Rethinking Drones As Autonomous Robotics
The Obvious Reason the Industry Isn’t Rapidly Growing & What’s Missing
We hear it daily — “Launch your drone program!” Uninspired marketing campaigns littered across social media, websites and emails. A detrimental circle of brands mirroring brands, unwittingly stalling the rise of drones. The problem is, as an industry, they’re missing the damn point. Take for example a use case we see all too often — construction. When handheld drills started showing up on jobsites, we didn’t hear Black + Decker say, “launch your drill program!” Why not? Drills are just enablers. They allow workers to do what they were already doing — except better, faster and more efficiently. The breakthrough had little to do with the actual tool itself, and more the new ability to enable faster holes. Drones are no different.
The goal isn’t to “put a drone on every construction site.” Drones are promising new vehicles that have the potential to transform industry, but they also inherently introduce new costs and complexities. The thought of adding new tools, new responsibilities, new certifications and permits, and new burdens to an already complex operation is the exact opposite of what most project managers consider helpful. This might begin to explain why drone service providers today are collectively struggling to grow at any meaningful velocity. We’re creating “launch your drone programs” solutions that make it easier for businesses to own and operate drones, when we should be making the drone invisible, and become laser-focused on the data drones generate and an infrastructure that supports rapid spatial insights.
We need to stop putting drones on construction sites, and start giving the industry the very thing that drones enable — insight. Drones will be on every job site in the next few years, but not as another tool on the tool belt. The project manager isn’t adopting a drone program. They’re adopting a visual insights program that captures a new, historical perspective across their sites. They’re providing situational awareness holistically throughout their organization. They’re making decisions based on the actual state of projects, and the insights affordable by new perspectives and sensors.
Drones to Autonomous Robots
This idea naturally begs the question, so how do you enable the industry? There’s over 1,000,000 highly capable, commercial-grade drones in the US. That’s a fleet that outnumbers active Uber drivers, all the airplanes that have existed over the span of history, as well as all the vehicles operated by FedEx and UPS combined. Unfortunately, these aerial vehicles largely sit idle, collecting dust, and serving very little purpose. In this state, drones are little more than flying cameras, occasionally used by novice pilots to take fun pictures or capture cool videos. From this perspective, it’s hardly obvious why the drone industry is estimated to be valued at over $127B by 2020.
But something special happens when you remove the pilot from the drone — it becomes an autonomous robot. Suddenly you go from about a million novel playthings, to a fleet of state-of-the-art, autonomous robots capable of enabling nearly every industry, today, with ground-breaking perspective and insight.
New Data & New Insights
Freeing drones from the error-prone hands and distracted gaze of humans not only eliminates the uncertainty and unpredictability of a million or so independent pilots, it permits precision data. When you think about it, you’re going from a million pilots to one flawless pilot, capable of reacting to the environment in real-time and synchronizing with other nearby autonomous robots. When a drone, or more accurately in context an autonomous robot, can repeatedly fly the same path in the 3D world with absolute precision and accuracy, it ceases to provide unstructured data (or more simply put — drone photography). This solves a bad data dilemma plaguing the industry since drone service providers began offering imagery to customers.
What emerges is a completely new class of spatial data. Once you master a ‘mission standard’ capable of repeatedly navigating the physical world, imagery becomes data, and data can then become insight. This new class of data has four dimensions. Autonomous robots repeatedly capture precision data in the XYZ physical space, thus integrating the added dimension of time. What is so important about “4D Data” is it doesn’t just represent a new contextual representation of the physical condition of an environment, it also opens the door to computer analysis to reveal patterns, trends, and relationships — training machine learning and artificial intelligence to think and interact in the world around us.
Why Hasn’t the Drone Market Taken Off?
When drones become autonomous robots, the industry is also suddenly capable of shifting from expansion at a linear scale, to something much more exponential. Right now, the drone industry is limited in throttle by FAA regulations that mandate one pilot per drone economics. The equation is linear. If you double the pilots, you double the output. While a 1:N model would precipitously permit exponential growth, when your goal is to “put a drone on every construction site,” you can’t meaningfully adapt your business model to scale, even if this regulation was lifted tomorrow. Similar to how early Uber was able to scale with a largely 1 driver: 1 passenger model, the drone industry is capable of considerable expansion. So why hasn’t it?
