Eric Frew News

Building next generation autonomous robots to serve humanity

Anonymous — Fri, 17 Nov 2023 23:11:12 +0000

Building next generation autonomous robots to serve humanity Anonymous (not verified) Fri, 11/17/2023 - 16:11

Jeff Zehnder

One thousand feet underground, a four-legged creature scavenges through tunnels in pitch darkness. With vision that cuts through the blackness, it explores a spider web of paths, remembering its every step and navigating with precision. The sound of its movements echo eerily off the walls, but it is not to be feared – this is no wild animal; it is an autonomous rescue robot.

Initially designed to find survivors in collapsed mines, caves, and damaged buildings, that is only part of what it can do.

Created by a team of ��񱦵� researchers and students, the robots placed third as the top US entry and earned $500,000 in prize money at a Defense Advanced Projects Research Agency Subterranean Challenge competition in 2021.

Going Futher

Two years later, they are pushing the technology even further, earning new research grants to expand the technology and create new applications in the rapidly growing world of autonomous systems.

“Ideally you don’t want to put humans in harm’s way in disaster situations like mines or buildings after earthquakes; the walls or ceilings could collapse and maybe some already have,” said Sean Humbert, a professor of mechanical engineering and director of the Robotics Program at ��񱦵�. “These robots can be disposable while still providing situational awareness.”

The team developed an advanced system of sensors and algorithms to allow the robots to function on their own – once given an assignment, they make decisions autonomously on how to best complete it.

Advanced Communication

A major goal is to get them from engineers directly into the hands of first responders. Success requires simplifying the way the robots transmit data into something approximating plain English, according to Kyle Harlow, a computer science PhD student.

“The robots communicate in pure math. We do a lot of work on top of that to interpret the data right now, but a firefighter doesn’t have that kind of time,” Harlow said.

To make that happen Humbert is collaborating with Chris Heckman, an associate professor of computer science, to change both how the robots communicate and how they represent the world. The robots’ eyes – a LiDAR sensor – creates highly detailed 3D maps of an environment, 15 cm at a time. That’s a problem when they try to relay information – the sheer amount of data clogs up the network.

“Humans don’t interpret the environment in 15 cm blocks,” Humbert said. “We’re now working on what’s called semantic mapping, which is a way to combine contextual and spatial information. This is closer to how the human brain represents the world and is much less memory intensive.”

High Tech Mapping

The team is also integrating new sensors to make the robots more effective in challenging environments. The robots excel in clear conditions but struggle with visual obstacles like dust, fog, and snow. Harlow is leading an effort to incorporate millimeter wave radar to change that.

“We have all these sensors that work well in the lab and in clean environments, but we need to be able to go out in places such as Colorado where it snows sometimes,” Harlow said.

Where some researchers are forced to suspend work when a grant ends, members of the subterranean robotics team keep finding new partners to push the technology further.

Autonomous Flight

Eric Frew, a professor of aerospace at ��񱦵�, is using the technology for a new National Institute of Standards and Technology competition to develop aerial robots – drones – instead of ground robots, to autonomously map disaster areas indoors and outside.

“Our entry is based directly on the Subterranean Challenge experience and the systems developed there,” Frew said.

Some teams in the competition will be relying on drones navigated by human operators, but Frew said ��񱦵�’s project is aiming for an autonomous solution that allows humans to focus on more critical tasks.

Although numerous universities and private businesses are advancing autonomous robotic systems, Humbert said other organizations often focus on individual aspects of the technology. The students and faculty at ��񱦵� are working on all avenues of the systems and for uses in environments that present extreme challenges.

“We’ve built world-class platforms that incorporate mapping, localization, planning, coordination – all the high level stuff, the autonomy, that’s all us,” Humbert said. “There are only a handful of teams across the world that can do that. It’s a huge advantage that ��񱦵� has.”

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Designing flying AI systems to study supercell thunderstorms up close

Anonymous — Wed, 08 Dec 2021 21:40:14 +0000

Designing flying AI systems to study supercell thunderstorms up close Anonymous (not verified) Wed, 12/08/2021 - 14:40

Jeff Zehnder

Above: Members of the ��񱦵� flight crew working on a RAAVEN drone in 2019 during a mission with a tornado in the distance.
Header: The RAAVEN drone flying near a storm system.

A team of ��񱦵� scientists and engineers have landed a major grant to design next-generation uncrewed aircraft systems (UAS) to fly into the heart of supercell thunderstorms that can spawn tornadoes.

“We’re trying to improve forecasts of severe weather,” said Eric Frew, a professor of aerospace engineering sciences. “There are things you can’t understand without flying into the storm from the air, things ground radar does not tell you.”

Frew’s team has earned a three-year, $1.5 million National Science Foundation grant to get closer than ever before to the heart of supercell storms: by launching probes that can fly directly inside them.

“We’re flying drones at the edge of storms and are being successful, but we can’t pierce the heart of the storm with the drone because the winds and precipitation are too strong,” said Frew, who is the principal investigator of the grant.

The goal of the research is to develop a drone that can fly as close to a storm as possible and then deploy a series of helium balloon probes carrying sensor packages that will be sucked into the center of the storms at altitude and report back data on the conditions inside.

