How to Democratize Humanitarian Robotics

Our world is experiencing an unprecedented shift from manually controlled technologies to increasingly intelligent and autonomous systems powered by artificial intelligence (AI). I believe that this radical shift in both efficiency and productivity can have significant positive social impact when it is channeled responsibly, locally and sustainably.


This is why my team and I founded WeRobotics, the only organization fully dedicated to accelerating and scaling the positive impact of humanitarian, development and environmental projects through the appropriate use of AI-powered robotics solutions. I’m thrilled to announce that the prestigious Rockefeller Foundation shares our vision—indeed, the Foundation has just awarded WeRobotics a start-up grant to take Humanitarian Robotics to the next level. We’re excited to leverage the positive power of robotics to help build a more resilient world in line with Rockefeller’s important vision.


Aerial Robotics (drones/UAVs) represent the first wave of robotics to impact humanitarian sectors by disrupting traditional modes of data collection and cargo delivery. Both timely data and the capacity to act on this data are integral to aid, development and environmental projects. This is why we are co-creating and co-hosting global network of “Flying Labs”; to transfer appropriate aerial robotics solutions and relevant skills to outstanding local partners in developing countries who need these the most.

Our local innovation labs also present unique opportunities for our Technology Partners—robotics companies and institutes. Indeed, our growing network of Flying Labs offer a multitude of geographical, environmental and social conditions for ethical social good projects and responsible field-testing; from high-altitude glaciers and remote archipelagos experiencing rapid climate change to dense urban environments in the tropics subject to intense flooding and endangered ecosystems facing cascading environmental risks.

The Labs also provide our Technology Partners with direct access to local knowledge, talent and markets, and in turn provide local companies and entrepreneurs with facilitated access to novel robotics solutions. In the process, our local partners become experts in different aspects of robotics, enabling them to become service providers and drive new growth through local start-up’s and companies. The Labs thus seek to offer robotics-as-a-service across multiple local sectors. As such, the Labs follow a demand-driven social entrepreneurship model designed to catalyze local businesses while nurturing learning and innovation.

Of course, there’s more to robotics than just aerial robotics. This is why we’re also exploring the use of AI-powered terrestrial and maritime robotics for data collection and cargo delivery. We’ll add these solutions to our portfolio as they become more accessible in the future. In the meantime, sincerest thanks to the Rockefeller Foundation for their trust and invaluable support. Big thanks also to our outstanding Board of Directors and to key colleagues for their essential feed-back and guidance.

On Humanitarian Innovation versus Robotic Natives

I recently read an excellent piece entitled “Humanitarian Innovation and the Art of the Possible,” which appeared in the latest issue of the Humanitarian Practice Network’s (HPN) magazine. The author warns that humanitarian innovation will have limited systemic impact unless there is notable shift in the culture and underlying politics of the aid system. Turns out I had written a similar piece (although not nearly as articulate) during the first year of my PhD in 2005. I had, at the time, just re-read Alex de Waal’s Famine Crimes: Politics and the Disaster Relief Industry in Africa and Peter Uvin’s Aiding Violence.


Kim Scriven, the author of the HPN piece and one of the leading thinkers in the humanitarian innovation space, questions whether innovation efforts are truly “free from the political and institutional blockages curtailing other initiatives” in the humanitarian space. He no doubt relates to “field-based humanitarians who have looked on incredulously as technological quick fixes are deployed from afar to combat essentially political blockages to the provision of aid.” This got me thinking about the now well-accepted notion that information is aid.

What kinds of political blockages exist vis-a-vis the provision of information (communication) during or after humanitarian crises? “For example,” writes Kim, “the adoption of new technology like SMS messaging may help close the gap between aid giver and aid recipient, but it will not be sufficient to ensure that aid givers respond to the views and wishes of affected people.” One paragraph later, Kim warns that we must also “look beyond stated benefits [of innovation] to unintended consequences, for instance around how the growing use of drones and remote communication technologies in the humanitarian sphere may be contributing to the increased use of remote management practices, increasing the separation between agencies and those they seek to assist.”

