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Month: May 2022

The Engineering Challenges of Building an Autonomous Indoor Robot

Initially, we opted for speed over (near) perfection… then we learned our lesson…

Amit Moran, Co-founder and CTO

 When we embarked on the journey of designing and building an autonomous indoor flying robot – our signature product – we quickly realized the challenges would be multidisciplinary. 

As engineers know, creating a successful device or machine requires the integration of software, hardware, and algorithms. In building an indoor drone, all three of these components had to work hand in hand to address our primary challenge – namely to fly a drone indoors, in a confined space, without human control. 

Ghost in the Room 

One of the first challenges we encountered is what we fondly nicknamed “the ghost.” For some unknown reason, initially our Tando™ drone was seeing objects and walls that were not there. These “ghost” objects caused the drone to move in the wrong direction to avoid obstacles that did not exist.

Obviously it occurred just before a demo. We rushed to solve the problem. Stressed, we examined the mechanical structure of the sensors, thinking something was on the sensors’ way. Our algorithm engineers rushed to write algorithms that taught the flying robot to detect the probability of objects in its space and filter them out. Those are very useful till this day but they didn’t solve the problem. We had the feeling that we had tried everything. Then a software engineer researched and found that we can optimize the output by using a different driver. We tried that and like a charm – issue solved. 

Avoid Patches  

But that was just our first challenge. One of our innovations was to build a docking station for the drone that attached to the ceiling of structures like data centers and warehouses. By placing the dock on the ceiling, we created a device that could be useful 24/7. While it was docked (the majority of the day) it served as a security camera and charging station. When the drone went on its security or inspection missions, the dock acted as the drone’s home base. In other words, it’s a camera by day and a security guard by night.

In the beginning, however, the drone could not successfully attach to the dock. Every time it got close, the height sensors failed, causing the robot to go ballistic and frequently crash.  Again, we rushed through our protocols of checking the software, hardware, and algorithms. 

As the saying indicates “when you have a hammer, everything looks like a nail”, well at the time the majority of the R&D was software and algorithm engineers and we tended to solve anything with this. As a first step, our software and algorithms engineers wrote a program that instructed the drone to land safely on the ground if any sensor error occurred. But that was just a failsafe to prevent the drone from falling to the ground and causing injury or damage. To address the underlying cause of the docking issue eventually we turned to our electronic engineers who took control.

They discovered that each time the Tando touched the docking station, static interference was created that caused the sensors to go awry. Adding a capacitor on some of our sensitive sensors worked like a charm.  

We realized by then that we didn’t have a methodology to figure out the root of the different problems we are facing. Was it mechanical? Electronic? An algorithm issue? No one on our team could figure it out.

We decided that we needed to adopt a different approach: Since no one of us could fix the problem independently within our siloed fields, we had to work together as a team. Our first step was to nominate a lead investigator – a systems engineer or a senior developer who could offer a wide perspective on the entire process. We didn’t want to just patch the problem and move on. We wanted a holistic solution that would last for years to come. 

Swiss Cheese Navigation

Another significant engineering hurdle concerned navigation. Drones that operate outdoors use GPS to determine their location. But indoors, GPS is either unavailable or spotty. 

Indoor drone operation also requires the robot to move precisely. An outdoor drone can make navigation errors of a meter or two with no great effect on its performance. But in narrow indoor spaces, the margin for error is much less. A meter off, and the robot hits a person, a doorway, or art on the wall. 

To solve the navigation problem, we adopted the Swiss Cheese Model, a methodology used in risk assessment and analysis. This model postulates that problems can be mitigated by building a system in which different types of defenses are layered behind each other (like slices of Swiss cheese placed next to each other in which the holes appear in different places). One problem will hit the “cheese,” so to speak, while another will penetrate a hole. Nothing can slip all the way through.

Our navigation system combines a variety of sensors and algorithms. The Tando™ contains both cameras and a LIDAR detection system, which allow those two different sensors to work in tandem to mitigate risks and correct course. Since these layers are independent of one another, if a problem arises, there is no single point of failure. 

What We Learned 

Solving these three major problems and defining our work methodology spurred our growth as a company. Within our team, we confirmed that we have the talent and commitment to address any engineering, software, or hardware issue. And when our Tando™ unit was ready for market, we had produced an autonomous drone that accurately navigates the space around it, and that can attach and detach from its docking station 100% autonomously. 

We also learned that it’s better to solve problems correctly rather than quickly. There’s a temptation in startup culture to quickly bring a product to market. After all, time is money. But we discovered that a long-term fix to a problem creates a greater ROI over time than a temporary patch. 

We also discovered – through trial and error – how best to assign various engineering issues to our staff. Rather than assigning a single person to solve a problem, we decided to create mini teams. In turn, these teams built risk management tables that outline various plans for solving problems, along with likely outcomes and risk factors for each approach. This methodology also gave us parameters to define failure and stop work if a particular direction was not producing results. 

Growth Spurred by Innovation

In just four years, we’ve grown from two founders working out of a small coworking office to over 40 dedicated team members today. We’ve accomplished that growth through teamwork, the determination to solve engineering challenges, and the drive to bring advanced technologies to market. If you are an engineer who thinks like us, and takes pride and pleasure in solving problems, we’d love to hear from you. 