While UASs are often remote controlled by humans on the ground, the goal of this system is for it to work fully autonomously. The UAV will make its own decisions about how close it can safely get to a storm and when it should release the probes, using artificial intelligence to make choices based on quickly changing storm conditions faster than a team of people could.

Developing this type of system is a new frontier in artificial intelligence research. Assistant Professor Zachary Sunberg is a co-principal investigator on the grant; his expertise is in high-performance artificial intelligence algorithms for decision making under uncertain conditions.

“The storms that we plan to study are extremely difficult to model, so there is a lot of uncertainty,” Sunberg said. “My role will be to use artificial intelligence to optimize the aircraft's path to deploy the balloons in the places that they will gather the most information about the storm. It is one of the most exciting applications of my artificial intelligence work.”

These systems will eventually be deployed in the field during storm-chasing campaigns. Frew and colleagues at ��񱦵� have made numerous multi-week excursions across the Great Plains following supercell storms and flying UAVs to gather data that can be analyzed by scientists to improve weather predictions and early warning systems for tornadoes.

“This has all been part of a 15-year vision of an autonomous airborne scientist. It used to be that being in the field was a barrier to communication. Now we have aircraft that have LTE and access to the internet, which opens us up to cloud computing. It makes for much more capable artificial intelligence,” Frew said. “The aircraft is just one part though. The science gathering is the aircraft, the team, the ground station computer, algorithms in cloud servers. We have the big brain of the internet at our disposal in ways we never did before.”

In addition to Frew and Sunberg, the research also includes Brian Argrow, professor of aerospace engineering sciences at ��񱦵�, and Adam Houston of the Department of Earth and Atmospheric Sciences at the University of Nebraska-Lincoln.

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NSF grants aim to improve security and safety of autonomous cars and systems

Anonymous — Fri, 30 Oct 2020 15:43:29 +0000

NSF grants aim to improve security and safety of autonomous cars and systems Anonymous (not verified) Fri, 10/30/2020 - 09:43

Researchers at ��񱦵� are leading four new NSF-funded projects that are exploring the safety and security of autonomous systems, including those used in self-driving vehicles.

The work is part of an international effort to address the significant safety and security obstacles to widespread adoption of these systems in the very near future.

Assistant Professor Majid Zamani is leading several of these projects within the Department of Computer Science. He is also part of the Autonomous Systems Interdisciplinary Research Theme in the college. He said this cluster of projects all address safety and security but embrace and apply knowledge from different fields such as control theory, formal methods and machine learning.

“One of the projects looks at how to prevent outside intruders from gaining private information about autonomous systems through their sensor measurements,” Zamani said. “Another ensures the actual auto-pilot systems–the embedded control software–work safely as intended, both in calm and warm days in Arizona and in snowy weather in Michigan, by embracing ideas from transfer learning.”

Assistant Professor Ashutosh Trivedi is also heavily involved in the work, leading one of the projects that looks at machine learning techniques for creating foolproof safety systems. A member of the research theme as well, he said the answers that will come out of this kind of work over the next three years will have many applications for aerospace systems and more tangible aspects of everyday life.

“The safety and security of cyber-physical systems will eventually go well beyond the autonomous cars we are working with here,” Trivedi said. “These systems are the technological backbone of the increasingly interconnected and smart world where a design fault or security vulnerability can be catastrophic to the system, to the user or to those around them. This work has implications for wearable and implantable medical devices, smart infrastructure and connected communities, to name only a few areas.”

Here are the project details including staffing and funding totals:

Project Title: CPS: Medium: Correct-by-Construction Controller Synthesis using Gaussian Process Transfer Learning
Principal Investigator: Majid Zamani, Department of Computer Science
Co-Principal Investigators: Morteza Lahijanian and Eric Frew, Department of Aerospace Engineering Sciences
Amount: $1,200,000
About: This project explores improvements to embedded control software for safety-critical cyber-physical systems in autonomous vehicles. Embedded control software forms the main core of autonomous systems wherein software components interact with physical systems such as traffic networks and power networks to name a few. These systems often have complex dynamics that are difficult to predict and ensure when it comes to safe operation. This project investigates a novel correct-by-construction controller synthesis scheme for these systems by embracing ideas from Gaussian processes. If successful, this could allow safety controllers developed for one type of autonomous vehicle to be transferred to another of a wholly new type – or for use in a new environment all together ¬– while still ensuring the original safety guarantee. This would save time on production and will be tested on underwater and aerial vehicles with an eye to future applications outside of self-driving cars.

Project Title: Secure-by-Construction Controller Synthesis for Cyber-Physical Systems
Principal Investigator: Majid Zamani, Department of Computer Science
Co-Principal Investigator: Ashutosh Trivedi, Department of Computer Science
Amount: $387,640
About: The security of autonomous vehicles from outside intruders is a new and growing area of research which has previously lagged behind more obvious safety concerns around the car’s actual operation. But because these vehicles collect and use a tremendous amount of personal data, they are appealing targets for hackers who can intrude through internet connected systems or other linked personal devices. From there they can deduce private internal information such as destination history or even potentially tamper with the vehicle. The proposed research aims to address this in parallel with the physical safety of the vehicle on the road. The ultimate goal is to develop algorithmic techniques and computational tools for constructing discrete controllers guaranteeing both safety and privacy properties, which are then automatically refined as hybrid controllers for the original systems. Doing would speed up overall development as security features would not have to be added on after the systems are already fully designed. This should also allow for more overlapping protection in both the physical and security arenas.