I find this all very intriguing for several reasons. First, the concern regarding the separation—taken to be the physical distance—between agencies and those they seek to assist is an age-old concern. I first came across said concern while at the Harvard Humanitarian Initiative (HHI) in 2007. At the time, ironically, it was the use of SMS in humanitarian and development projects that provoked separation anxiety amongst aid groups. By 2012, humanitarian organizations were starting to fear that social media would further increase the separation. But as we’ve said, communication is aid, and unlike food and medication, digital information doesn’t need to hitch a ride on UN planes and convoys to reach their destination. Furthermore, studies in social psychology have shown that access to timely information during crises can reduce stress, anxiety and despair. So now, in 2016, it seems to be the turn of drones; surely this emerging technology will finally create the separation anxiety that some humanitarians have long-feared (more on this in a bit).

The second reason I find Kim’s points intriguing is because of all the talk around the importance of two-way communication with disaster-affected communities. Take the dire refugee crisis in Europe. When Syrians finally escape the horrid violence in their country and make it alive to Europe, their first question is: “Where am I?” and their second: “Do you have WiFi?” In other words, they want to use their smartphones to communicate & access digital information precisely because mobile technology allows for remote communication and access.

Young humanitarian professionals understand this; they too are Digital Natives. If crisis-affected communities prefer to communicate using mobile phones, then is it not the duty of humanitarian organizations to adapt and use those digital communication channels rather than force their analog channels on others? The priority here shouldn’t be about us and our preferences. But is there a political economy—an entrenched humanitarian industrial complex—that would prefer business as usual since innovation could disrupt existing funding channels? Could these be some of the political & institutional blockages that Kim hints at?

The third reason is the reference to drones. Kim warns that the “growing use of drones and remote communication technologies in the humanitarian sphere may be contributing to the increased use of remote management practices, increasing the separation between agencies and those they seek to assist.” Ironically, the same HPN magazine issue that Kim’s piece appears in also features this article on “Automation for the People: Opportunities and Challenges of Humanitarian Robotics,” co-authored by Dr. Andrew Schroeder & myself. Incidentally, drones (also as UAVs) are aerial robots.

Kim kindly provided Andrew and I with valuable feedback on earlier drafts. So he is familiar with the Humanitarian UAV Code of Conduct and its focus on Community Engagement since we delve into this in our HPN piece. In fact, the header image featured in Kim’s article (also displayed above) is a photograph I took whilst in Nepal; showing local community members using a map created with aerial robots as part of a damage assessment exercise. Clearly, the resulting map did not create physical separation—quite on the contrary, it brought the community and robotics operators together as has happened in Haiti, Tanzania, the Philippines and elsewhere.

(As an aside, a number of UAV teams in Ecuador used the Code of Conduct in their response efforts, more here. Also, I’m co-organizing an Experts Meeting in the UK this June that will, amongst other deliverables, extend said code of conduct to include the use of aerial robotics for cargo transportation).

What’s more, Andrew and I used our article for HPN to advocate for locally managed and operated robotics solutions enabled through local innovation labs (Flying Labs) to empower local responders. In other words, and to quote Kim’s own concluding paragraph, we agree that “those who focus on innovation must do a better job of relocating innovation capacity from HQ to the field, providing tools and guidance to support those seeking to solve problems in the delivery of aid.” Hence, in part, the Flying Labs.

In fact, we’ve already started co-creating Kathmandu Flying Labs, and thanks to both the relevant training and the appropriate robotics technologies that we transferred to members of Kathmandu Flying Labs following the devastating earthquakes in 2015, one of these partners—Kathmandu University—have since carried out multiple damage assessments using aerial robotics; without needing any assistance from us or needing our permission for that matter. The Labs are also about letting go of control, and deliberately so. Which projects Kathmandu Flying Labs partners decide to pursue with their new aerial robotics platforms is entirely their decision, not ours. Trust is key. Besides, the Flying Labs are not only about providing access to appropriate robotics solutions and relevant skills, they are just as much about helping to connect & turbocharge the local capacity for innovation that already exists, and disseminating that innovation globally.