Currently, the drone ecosystem is nascent and highly fragmented. Incredibly innovative hardware, software and services are emerging, however each technology addresses a niche problem or use case. Producing insights means an infrastructure that reaches across all these systems and technologies, encompassing initially requesting data, planning for data collection, dispatching robotics, autonomously capturing precision data, rapidly uploading and ingesting data, transforming, analyzing, distributing, and then visualizing the insight. If these steps and systems cannot communicate with one another, a human is required to make manual decisions and perform mundane actions to bridge the gaps between each step in the process.
Big Data-Levels of 4D Visual Insight
We’re driving the convergence of big data, unlimited processing power, IoT, machine learning and artificial intelligence. We need to provide data-starved startups hoping to propel autonomous cars, smart cities or edge computing, with the same frequency of real-world data that satellites brought to macro-oriented industries and governments. To move this forward, it’s not just a matter of rethinking drones as autonomous robotics capable of collecting precision data, we also need to solve for a velocity, volume, variety and veracity of 4D Visual Data.
Before we go into what this system would look like, it’s important to make a clear distinction between “data” and “insight.” In the same way a Project Manager doesn’t want a “drone program,” they emphatically don’t want raw drone data either. Data eats up your time and keeps you busy digging through folders organizing image assets, managing files storage and shared access. Data is what drones capture, but insights are the material reason why you’re beginning to see drones buzzing around construction sites, inspecting infrastructure or assessing crop health.
To facilitate big-data levels of physical-world data (and thus insight), we must first unify the jumbled noise of a hundred nascent drone hardware, software and service startups down to one single command. It should be as easy as any certified pilot with a capable drone traveling to a location and pressing ‘go.’ The drone autonomously comes to life, flies a predetermined mission and captures identical data sets to previous captures. If a battery is low, the drone will return home for a swap and then resume uninterrupted data capture. When finished, the pilot should only have to give one more command, ‘upload,’ to automatically upload data to the cloud for processing and analysis. From here the 4D insights would appear in the customer’s portal within minutes or hours.
What’s missing isn’t so much another end-service or a new-and-improved drone, as much as an end-to-end framework that facilitates and interconnects automation between technologies and services that already exist in the drone ecosystem. We need a cloud-like, system of systems to create a truly end-to-end 4D insight supply chain that eliminates the friction between steps in the process. Only this will enable a rise of autonomous robotics and spatial data, at a rate not seen since satellites began capturing a 2D history of the earth. In parallel with the recent emergence of data sciences, unlimited computer power, edge computing, AI and machine learning, vast amounts of spatial data can be collected and turned into valuable and actionable insight — useful to both humans and other autonomous robotic interacting in the same physical spaces.
A New Category
This is the mission of Hangar, and the perspective we share on the drone industry.
Any way you segment the DSP market, Hangar doesn’t fit in a box, or fall into any existing Gartner Magic Quadrant. We’re creating a new category. One that transforms drones into autonomous robotics, performs sophisticated precision missions repeatedly and interchangeably, and unifies third-party drone technologies and services that exist in the marketplace today, creating a scalable spatial insight supply chain.
In 2016, Hangar acquired the earliest and most significant software in autonomous drone technology — Autopilot, and we’ve pushed the boundaries of autonomous flight ever since (If you’re curious about scaling 1:N, the answer is an emphatic hell yeah). Last year Hangar officially released the first version of Robotics-as-a-System™; the world’s first partner-integrated, internet-scale platform designed to put robotics to work by automating a modular end-to-end 4D Data supply chain. This simplifies the entire request-to-insight supply chain down to handful of decisions, providing a seamless alternative for obtaining a large variety of 4D Visual Insights. We’ve unified leaders in the drone ecosystem, focusing on a new class of data and insight that will fuel innovation in categories like machine learning, artificial intelligence and edge computing. And most importantly, we’re shifting the paradigm of “putting a drone on every Construction site,” to giving industry the very thing drones can enable — 4D Visual Insight.
About the Author(s)
Josh Meler is the Senior Director of Marketing at Hangar Technology, Inc. Prior to working at Hangar, Josh was Chief Marketing Officer at a startup that created a new category in PaaS offerings for mobile apps.
It’s no coincidence that my career is about as old as the first generation iPhone. I’ve seen firsthand a monumental shift in how the world works. For 500 years, the movement of ideas and capabilities was dependent solely on people and physical mediums. Then, in the most disruptive fraction of years in our humanity, that model was violently turned upside down, giving rise to the age of connectivity, mobility, and now —autonomicity .
I’m obsessed with this idea, and have made it my career’s ambition to be a first-mover, shaping how these emerging technologies affect the global landscape.