Project Title: SHF: Small: Omega-Regular Objectives for Model-Free Reinforcement Learning
Principal Investigator: Ashutosh Trivedi, Department of Computer Science
Co-Principal Investigator: Fabio Somenzi, Department of Electrical, Computer and Energy Engineering
Amount: $500,000
About: In reinforcement learning, software agents rely on and receive rewards that promote the achievement of given objectives or tasks. Scalar rewards can be used to reinforce the desired behavior, like keeping the car on the road and between the lines or withheld when drifting out of bounds. This machine learning technique has been demonstrated to be effective in many autonomous systems such as self-driving cars and manufacturing systems as well as other aspects of modern life such as social networks and internet connected devices. However, their integration into safety-critical settings for self-driving cars requires a new set of methods to ensure the decisions they ultimately make are the right ones. This project develops a rigorous approach to the design and verification of reinforcement learning-enabled systems that addresses issues of safety, efficiency, and scalability. This project also aims to develop an open source tool to create reinforcement learning algorithms to that end.

Project Title: An Entropy Approach to Invariance and Reachability of Uncertain Control Systems with Limited Information
Individual Principal Investigator: Majid Zamani, Department of Computer Science
Amount: $379,327
About: This project explores how autonomous vehicles can cope with limited bandwidth while interacting with cloud-based servers to share information and at the same time ensure their physical safety. Currently, communication systems, digital sensors, and microprocessors are being used by the car’s embedded control systems to respond to the needs and requests of external traffic network or the needs of the internal engine control for example. The interplay between those safety and reliability requirements – and the car’s ability to respect or enforce them – is key to keeping the vehicle safe on the road. While possible now, there is a finite amount of communication bandwidth available for maintaining that balance and the number of cars looking to use it is expected to go up over time. This research aims to establish the fundamental minimum data rates – or bandwidth – needed to make sure that the safety of the vehicles are not compromised. The results of this project will also enable the first step towards the efficient deployment of many innovative applications including underwater vehicles, sensor networks, and industrial control networks.

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Drones go underground in high-stakes competition

Anonymous — Thu, 06 Feb 2020 15:48:41 +0000

Drones go underground in high-stakes competition Anonymous (not verified) Thu, 02/06/2020 - 08:48

Roughly one story belowground, in an undisclosed location in Boulder County, close to a dozen engineers hustle up and down a series of utility tunnels—a network of corridors filled with pipes and lit only by sporadic lightbulbs.

The students and faculty members have come to this dim and dusty environment this morning to do something they can’t do aboveground: test out a fleet of autonomous vehicles, or drones. These robots, which are called “Huskies,” are several feet tall and look like what you might get if you crossed a radio-controlled car with a Humvee.

And they’ll soon become part of ��񱦵�’s efforts to achieve new feats of spelunking.

That’s because these engineers are contestants in the Subterranean Challenge, a high-stakes competition launched by the U.S. Defense Advanced Research Projects Agency (DARPA). Over three years, teams of researchers from across the world will vie against each other to push their robotics knowledge to the limits—designing vehicles that can navigate underground environments just like this one.

Sean Humbert, a professor in the Paul M. Rady Department of Mechanical Engineering, leads the ��񱦵� contingent, one of six funded teams in the challenge. This $4.5 million-dollar collaboration, dubbed Multi-agent Autonomy with Radar-Based Localization for Exploration (MARBLE), also includes engineers from CU Denver and the Massachusetts-based Scientific Systems Company, Inc.

Humbert hopes that the technology developed by his research group will one day lead to rolling or flying drones that can scour caves or collapsed subway tunnels around the world—and find the human survivors trapped inside.

But first, he and his colleagues will need to pass three grueling tests and a final event designed by DARPA.

They’ve already completed one test, a search-and-rescue operation that took place in an old coal mine in Pennsylvania. Their next trial takes place later this month and will bring the group to an abandoned research facility near Olympia, Washington.

“It was really impressive to see all of our outstanding students troubleshoot and solve problems real-time in the field,” Humbert said. “There will certainly be some ground-breaking science and engineering products that come out of this program, but I think the lasting contribution will be the next generation of field roboticists.”

A harsh world

Some of those field roboticists are gathering now in the utility tunnels.

The ��񱦵� team has set up an operations center of sorts in one corner of this area, complete with a folding table and several computer monitors.

“We’ve become pretty used to sitting in the dust,” said Michael Ohradzansky, a graduate student in the Department of Computer Science.

Top: MARBLE team members ready a Husky robotic vehicle to enter Edgar mine; middle: The LIDAR system mounted on top of this Husky allows the robot to navigate underground; bottom: Michael Ohradzansky (pointing) and team members look on at the challenge arena during a search-and-rescue event in Pennsylvania (Credits: ��񱦵� College of Engineering and Applied Science, top and middle; DARPA, bottom)

He and his teammates type a series of commands into a computer, and a nearby Husky revs to life. It begins to roll down the connecting corridor, dodging the pipes that stick out at all angles. Soon, the robot disappears around a bend, leaving the space behind it dark.