Kathmandu University’s damage assessments didn’t create a separation between themselves and the local communities. KU followed the UAV Code of Conduct and worked directly with local communities throughout. So there is nothing inherent to robotics as a technology that innately creates the separation that Kim refers to. Nor is there anything inherent to robotics that will ensure that aid givers (or robots) respond to the needs of disaster-affected communities. This is also true of SMS as Kim points out above. Technology is just a tool; how we chose to use technology is a human decision.

The fourth and final reason I find Kim’s piece intriguing is because it suggests that remote management practices and physical separations between agencies and those they seek to assist are to be avoided. But the fact of the matter is that remote management is sometimes the most efficient solution; in some cases, it is the only solution, as clearly evidenced in the protracted response to the complex humanitarian crisis in Syria. In fact, the United Nation’s Inter-Agency Standing Committee (IASC) suggests bolstering remote management in some cases. And besides, the vast majority of humanitarian interventions engage in some level of remote management.

So if we can use aerial robotics to deliver essential supplies more quickly, more reliably and at lower cost (like in Rwanda), then how exactly does using fewer motorbikes or trucks to deliver said supplies create more separation between agencies and those they seek to assist? In the case of Rwanda, aerial robotics solutions are airlifting much-needed blood supplies to remote health clinics across the country. I’d like to know how exactly this creates a separation between the doctors administering the blood transfusion and the patients receiving said transfusion. As for using aerial robotics solutions to collect data, we’ve already shown that community engagement is key and that local partners can expertly manage the operation of robotics platforms independently. The most obvious alternative to aerial imagery is satellite imagery, but orbiting satellites certainly don’t allow local partners and communities to participate in data collection.

So are there “political and institutional blockages” against the use of robotics in humanitarian efforts? Might humanitarian organizations receive less funding if aerial robotics solutions prove to be cheaper, more effective and more scalable? Is this one reason, to quote Kim, that “Emerging ideas get stuck at the pilot stage or siloed within a single organization unable to achieve scale and impact”? Are political & institutional barriers curtailing in part the entry of new and radically more efficient solutions to deliver aid? If these autonomous solutions require less international staff to manually operate, will the underlying politics of the $25 billion dollar-a-year aid industry allow such a shift? Or will it revert to fears over (money) separation anxiety?

We should realize that disaster-affected communities today are increasingly digital communities. As such, Digital Natives do not necessarily share the physical separation anxieties that aid organizations seemingly experience with every new emerging technology. Digital Natives, by definition, prefer a friction-free world. But by the time we catch on, we’ll no doubt struggle to understand the newer world of Robotic Natives. We’ll look on incredulously as the new generation of Robotic and AI Natives prefer to interact with Facebook chatbots over “analog humanitarians” during disasters. Some of us may cry foul when Robotic Natives decide to get their urgent 3D-printed food supplies delivered to them via aerial robotics while riding a driverless robotics car to their auto-matically built-in-time shelter.

In conclusion, yes, we should of course be aware and weary of the unintended consequences that new innovations in technology may have when employed in humanitarian settings. Has anyone ever suggested the contrary? At the same time, we should realize that those same unintended consequences may in some cases be welcomed or even preferred over the status quo, especially by Robotic Natives. In other words, those unintended effects may not always be a bug, but rather a feature. Whether these consequences are viewed as a bug or a feature is ultimately a political decision. And whether or not the culture and underlying politics of the aid system will shift to accommodate the new bug as-a-feature worldview, we may be deluding ourselves if we think we can change the world-view of Robotics Natives to accommodate our culture and politics. Such is the nature of innovation and systemic impact.

How Can Digital Humanitarians Best Organize for Disaster Response?

I published a blog post with the same question in 2012. The question stemmed from earlier conversations I had at 10 Downing Street with colleague Duncan Watts from Microsoft Research. We subsequently embarked on a collaboration with the Standby Task Force (SBTF), a group I co-founded back in 2010. The SBTF was one of the early pioneers of digital humanitarian action. The purpose of this collaboration was to empirically explore the relationship between team size and productivity during crisis mapping efforts.


