR are utilizing cellular networks as the primary network for BVLOS use cases. We host media servers in the cloud to record the video stream, and re-broadcast it to various consumers beyond the pilot.
4. 5G Network Slicing
The current generation of public cellular networks cannot support mission critical operations such as aviation, due to the lack of service level guarantees(SLG).
In the impending 5G rollout, one new feature is network slicing—the ability for a prioritized SIM to temporarily reserve a dedicated frequency spectrum, avoiding congestion originating from consumer devices. This makes connection to the cloud even more reliable than connecting via Wi-Fi from a GCS, as it avoids competing for use of spectrum from ubiquitous Wi-Fi devices.
To make this reliability even more apparent, Garuda CoPilot—our on-board companion system with LTE— is designed to have two or more LTE connections from diversified telcos, including private LTE base stations were available. We also secure the link with the latest cybersecurity technologies, such as having physical, secure elements on drones for authentication and encryption.
5. Artificial Intelligence (AI)
The cloud has unlimited scale when it comes to compute resources, power that a drone does not have on-board. By connecting drone sensors, video, and pilot commands to a cloud infrastructure, we can execute compute intensive machine learning (ML) and computer vision (CV) algorithms to help with the drone’s navigation or mission goals.
Although the primary use cases for ML/CV now are navigation and surveillance, the potential is endless. For example, GR is heavily involved with vision-based analytics in agriculture setting where we census crops and detect issues. Maybe one day, drone AI will verify your identity by scanning your face before lowering the pizza you ordered to you.
Cloud Players in the Drone Market
A brave new world is emerging at the confluence of aviation, infocomm, and public safety, one that promises better utilization of the 3rd dimension of space above our cities, but also one that challenges many status quos.
End Users of drone operation platforms, such as government agencies, facility managers, logistics companies, and security agencies, should not shy away from investing in full end-to-end trials, as part of the learning journey. Existing SOP should not get in the way of studying new drone centric concept-of-operations.
On the other hand, many traditional IT businesses are looking to increase their customer’s productivity with workflow built around drones and robotics, while retaining the cloud investments made earlier. Garuda Robotics hopes to help make that transition easier by providing a BVLOS Platform-as-a-Service (PaaS), drone test sites in Singapore, as well as ready-to-fly products such as Plex Horizon, a flight control system for BVLOS operations.
These pre-made software applications and components are, however, no match for a timely investment to fly, to learn to fly from professionals, to see the different points of view from manned aviation and regulators, and to build solutions from the perspective of the operator. Safety first.