“All this is testing autonomy,” said Christoffer Heckman, an assistant professor in computer science and a MARBLE team member.

Once the researchers press go, their robotic vehicles must be able to work together to perform their searches—all without the aid of a human operator.

That’s where things get tricky.

“Underground environments are very harsh,” Heckman said. “They don’t have very good lighting. They can be filled with gas and smoke. They can be very muddy or wet.”

Autonomous vehicles, in other words, face a different set of challenges deep underground than they would in a lab or even on city streets.

Take vision: To see in such environments, Heckman and his colleagues are designing robots that view their surroundings using three different types of sensors. They include a traditional camera, radar and a laser-based system called Light Detection and Ranging (LIDAR).

Mapping is a big problem, too. The team’s drones, Heckman explained, won’t have access to GPS in the subterranean realm. That means they’ll have to enter a completely new environment, sketch out its twists and turns and even trade maps with other robots all on their own.

“When we go into a building, humans automatically develop a 3D map in their heads,” Heckman said. “That can tell you where stairs are, where elevator shafts are. Those are the kinds of features we want our autonomous vehicles to take away from an area.”

Taking flight

When the group traveled to the Pennsylvanian mine in August 2019, they faced an obstacle course of sorts.

Just before the event, DARPA hid a series of objects throughout that arena—life-sized dummies, red backpacks and cell phones. To score points, the MARBLE team released a fleet of Huskies into the mine, allowing the drones to seek out and pinpoint the location of those Easter eggs.

“Once we see an object, we can back-calculate its position relative to the starting gate,” said Michael Miles, a graduate student in computer science.

The group just missed out on placing in the top three finishers, Miles said, when one of their Huskies got stuck in about a foot of mud.

But he and his colleagues are raring to go for their next chance, which will kick off Feb. 18 in Washington State. The third challenge is slated for August 2020 and the final test a year after that.

This month, the researchers’ robots will have to explore several floors instead of one, forcing them to climb up stairs and scan lofty atria for lost dummies.

To enable them to do that, Miles and his team members have converted several of their Huskies into “aircraft carriers.” These robots will haul flying quadcopters deep into the competition arena, then launch those drones to explore where rolling vehicles can’t.

“I’m feeling pretty good about this challenge,” Miles said. “We’ll be working 70-hour weeks in the lead-up, but I think we learned a lot from last time.”

Fellow graduate student Ohradzansky added that the long days are worth it. He said that the project has given him and his team members a chance to do something that few university robotics researchers ever get to do—test their creations in the real, and very messy, world.

“Many researchers tend to stay in the realm of simulations, and everything works perfect in simulations,” he said. “What’s really different about this is we actually go out into the field, and that’s where you get a whole new level of challenge.”

��񱦵� MARBLE team members also include Eric Frew, a professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences. CU Denver team members include Mark Golkowski, Ron Rorrer, Jae-Do Park and Vijay Harid.

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Solving AI’s (over)confidence problem

Anonymous — Tue, 07 Jan 2020 15:50:19 +0000

Solving AI’s (over)confidence problem Anonymous (not verified) Tue, 01/07/2020 - 08:50

Jeff Zehnder

Nisar Ahmed and Eric Frew

��񱦵� researchers are developing artificial intelligence systems so computers can recognize and explain their own limitations to users.

It takes on an important issue people face with each other every day.

“We all have different competencies and we know our own limitations. If I'm asked to complete a task, I generally know if I can do it. Machines aren't programmed like that,” said Nisar Ahmed, an assistant professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences at the ��񱦵�.

Ahmed is serving as principal investigator at ��񱦵� on a new, multi-university grant from the Defense Advanced Research Projects Agency.

The $3.9 million grant, which is being led by the Charles Stark Draper Laboratory and also includes the University of Texas at Austin, seeks to build “competency-aware machine learning”—essentially, machine learning systems that, when given a task, can tell you if they'll be able to do it and also explain why.

It is an area with broad and serious applications, according to Eric Frew, a ��񱦵� aerospace professor serving as a co-investigator on the project.

“Do you trust this drone to deliver a package of medicine, or do you take it in your own car, which will take three times as long to get there? If you're a soldier, do you trust a drone to go over a hill and search for an enemy? Will it be thorough enough?” Frew said.

Ahmed notes the engineers who design drones generally understand their every capability or lack thereof, but end-users naturally will not have the same level of knowledge. A drone that can tell you if it will likely be successful in completing a task should be more trustworthy to the operator.

The work is focused on unmanned aerial vehicles but has applications to ground robots and other AI systems.

“It's a combination of aerospace, computer science, and a little bit of psychology,” Ahmed said. “It's very interdisciplinary.”

The goal is not to pre-program drones with every possible mission or obstacle they could face, but rather develop a learning-based AI that has a base level of knowledge and can think abstractly in new situations and explain its decisions – just like people do.

“Humans are generally better than machines at adapting to unknowns, taking an unforeseen problem they have never faced before and comparing it to past events to find solutions. Machines haven't been programmed like that up to now,” Ahmed said.

Frew compares it to a situation understood by nearly all American adults - getting your driver's license.