Duncan and Team from Microsoft simulated the SBTF’s crisis mapping efforts in response to Typhoon Pablo in 2012. At the time, the United Nations Office for the Coordination of Humanitarian Affairs (UN/OCHA) had activated the Digital Humanitarian Network (DHN) to create a crisis map of disaster impact (final version pictured above). OCHA requested the map within 24 hours. While we could have deployed the SBTF using the traditional crowdsourcing approach as before, we decided to try something different: microtasking. This was admittedly a gamble on our part.

We reached out to the team at PyBossa to ask them to customize their micro-tasking platform so that we could rapidly filter through both images and videos of disaster damage posted on Twitter. Note that we had never been in touch with the PyBossa team before this (hence the gamble) nor had we ever used their CrowdCrafting platform (which was still very new at the time). But thanks to PyBossa’s quick and positive response to our call for help, we were able to launch this microtasking app several hours after OCHA’s request.

Fast forward to the present research study. We gave Duncan and colleagues at Microsoft the same database of tweets for their simulation experiment. To conduct this experiment and replicate the critical features of crisis mapping, they created their own “CrowdMapper” platform pictured below.

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The CrowdMapper experiments suggest that the positive effects of coordination between digital humanitarian volunteers, i.e., teams, dominate the negative effects of social loafing, i.e., volunteers working independently from others. In social psychology, “social loafing is the phenomenon of people exerting less effort to achieve a goal when they work in a group than when they work alone” (1). In the CrowdMapper exercise, the teams performed comparably to the SBTF deployment following Typhoon Pablo. This suggests that such experiments can “help solve practical problems as well as advancing the science of collective intelligence.”

Our MicroMappers deployments have always included a live chat (IM) feature in the user interface precisely to support collaboration. Skype has also been used extensively during digital humanitarian efforts and Slack is now becoming more common as well. So while we’ve actively promoted community building and facilitated active collaboration over the past 6+ years of crisis mapping efforts, we now have empirical evidence that confirms we’re on the right track.

The full study by Duncan et al. is available here. As they note vis-a-vis areas for future research, we definitely need more studies on the division of labor in crisis mapping efforts. So I hope they or other colleagues will pursue this further.

Many thanks to the Microsoft Team and to SBTF for collaborating on this applied research, one of the few that exist in the field of crisis mapping and digital humanitarian action.

The main point I would push back on vis-a-vis Duncan et al’s study is comparing their simulated deployment with the SBTF’s real-world deployment. The reason it took the SBTF 12 hours to create the map was precisely because we didn’t take the usual crowdsourcing approach. As such, most of the 12 hours was spent on reaching out to PyBossa, customizing their microtasking app, testing said app and then finally deploying the platform. The Microsoft Team also had the dataset handed over to them while we had to use a very early, untested version of the AIDR platform to collect and filter the tweets, which created a number of hiccups. So this too took time. Finally, it should be noted that OCHA’s activation came during early evening (local time) and I for one pulled an all-nighter that night to ensure we had a map by sunrise.

The Value of Timely Information During Disasters (Measured in Hours)

In the 2005 World Disaster Report (PDF), the International Federation of the Red Cross states unequivocally that access to information during disasters is equally important as access to food, water, shelter and medication. Of all these commodities, however, crisis information is the most perishable. In other words, the “sell-by” or “use-by” date of information for decision-making during crisis is very short. Put simply: information rots fast, especially in the field (assuming that information even exists in the first place). But how fast exactly as measured in hours and days?

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Enter this handy graph by FEMA, which is based on a large survey of emergency management professionals across the US. As you’ll note, there is a very clear cut-off at 72 hours post-disaster by which time the value of information for decision making purposes has depreciated by 60% to 85%. Even at 48 hours, information has lost 35% to 65% of its initial tactical value. Disaster responders don’t have the luxury of waiting around for actionable information to inform their decisions during the first 24-72 hours after a disaster. So obviously they’ll take those decisions whether or not timely data is available to guide said decisions.