How to Bring the World the First Ceiling-based Docking Station for Indoor Drones

We travel to a lot of trade shows, customer sites and meetings in the USA, Canada and all across Europe. Inevitably, the question we hear most often is: How’d you do it? How did you get an indoor drone to dock on a charging and monitoring station mounted on the ceiling?  by Amit Moran, CTO & Co-Founder.

For us, it’s a thrilling question, because we love to talk about engineering challenges generally, and the software, hardware, and algorithms that made ceiling docking possible specifically.

Those kinds of engineering challenges are what animates us as professionals. (We’re geeks, we admit it!)
The conversations at these meetings also give us a chance to talk about our company, and the kind of culture we are cultivating. We tell people: at Indoor Robotics, we do things differently. We set out to solve problems – even though it’s hard, and even though others have failed in the past – because that’s what we do. We’re problem solvers.

But since not everyone comes to these shows, or has visited our offices in Israel, we decided to interview our CTO, Amit Moran, to provide some insight into the creative process that went into solving this particular engineering challenge.

What was the motivation to create a ceiling docking station that could be placed in public space like a mall or an office?

It all starts with a business need. We wanted to build a device that would be useful 24 hours per day, even while it’s docked – a camera by day and security guard by night.

Think about a different type of robot – a Roomba. A Roomba does its job cleaning the floor, then goes back to the docking station to charge. While it’s there, it does nothing but charge. It takes up space, energy and accumulates dust. It just charges. It’s passive.

So we wanted to build something that would be useful even while it’s docked. Our solution was to empower our autonomous flying robot, the Tando™, with a dual-purpose. While it’s docked, it acts as a security camera. But when it’s time for a security inspection, it releases itself from the docking station, carries out its mission, and then comes back to charge and monitor. Autonomously.

If we would not have done it this way, most out of the 24 hours of the day would have been wasted.
Our idea was that the Tando™ should always provide value. It can be a camera by day (while it’s docked) that can detect movement, stream video, and provide a security feed like any other camera. But when it needs to detach and go on its mission – or if an alarm goes off and it needs to investigate – it becomes a flying security guard. That’s why we created the solution of ceiling docking.

Can you describe the technical challenge involved in creating a ceiling-based docking station?

The first challenge was that no one had ever done it before.
There was no precedent, no model to follow. We had to invent a ceiling docking procedure and we had to invent the way it charges from the top.

We could have had the robot land on a shelf if we just wanted to solve the real estate problem, in other words the issue of where to dock the drone. But we wanted to solve the value problem and that’s more complex. We wanted the drone to be able to dock and charge efficiently, monitor its surroundings with its built-in cameras and sensors, and detach safely when needed. We came to the conclusion that the best way to do this is to make the drone attach and charge from its top side to the docking station, and that had never been done before.

First, we analyzed the problem and edge cases. One of those cases had us design a mechanism that would latch the drone securely during a natural catastrophe like an earthquake or a routine power outage. It had to stay connected, otherwise there was the concern it could detach and fall, creating a safety hazard.

Because we are docking on the ceiling, the docking mechanism itself – the way the drone positions itself and attaches – is critical. If the drone misses the docking station, it can fall. We could not be satisfied with a 95% success rate, nor with 99% either – it had to be 100%! How do you achieve 100%? In engineering, that’s never possible. So we’re at 99.999%, and in the 0.0001% case of an actual failure, the drone knows how to land safely, and alert the operators. For that scenario, we had to create a separate landing process.

Are there any technical advantages to an indoor drone docking on the ceiling?

Yes, less ground turbulence. When a helicopter tries to land, the air flow created by the rotors hits the ground and shoots back up. That is called “ground effect” and applies to both helicopters and drones. That phenomenon makes it hard for flying objects to land with precision and is the reason many docking stations of autonomous drones are bigger than the drone itself – to account for the ground effect and the problem it creates for landing. But that’s not the case on the ceiling.

When the drone is docked, how does it disconnect to start a security patrol?

This was very challenging. We had to take into account all the safety requirements – it had to detach with ease for a security mission but could never detach without a specific command. It also had to stay secure in any eventuality, like a power outage or earthquake.

We developed several solutions. From an algorithm and software point of view, there’s an important protocol between the drone and the docking station. Before it detaches, the drone self-tests its sensors, motors, processing unit, memory, battery and temperature. It needs to make sure it’s in good working order. Then it asks the docking station to detach through a confirmation process. An audible alarm and flashing lights indicate to its surroundings that Tando™ is about to detach, allowing anyone around to proactively create some space. The docking station then releases the drone via a mechanism that causes the magnetic force to weaken and allows the drone to go to its mission.

If at any point during this process, the system determines there is a problem, the process is aborted immediately. This can be done up to the very last second before Tando™ is detached.

What did you learn from creating the ceiling docking station for the Tando™?

Innovation requires the work of many different disciplines. It’s not just a great algorithm or robust software or an excellent mechanical design. What’s required is an out-of-the-box-thinking team, the desire to innovate, and the drive to make all these work together. And so much testing.

But the process was so fulfilling. By the end, we had 4 patents, and a whole new device to introduce to the indoor drone market. Not only for me, but for my team as well, it was an incredibly rewarding experience. Of course, we’re already on to the next engineering challenges, and having fun doing it.

Our market is expanding and we’re always looking for great people who are inspired by engineering, the technical problems it can solve, and the business opportunities it creates.
To talk to us about joining our team, contact us here.