“We don't test you on every possible circumstance you could face as a driver. We give you a driving test that covers a handful of situations and a knowledge test and then trust you with a license and that you can use reasoning behind the wheel,” Frew said.

Over the course of the grant, they will develop new competency-awareness assessment algorithms for AI systems, and then put them to the test using drones.

“We’re working on a problem that has mostly gone unnoticed in the computing, machine learning, and AI world, but gets at questions a lot of people have about trust. Will this robot do what I tell it to? Can it?” Ahmed said. “By developing systems that are aware that they have lots of answers, but don't have all the answers all the time and can tell us that, it should make them easier to use. I'm very excited about the possibilities.”

��񱦵� researchers are developing artificial intelligence systems so computers can recognize and explain their own limitations to users.

It takes on an important issue people face with each other every day.

“We all have different competencies and we know our own limitations. If I'm asked to...

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Students critical to massive drone study of tornadoes

Anonymous — Fri, 25 Oct 2019 23:57:30 +0000

Students critical to massive drone study of tornadoes Anonymous (not verified) Fri, 10/25/2019 - 17:57

Researchers from ��񱦵� flew drones into severe storms this spring for project TORUS, one of the largest and most ambitious drone-based investigations of meteorological phenomena ever, with students leading much of the work.

Project TORUS—Targeted Observation by Radars and UAS of Supercells—is a partnership between ��񱦵�, the University of Nebraska-Lincoln (which is leading the work), Texas Tech University, the University of Oklahoma and the National Severe Storms Laboratory that will continue into 2020. The goal of the project is to collect data to improve the conceptual model of supercell thunderstorms—the parent storms of the most destructive tornadoes—to improve forecasting. According to Smead Aerospace Professor Eric Frew, a principal investigator on the project, better forecasting means more warning time and fewer false alarms, which could save lives in the future.

“What was really exciting about what we were able to accomplish was that these drones were designed, fielded and operated by students,” Frew said. “I had sophomores and juniors on this team accomplishing something that had never been done before.”

Funding for the project came from the National Science Foundation and the National Oceanic and Atmospheric Administration. Support also came from the ��񱦵� Grand Challenge.

��񱦵�’s portion of the project was led by faculty from the College of Engineering and Applied Science through the Integrated Remote and In Situ Sensing initiative. The team was responsible for piloting up to three drones around the storms simultaneously to measure temperature, pressure, humidity and wind speeds. Drones are a critical component of the overall TORUS project because they sense data from inside the storm—data that cannot be obtained without physically being there to take the measurements. That information will be combined with remote sensing data obtained by the other collaborators collected around the same storm later.

In all, the ��񱦵� team totaled over 40 hours of air time on 51 flights, including seven tornado-producing storms, over the nearly monthlong deployment throughout the Great Plains.

The university has been using drones for this type of work since 2010 and was the first in the world to do so. The lessons learned over the years informed the design of the new unmanned aircraft used this spring. Built from lightweight yet high-strength foam from RiteWing RC, the drones include an avionics system and many other aspects custombuilt by the team. They are also modular in design, allowing for fast and easy repairs in the field.

Aerospace engineering senior Danny Liebert pilots one of the drones for the team and said he loves how rugged it is compared to the previous “TTwistor” model.

“The TTwistor drone we used was great but just not as durable. These new aircraft are awesome. They take it like a champ out there,” he said. Frew said he can envision a future in which drones are used as forward deployment tools for weather prediction and data collection. Work on TORUS and future projects can make that a reality.

“We can see the technology advancing to a point where small towns or individuals have these drones and they release them into precursor environments to help feed into the weather forecasting system, much like the citizen scientists who report temperature and snow or water accumulations every day around the U.S.,” he said.

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Brainwaves Podcast - Natural disasters: How new science will help us survive

Anonymous — Wed, 07 Aug 2019 21:42:55 +0000

Brainwaves Podcast - Natural disasters: How new science will help us survive Anonymous (not verified) Wed, 08/07/2019 - 15:42

Tornadoes, floods, fires and more affect 160 million people per year worldwide. On this episode of the ��񱦵� Brainwaves podcast, what science is doing to help people and their property survive.

Interviews include Lori Peek, director of the Natural Hazards Center, Brian Argrow and Eric Frew with the TORUS Project and Michelle Meyer, a researcher looking at how men and women behave differently in natural disasters and are treated differently afterwards.

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The air up there: CU team deploys multiple drones in tornado study

Anonymous — Mon, 01 Jul 2019 15:55:30 +0000

The air up there: CU team deploys multiple drones in tornado study Anonymous (not verified) Mon, 07/01/2019 - 09:55

It’s a little after 6:30 p.m. when Aidan Sesnic calls a huddle for members of the ��񱦵� TORUS team on the side of a lonely dirt road in rural Oklahoma. This particular safety briefing would be standard, if not for the large black- and green-tinged supercell thunderstorm crawling across the soft, rippling plains behind him.

Sesnic is bathed in warm light from the rapidly setting sun as he calmly and quickly lists the weather conditions and possible issues, such as powerlines near the landing space, from a checklist. The aerospace engineering sophomore’s group is one of three nearby, all preparing to launch unmanned aircraft to gather data about the storm.