In a way, the graph also serves as a “historical caricature” of the availability of crisis information over the past 25 years:


During the early 1990s, when the web and mobile phones were still in their infancy, it often took weeks to collect detailed information on disaster damage and needs following major disasters. Towards the end of the 2000’s, thanks to the rapid growth in smartphones, social media and the increasing availability of satellite imagery plus improvements in humanitarian information management systems, the time it took to collect crisis information was shortened. One could say we crossed the 72-hour time barrier on January 12, 2010 when a devastating earthquake struck Haiti. Five years later, the Nepal earthquake in April 2015 may have seen a number of formal responders crossing the 48-hour threshold.

While these observations are at best the broad brushstrokes of a caricature, the continued need for timely information is very real, especially for tactical decision making in the field. This is why we need to shift further left in the FEMA graph. Of course, information that is older than 48 hours is still useful, particularly for decision-makers at headquarters who do not need to make tactical decisions.

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In fact, the real win would be to generate and access actionable information within the first 12- to 24-hour mark. By the end of the 24-hours, the value of information has “only” depreciated by 10% to 35%. So how do we get to the top left corner of the graph? How do we get to “Win”?

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By integrating new and existing sensors and combining these with automated analysis solutions. New sensors: like Planet Lab’s growing constellation of micro-satellites, which will eventually image the entire planet once every 24 hours at around 3-meter resolution. And new automated analysis solutions: powered by crowdsourcing and artificial intelligence (AI), and in particular deep learning techniques to process the Big Data generated by these “neo-sensors” in near real-time, including multimedia posted to social media sites and the Web in general.

And the need for baseline data is no less important for comparative analysis and change detection purposes. As a colleague of mine recently noted, the value of baseline information before a major disaster is at an all time high but then itself depreciates as well post-disaster.

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Of course, access to real-time information does not make a humanitarian organization a real-time response organization. There are always delays regard-less of how timely (or not) the information is (assuming it is even available). But the real first responders are the local communities. So the real win here would be to make make this real-time analysis directly available to local partners in disaster prone countries. They often have more of an immediate incentive to generate and consume timely, tactical information. I described this information flow as “crowdfeeding” years ago.

In sum, the democratization of crisis information is key (keeping in mind data-protection protocols). But said democratization isn’t enough. The know-how and technologies to generate and analyze crisis information during the first 12-24 hours must also be democratized. The local capacity to respond quickly and effectively must exist; otherwise timely, tactical information will just rot away.

I’d be very interested to hear from human rights practitioners to get their thoughts on how/when the above crisis information framework does, and does not, apply when applied to human rights monitoring.

Humanitarian Cargo Delivery via Aerial Robotics is Not Science Fiction (Updated)

I had the opportunity to visit Zipline’s field-testing site in San Francisco last year after the company participated in an Experts Meeting on Humanitarian UAVs (Aerial Robotics) that I co-organized at MIT. The company has finally just gone public about their good work in Rwanda, so I’m at last able to blog about it on iRevolutions. When I write “finally”, this is not meant to be a complaint; in fact, one aspect that really drew me to Zipline in the first place is the team’s genuine down-to-earth, no-hype mantra. So, I use the word finally since I now finally have public evidence to backup many conversations I’ve had with humanitarian partners on the topic of cargo delivery via aerial robotics.

Zip Delivery

As I had signed an NDA, I was (and still am) only allowed to discuss information that is public, which was basically nothing until today. So below is a summary of what is at last publicly known about Zipline’s pioneering aerial robotics efforts in Rwanda. I’ve also added videos at the end.


  • Zipline’s Mission: to deliver critical medical products to health centers and hospitals that are either difficult or impossible to reach via traditional modes of transportation
  • Zipline Fleet: 15 aerial robotics platforms (UAVs) in Rwanda.
  • Aerial Robotics platform: Fixed-wing.
  • Weight of each platform: 10-kg.
  • Power: Battery-operated twin-electric motors.
  • Payload capacity: up to 1.5kg.
  • Cargo: Blood and essential medicines (small vials) to begin with. Eventually cargo will extend to lifesaving vaccines, treatments for HIV/AIDS, malaria, tuberculosis, etc.
  • Range: Up to 120 km.
  • Flight Plans: Pre-programmed and monitored on the ground via tablets. Individual plans are stored on SIM cards.









  • Flight Navigation: GPS using the country’s cellular network.
  • Launch Mechanism: Via catapult.
  • Maximum Speed: Around 100 km/hour.
  • Landings: Zipline’s aerial robot does not require a runway.
  • Delivery Mechanism: Fully autonomous, low altitude drop via simple paper parachute. Onboard computers determine appropriate parameters (taking into account winds, etc) to ensure that the cargo accurately lands on it’s dedicated delivery site called a “mailbox”.
  • Delivery Sites: Dedicated drop sites at 21 health facilities that can carry out blood transfusions. These cover more than half of Rwanda.

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  • Takeoff Sites: Modified shipping containers located next to existing medical warehouses.
  • Delivery Time: Each cargo is delivered within 1 hour. The aerial robot takes about 1/2 hour reach a delivery site.
  • Flight Frequency: Eventually up to 150 flights per day.
  • Weather: Fixed-wings can operate in ~50km/hour winds.
  • Regulatory Approval: Direct agreements already secured with the Government of Rwanda and country’s Civil Aviation Authority.


Think Global, Fly Local: The Future of Aerial Robotics for Disaster Response

First responders during disasters are not the United Nations or the Red Cross. The real first responders, by definition, are the local communities; always have been, always will be. So the question is: can robotics empower local communities to respond and recover both faster and better? I believe the answer is Yes.

But lets look at the alternative. As we’ve seen from recent disasters, the majority of teams that deploy with aerial robotics (UAVs) do so from the US, Europe and Australia. The mobilization costs involved in flying a professional team across the world—not to mention their robotics equipment—is not insignificant. And this doesn’t even include the hotel costs for a multi-person team over the course of a mission. When you factor in these costs on top of the consulting fees owed to professional international robotics teams, then of course the use of aerial robotics versus space robotics (satellites) becomes harder to justify.

There is also an important time factor. The time it takes for international teams to obtain the necessary export/import permits and customs clearance can be highly unpredictable. More than one international UAV team that (self) deployed to Nepal after the tragic 2015 Earthquake had their robotics platforms held up in customs for days. And of course there’s the question of getting regulatory approval for robotics flights. Lastly, international teams (especially companies and start-up’s) may have little to no prior experience working in the country they’re deploying to; they may not know the culture or speak the language. This too creates friction and can slow down a humanitarian robotics mission.

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What if you had fully trained teams on the ground already? Not an international team, but a local expert robotics team that obviously speaks the local language, understands local customs and already has a relationship with the country’s Civil Aviation Authority. A local team does not need to waste time with export/import permits or customs clearance; doesn’t need expensive international flights or weeks’ worth of hotel accommodations. They’re on site, and ready to deploy at a moment’s notice. Not only would this response be faster, it would be orders of magnitudes cheaper and more sustainable to carry through to the recovery and reconstruction phase.

In sum, we need to co-create local Flying Labs with local partners including universities, NGOs, companies and government partners. Not only would these Labs be far more agile and rapid vis-a-vis disaster response efforts, they would also be far more sustainable and their impact more scalable than deploying international robotics teams. This is one of the main reasons why my team and I at WeRobotics are looking to co-create and connect a number of Flying Labs in disaster prone countries across Asia, Africa and Latin America. With these Flying Labs in place, the cost of rapidly acquiring high quality aerial imagery will fall significantly. Think Global, Fly Local.

Aerial Robotics for Payload Delivery in Developing Countries: Open Questions

Should developing countries seek to manufacture their own robotics solutions in order to establish payload delivery services? What business models make the most sense to sustain these services? Do decision-support tools already exist to determine which delivery routes are best served by aerial robots (drones) rather than traditional systems (such as motorbikes)? And what mechanisms should be in place to ensure that the impact of robotics solutions on local employment is one of net job creation rather than job loss?

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There are some of the questions I’ve been thinking about and discussing with various colleagues over the past year vis-a-vis humanitarian applications. So let me take the first 2 questions and explore these further here. I’ll plan on writing a follow up post in the near future to address the other two questions.