Together, these groups are taking part in TORUS—the largest and most ambitious drone-based investigation of severe thunderstorms ever. The goal is to learn more how supercell thunderstorms form tornadoes and eventually to increase tornado warning times. Faculty, staff and students like Sesnic from the College of Engineering and Applied Science are at the heart of it all.

When the briefing ends, Sesnic pilots a drone up and into the area near the storm to collect wind speed, air pressure, precise GPS location data, and other information about the storm that ground-based research teams simply cannot get. The process is made more impressive by the speed with which it occurs. Depending on other teams’ success that evening–and the storm itself–Sesnic’s group can redeploy to get more data or quickly move out of danger should the storm shift. That level of mobility, flexibility and coordination is unprecedented for a CU team that has become quite experienced in this potentially life-saving research area over the last 25 years.

Above: Alex Hirst, a graduate researcher, helps get a drone ready for launch.
Below: Sara Swenson, a graduate researcher, makes an adjustment to a drone. Photos by Josh Rhoten, CEAS

Meet the RAAVEN

Project TORUS–or Targeted Observation by Radars and UAS of Supercells–is a two-year partnership between ��񱦵�, the University of Nebraska-Lincoln (which is leading the work), Texas Tech University, the University of Oklahoma and the National Severe Storms Laboratory. Funding comes from the National Science Foundation and the National Oceanic and Atmospheric Administration. Support also comes from the CU Grand Challenge and the Integrated Remote and In Situ Sensing initiative, or IRISS. The goal is to collect data to improve the conceptual model of supercell thunderstorms, the parent storms of the most destructive tornadoes, to help with future forecasting and warning.

In 2010, ��񱦵� engineers were the first in the world to deploy an unmanned aircraft system to collect data from supercell thunderstorms. The lessons learned from constructing and using that aircraft and the following versions informed the design of the new RAAVEN aircraft.

Piloted by students and staff, the drones were catapulted from the roof of an SUV, or a launcher placed on the ground, into the storms in spring 2019. In all, the CU team deployed up to three aircraft simultaneously, totaling over 40 hours of air time on 51 flights, including seven tornado-producing storms.

RAAVEN stands for Robust Autonomous Aerial Vehicle – Endurant and Nimble. Built from lightweight yet high-strength foam from RiteWing RC, the drones also include an avionics system and many other aspects custom-built by the IRISS team. That includes the car launch system, which can launch a 15-pound aircraft up to 50 mph in less than a second.

The drones are modular in design, meaning parts from one can be used to repair another. The result is fewer down days for large repairs and easier fixes in the field. They also don’t use landing gear, removing a breakable part and making it easy to land the aircraft virtually anywhere.

“The way we launch these and their durability have made us much nimbler in responding and re-deploying than we have been in the past,” said CU IRISS Engineering Manager Steve Borenstein. “I don’t think we could have designed these to work as well as they have during this project without the time in the field we have had–experiencing the conditions, making repairs and learning what was needed to get these up and get the data back.”

Aerospace engineering senior Danny Liebert pilots one of the drones for the team and said he loves how rugged it is compared to the previous “TTwistor” model.

“The TTwistor drone we used was great but just not as durable. These new aircraft are awesome. They take it like a champ out there,” he said.

IRISS Director and CU Project Co-Leader Brian Argrow said the drones have exceeded expectations for toughness and flexibility, but that isn’t the most impressive aspect of the aircraft in his mind.

“The work Steve has done with data flow and communications management on these is just as important as the airplane itself,” he said. “The things he has refined have enabled us to deploy three teams simultaneously, connected with each other and integrated with meteorologists. I am as amazed by that as I am the aircraft.”

Above: Graphic design by Rochelle Zamani, words by Josh Rhoten.
Below: Professor Brian Argrow talks with a team member between deployments. Photo by Josh Rhoten, CEAS

Getting the information needed to save lives

Smead Aerospace Professor Eric Frew explains the logistical challenges of the project with the wry smile of someone who has learned a great deal of patience over his years in the field on this and similar projects.

“We call it hurry up and wait,” said Frew, who is leading the CU portion of the project with Argrow. “We call it that because you really want to position yourselves and then see what the weather's doing. Then you wait until you have a good sense of things before you rush to the next stop. We are doing this with a large team all across the Great Plains, so it really is quite a logistical challenge.”

Teams conducted fieldwork from May 13 through June 16 and covered virtually all of the Central Plains including parts of Texas, Nebraska, Kansas, Oklahoma and Colorado. It was an especially busy storm season, particularly in May, with more than 200 tornadoes reported across the entire U.S. May also included a 12-day streak with at least eight reported tornadoes, smashing the previous record set in 1980 and showing how severe the season was inside and out of the TORUS operations area.

Mornings on the project start with a weather briefing about where the team might have the best chance to intercept a supercell storm. Team leaders also look at possible intercept locations for the next two days, factoring in Federal Aviation Administration restrictions, travel distance and hotel availability for the more than 50 professional and student scientists participating. From there, it’s “hurry up and wait” with storm tracking, data collection and recovery often going late into the night. It’s a grind for the team, but data collected by these drones could have tremendous value when it comes to prediction of tornado behavior. That’s because certain variables, such as humidity, cannot be accurately measured without actually touching the storm with precise instruments. Weather balloons can get some of this information, but a fixed-wing drone offers several advantages, including more control over the specific collection points.

2019 ��񱦵� team roster

Brian Argrow – PI, director of IRISS, AES professor
Eric Frew – PI, AES professor
Steve Borenstein – IRISS engineering manager
Chris Choate – IRISS aircraft systems engineer/pilot
Michael Rhodes – IRISS lab manager
Dan Hesselius – Director of flight operations for IRISS
Laura Clayton – Program manager, IRISS
Dominic Dougherty – AES junior, flight crew
Alex Hirst – AES PhD student, flight crew
Dishank Kathuria – AES junior, flight crew
Cole Kenny – AES senior, flight crew
Danny Liebert – AES senior, flight crew
Anders Olsen – AES junior, flight crew
Aidan Sesnic – AES junior, flight crew
Sara Swenson – AES PhD student, flight crew

That all plays into the team's goal of exposing how a storm's unique structure contributes to tornado formation. Understanding this aspect better would reduce the number of false-alarm tornado warnings and improve detection of the potentially lethal storms.

“Something like 95% of the most violent tornadoes come from a supercell thunderstorm, but only single-digit percentages of supercells create these tornadoes,” Frew said. “So in order to understand what about this particular storm is leading to a tornado, you need to have a lot of data where that transition does happen and a lot of data where that transition doesn't happen so you can see what's different. Ideally, half of our data comes from storms that produce tornadoes and the other half comes from those that don’t.”

Frew said he can envision a future in which drones are used as forward deployment tools for weather prediction and data collection, responding to weather models and data from other drones in real time to decide where to go next. Work on TORUS and future projects can make that a reality.

“We can see the technology advancing to a point where small towns or individuals have these drones and they release them into precursor environments to help feed into the weather forecasting system–much like the citizen scientists who report temperature and snow or water accumulations every day around the U.S.,” he said.

With another year of fieldwork in 2020 still to come, it is too early to know what the data collected so far by the TORUS team says about supercell formation.“There’s no question that we’ve taken new, novel data that’s never been collected before,” Frew said. “But we want to get a lot of data before we really look at it and try to make some conclusions. We scheduled two years because that's what we think it takes to have a really strong dataset.”

AES senior Danny Liebert : “These new aircraft are awesome. They take it like a champ out there." Rhoten, CEAS

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Podcast: AES Professor Frew on drone based storm research, airborne scientists and the movie "Twister"

OnCue talked to Professor Eric Frew about how drones are contributing to cutting edge storm research, long travel days with the project, and expectation versus reality in the '90s classic tornado movie "Twister." Read more

Meet the other teams involved in TORUS 2019

��񱦵� worked with the University of Nebraska-Lincoln, Texas Tech University, the University of Oklahoma and the National Severe Storms Laboratory on the project. Read more

Meet the RAAVEN drone that gathers data from the storms

��񱦵� engineering has a long history of using drones to study severe storms and tornadoes. See the technical specs for the RAAVEN, the most flexible and sophisticated tool ever used for this kind of work here. Read more

Researchers from ��񱦵� flew drones into severe storms this spring in one of the largest and most ambitious drone-based investigations of meteorological phenomena ever.

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CU researchers using drones to study tornados over Central Plains

Anonymous — Tue, 30 Apr 2019 18:06:50 +0000

CU researchers using drones to study tornados over Central Plains Anonymous (not verified) Tue, 04/30/2019 - 12:06

Project TORUS – or Targeted Observation by Radars and UAS of Supercells – is a partnership between ��񱦵�, the University of Nebraska-Lincoln (which is leading the work), Texas Tech University, the University of Oklahoma and the National Severe Storms Laboratory. Funding comes from the National Science Foundation and the National Oceanic and Atmospheric Administration. Support also comes from the CU Grand Challenge program and the Integrated Remote and In Situ Sensing initiative. The goal is to collect data to improve the conceptual model of supercell thunderstorms – the parent storms of the most destructive tornadoes – to help with future forecasting.

Fieldwork will run from May 13 through June 16 and will cover virtually all of the Central Plains including parts of North and South Dakota, Texas, Iowa, Wyoming, Nebraska, Kansas, Oklahoma and Colorado. It is the largest study of its kind based on the geographical area covered and the number of drones and other assets to be deployed. The list of equipment for the project includes four unmanned aircraft systems, a NOAA P3 manned aircraft, eight trucks equipped with meteorological instruments, three mobile radar systems, a mobile LIDAR system, and three balloon-borne sensor launchers.

In all, more than 50 scientists and students from the four universities will participate. This year the CU team includes three faculty, four staff members, five graduate students (including one international visiting graduate student) and six undergraduate flight crew members.

The CU team hopes to expose how small-scale structures within the storm — believed to be invisible to all but the most precise research-grade instruments — contribute to tornado formation. Understanding this better would reduce the number of false alarm tornado warnings and improve detection of the potentially lethal storms.