First, should developing countries take advantage of commercial solutions that already exist to build their robotics delivery infrastructure? Or should they seek instead to manufacture these robotics platforms locally instead? The way I see it, this does not have to be an either/or situation. Developing countries can both benefit from the robust robotics technologies that already exist and take steps to manufacture their own solutions over time.

This is not a hypothetical debate. I’ve spent the past few months going back and forth with a government official in a developing country about this very question. The official is not interested in leveraging existing commercial solutions from the West. As he rightly notes, there are many bright engineers in-country who are able and willing to build these robotics solutions locally.

Here’s the rub, however, this official has no idea just how much work, time and money is needed to develop robust, reliable and safe robotics solutions. In fact, many companies in both Europe and the US have themselves completely under-estimated just how technically challenging (and very expensive) it is to develop reliable aerial robotics solutions to delivery payloads. This endeavor easily takes years and millions of dollars to have a shot at success. It is far from trivial.

The government official in question wants his country’s engineers to build these solutions locally in order to transport essential medicines and vaccines between health clinics and remote villages. Providing this service is relatively urgent because existing delivery mechanisms are slow, unreliable and at times danger-ous. So this official will have to raise a substantial amount of funds to pay local engineers to build home-grown robotics solutions and iterate accordingly. This could take years (with absolutely no guarantee of success mind you).

On the other hand, this same official could decide to welcome the use of existing commercial solutions as part of field-tests in-country. The funding for this would not have to come from the government and the platforms could be field-tested as early as this summer. Not only would this provide local engineers with the ability to learn from the tests and gain important engineering insights, they could also be hired to actually operate the cargo delivery services over the long-term, thus gaining the skills to maintain and fix the platforms. Learning by doing would give these engineers practical training that they could use to build their own home-grown solutions.

One could be even more provocative: Why invest so much time and effort in local manufacturing when in-country engineers and entrepreneurs could simply use commercial solutions that already exist to make money sooner rather than later by providing robotics as a service? We’ve seen, historically, the transition from manufacturing to service-based economies. There’s plenty of profit to be made from the latter with a lot less start-up time and capital required. And again, one strategy does not preclude the other, so why forgo both early training and business opportunities when these same opportunities could help develop and fund the local robotics industry?

Admittedly, I’m somewhat surprised by the official’s zero tolerance for the use of foreign commercial technology to improve his country’s public health services; that same official is using computers, phones, cars, televisions, etc., that are certainly not made in-country. He does not have a background in robotics, so perhaps he assumes that building robust robotics solutions is relatively easy. Simply perusing the past 2 years of crowdfunded aerial robotics projects will clearly demonstrate that most have resulted in complete failure despite raising millions of dollars. That robotics graveyard keeps growing.

But I fully respect the government official’s position even if I disagree with it. In my most recent exchange with said official, I politely re-iterated that one strategy (local manufacturing) does not preclude the other (local business opportunities around robotics as service using foreign commercial solutions). Surely, the country in question can both leverage foreign technology while also building a local manufacturing base to produce their own robotics solutions.


Second, on business models, which models can provide sustainability by having aerial delivery services be profitable earlier rather than later? I was recently speaking to a good colleague of mine who works for a very well-respected humanitarian group about their plans to pilot the use of aerial robotics for the delivery of essential medicines. When I asked him about his organization’s business model for sustaining these delivery services, he simply said there was no model, that his humanitarian organization would simply foot the bill.

Surely we can do better. Just think how absurd it would be for a humanitarian organization to pay for their own 50 kilometer paved road to transport essential medicines by truck and decide not to recoup those major costs. You’ve paid for a perfectly good road that only gets used a few times a day by your organization. But 80% of the time there is no one else on that road. That would be absurd. Humanitarians who seek to embark on robotics delivery projects should really take the time to understand local demand for transportation services and use-cases to explore strategies to recoup part of their investments in building the aerial robotics infrastructure.

Surely remote communities who are disconnected from health services are also disconnected from access to other commodities. Of course, these local villages may not benefit from high levels of income; but I’m not suggesting that we look for high margins of return. Point is, if you’ve already purchased an aerial robot (drone) and it spends 80% of its time on the ground, then talk about a missed opportunity. Take commercial aviation as an analogy. Airlines do not make money when their planes are parked at the gate. They make money when said planes fly from point A to point B. The more they fly, the more they transport, the more they profit. So pray tell what is the point of investing in aerial robots only to have them spend most of their lives on the ground? Why not “charter” these robots for other purposes when they’re not busy flying medicines?

The fixed costs are the biggest hurdle with respect to aerial robotics, not the variable costs. Autonomous flights themselves cost virtually nothing; only 1-2 person’s time to operate the robot and swap batteries & payloads. Just like their big sisters (manually piloted aircraft), aerial robots should be spending the bulk of their time in the sky. So humanitarian organizations really ought to be thinking earlier rather than later about how to recoup part of their fixed costs by offering to transport other high-demand goods. For example, by allowing local businesses to use existing robotics aircraft and routes to transport top-up cards or SIM cards for mobile phones. What is the weight of 500 top-up or SIM cards? Around 0.5kg, which is easily transportable via aerial robot. Better yet, identify perishable commodities with a short shelf-life and allow business to fly those via aerial robot.

The business model that I’m most interested in at the moment is a “Per Flight Savings” model. One reason to introduce robotics solutions is to save on costs—variable costs in particular. Lest say that the variable cost of operating robotics solutions is 20% lower than the costs of traditional delivery mechanisms (per flight versus per drive, for example). You offer the client a 10% cost saving and pocket the other 10% as revenue. Over time, with sufficient flights (transactions) and growing demand, you break even and start to create a profit. I realize this is a hugely simplistic description; but this need not be unnecessarily complicated either.  The key will obviously be the level of demand for these transactions.

The way I see it, regardless of the business model, there will be a huge first-mover advantage in developing countries given the massive barriers to entry. Said barriers are primarily due to regulatory issues and air traffic management challenges. For example, once a robotics company manages to get regulatory approval and specific flight permissions for designated delivery routes to supply essential medicines, a second company that seeks to enter the market may face even greater barriers. Why? Because managing aerial robotics platforms from one company and segregating that airspace from manned aircraft can already be a challenge (not to mention a source of concern for Civil Aviation Authorities).

So adding new (and different types of) robots from a second company requires new communication protocols between the different robotics platforms operated by the 2 different companies. In sum, the challenges become more complex more quickly as new competitors seek entry. And for an Aviation Authority that may already be weary of flying robots, the proposal of adding a second fleet from a different company in order to increase competition around aerial deliveries may take said Authority some time to digest. Of course, if these companies can each operate in completely different parts of a given country, then technically this is an easier challenge to manage (and less anxiety provoking for authorities).

But said barriers do not only include technical (though surmountable) barriers. They also include identifying those (few?) use-cases that clearly make the most business sense to recoup one’s investments earlier rather than later given the very high start-up fixed costs associated with developing robotics platforms. Identifying these business cases is typically not something that’s easily done remotely. A considerable amount of time and effort must be spent on-site to identify and meet possible stakeholders in order to brainstorm and discover key use-cases. And my sense is that aerial robots often need to be designed to meet a specific use-case. So even when new use-cases are identified, there may still be the need for Research and Development (R&D) to modify a given robotics platform so it can most efficiently cater to new use-cases.

There are other business models worth thinking through for related services, such as those around the provision of battery-charging services, for example. The group Mobisol has installed solar home systems on the roofs of over 40,000 households in Rwanda and Tanzania to tackle the challenge of energy poverty. Mobisol claims to already cover much of Tanzania with solar panels that are no more than 5 kilometers apart. This could enabling aerial robots (UAVs) to hop from recharging station to recharging station, an opportunity that Mobisol is already actively exploring. Practical challenges aside, this network of charging stations could lead to an interesting business model around the provision of aerial robotics services.

As the astute reader will have gathered, much of the above is simply a written transcript me thinking out load. So I’d very much welcome some intellectual company here along with constructive feedback. What am I missing? Is my logic sound? What else should I be taking into account?