CU’s portion of the project is led by faculty from the College of Engineering and Applied Science through the Integrated Remote and In Situ Sensing initiative. The team is responsible for piloting the four drones around the storms to measure temperature, pressure, humidity and wind speeds. Drones are a critical component of the project because they sense data from inside the storm – data that cannot be obtained without physically being there to take the measurements. Combined with remote sensing data obtained by the other collaborators, the expectation is that these measurements will help reveal how severe storms evolve to create tornados.

The principal investigators at CU are Aerospace Department Chair Professor Brian Argrow and Professor Eric Frew. Both have years of experience and multiple field deployments doing this kind of work and will be on the road with the team this spring. Frew said this project is a great representation of their ongoing research, expanding partnerships and CU’s recognized expertise in the field.

“This project is the result of partnerships that have developed over the past 15 years to conduct this type of deployment,” he said. “In 2006 Associate Professor Adam Houston, the overall Project TORUS leader from the University of Nebraska, visited Professor Argrow here in Boulder, and they created the initial concept of operations for studying supercell thunderstorms with drones. Since then we have created new partnerships together and collaborated on several projects designing the technologies used for this mission.”

IRISS Chief Engineer Steve Borenstein said the opportunity for hands-on experience for students through the project, as well as the opportunity to observe severe weather with some of the nation’s top meteorologists is unrivaled.

“Our field campaigns challenge the entire team every day in terms of solving logistical problems and technical troubleshooting. Every student has a critical role in the preparations and mission deployments, including pilots, operators, and ground support,” he said. “Deployments are a tough three weeks, but the students leave with experience and memories that will last them forever.”

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CU is diving into the field of autonomous submarines

Anonymous — Tue, 23 Apr 2019 06:00:00 +0000

CU is diving into the field of autonomous submarines Anonymous (not verified) Tue, 04/23/2019 - 00:00

��񱦵� researchers are taking a deep dive into the realm of autonomous submarines through a Small Business Technology Transfer contract sponsored by the Office of Naval Research.

The work, which entered phase two last month, pairs the ��񱦵� Research and Engineering Center for Unmanned Vehicles center with Orbit Logic — a Maryland-based company with expertise in mission planning and scheduling across a variety of platforms and domains. The goal is to create autonomous submarines that can work together on long missions. That includes military applications like tracking an enemy or a scientific mission like exploring the sea floor.

Smead Aerospace Engineering Sciences Assistant Professor Nisar Ahmed said the work, titled Data Architecture Enabling Robust Cooperative Autonomy with Minimal Information Exchange, has been difficult but interesting because it is a new realm of operation for the team.

“Underwater is a totally new domain for us. There is a lot of commonality between what we are doing here and what we have done with autonomy in the air or the ground, but there are unique challenges that come with being underwater. Things like limited bandwidth, power availability and trouble with sensing,” he said.

Professor Sonia Martinez in the Mechanical and Aerospace Engineering Department at the University of California San Diego and SPAWAR Systems Pacific are also collaborating on the project.

The Small Business Technology Transfer program aims to “bridge the gap between performance of basic science and commercialization of resulting innovations” by linking businesses with researchers through federal dollars. In the program, federal funding from programs like the Department of Defense or the National Science Foundation is distributed as awards on a competitive basis. Funds given during phase one are generally used to establish technical merit, feasibility and commercial potential of the proposed research.

Phase one of this project showed:

That teams of underwater vehicles can stay in communication with limited bandwidth for planning and keeping track of each other without GPS.
How drones could explore a larger area by coordinating sweep patterns.
It was possible for one drone to call another after discovering something interesting outside of the planed route for help or further study.
That data could be collected from surfaced submarines and ferried back to base through aerial drones as a proof of concept.

Communication between underwater subs will be at the heart of the next phase, Ahmed said.

“Knowing what the vehicle is up to and where it is going — seeing what it wants to think about doing — is really hard,” he said. “Tethering them limits range and adds complexity. You want them to be autonomous, but also be in contact constantly. The other side of that though is that for military operations you don’t want them pinging constantly.”

Kenneth Center of Orbit Logic, the principal investigator on the research program, is eager about the work that will accomplished by the team in the next year.

“We are very excited about running this solution on real underwater vehicles. So often, fundamental research gets stuck in the laboratory without an opportunity to show its value,” he said. “This team will be demonstrating real capabilities, including using a Fleet Planning Tool to determine how a set of underwater vehicles can be configured to meet mission objectives – then load autonomous software onto the vehicles and see how well they do at meeting those objectives, even if unexpected conditions are encountered.”

Ahmed is part of the Autonomous Systems Interdisciplinary Research Theme in the college, and his co-PI Eric Frew is the director of the initiative. A new seed grant from the theme is attached to phase two and will be used to purchase an underwater vehicle for future testing. That vehicle will also be used in other research projects and by the student RoboSub team.

“This project highlights how the Autonomous Systems Interdisciplinary Research Theme is helping CU researchers expand in to new areas,” said Frew. “The new hardware provided by the seed grant gives this project the ability to conduct testing in realistic conditions and supports other faculty who are expanding their work from drones and self-driving cars into underwater vehicles and spacecraft applications.”

The ultimate goal is to have multiple vehicles to explore questions around communication and user experience.

“We want to make it easier for anyone to use these things, so they don’t have to have 15 windows open on a computer screen to explore a lake. That is part of the commercialization aspect of this project,” Ahmed said.

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