Nisar Ahmed News

Designing autonomous robots for use on Mars and closer to home

Anonymous — Mon, 15 Jul 2024 14:54:08 +0000

Designing autonomous robots for use on Mars and closer to home Anonymous (not verified) Mon, 07/15/2024 - 08:54

Jeff Zehnder

Preparing to engage the robot during the MDRS mission.

Pawel Sawicki (BioMedEngr MS’22, AeroEngr PhD’23) is exploring the barren landscape of Mars and testing out critical new technologies through a one-of-a-kind experience here on Earth.

Welcome to the Mars Desert Research Station, an “analog” astronaut research facility in the remote Utah desert. Operated by the Mars Society, the center gives scientists and engineers the opportunity to test out future space experiments without a long space journey.

Sawicki, a University of Colorado Boulder master’s and PhD alumnus, recently returned from the base, where he spent two weeks as a mission commander with a six-member crew. The team lived and worked under conditions remarkably similar to what NASA astronauts will face on the red planet.

“It was pretty exciting. We lived in the station and to go outside we had to wear EVA suits,” Sawicki said. “We’re simulating life on Mars so we can learn how to design experiments, equipment, and operations for when astronauts really go and face that challenge.”

Along with a series of geological and nuclear experiments was a 30 lb., four-wheel, ground robot provided by Nisar Ahmed, an associate professor of aerospace at the University of Colorado Boulder.

Robots will be important on future Mars missions, but only if users can easily understand their capabilities and limitations, said Nick Conlon, one of Ahmed’s PhD students in the Ann and H.J. Smead Department of Aerospace Engineering Sciences.

Ahmed’s lab is focused on developing methods so a robot can accurately tell operators how well it will be able to do a task. Called Factorized Machine Self-Confidence, the system will give users an easy way to grasp how competent the robot is.

“The objective was to use the robot to take video autonomously in different areas to create a 360 view of the environment, like Google Maps Street View,” Conlon said. “Before the robot starts as task, it analyzes its internal models to report if it can achieve the goal. Can it drive to a certain area, does it have enough battery to get back, can it avoid obstacles? Things like that.”

Conlon delivered the robot to MDRS and demonstrated the technology prior to the analog mission beginning.

While astronauts are likely to be highly trained on their equipment, the goal of this robotics research is to make it possible for regular users to utilize the technology with little trouble.

“People have different ideas of what a robot might be capable of,” Conlon said. “We don’t want them to over trust a piece of equipment and break it or get hurt or drive off a cliff. We also don’t want people to under trust and have it sit and collect dust in a corner. We want people to use it within its limits and want to use it.”

Conlon said much of the research with the robot thus far has been in controlled environments, making Sawicki’s MDRS mission a unique deployment opportunity.

“We’ll be writing a paper from all we’ve learned from this experience,” Sawicki said. “One of the key findings is just how to make the system super robust for a field study, taking it on an EVA, and wearing a spacesuit in the process.”

Although there were some early diagnostic issues, the robot was able to complete all of the requested site surveys, and both Conlon and Sawicki are hopeful the data will be helpful for subsequent MDRS missions.

One unique challenge that will face future Mars astronauts is communicating with home. Due to the massive distance between the red planet and Earth, one way transmissions have a minimum delay of 8-10 minutes. That makes any live calls impossible. The same restrictions are imposed on the analogue astronauts.

“The isolation was definitely a mental challenge. Nick was back in Colorado and when I had to work with him on an issue with the robot, there are no phone calls and you can’t exchange messages quickly. You send an email and wait,” Sawicki said.

Participating in an MDRS mission fulfilled a goal Sawicki had held since his time as a grad student. ��ý�Ļ��Ʒ offers a course called Medicine in Space and Surface Environments that takes students to MDRS, but during his PhD program Sawicki was unable to make it work with his schedule.

He reached out to MDRS after graduating to sign up for a mission on his own and they offered the opportunity to be mission commander.

“My PhD was in hypersonics but I had taken all of these bioastronautics classes and they said you’re a great fit for this mission,” Sawicki said. “I learned the trials and tribulations of what goes into an isolated mission like this, maintaining crew stability, scheduling. It was a great learning experience for me, and a unique opportunity for Ahmed and Conlon to learn about how future astronauts may one day work with, and alongside, autonomous robots.”

The MDRS 297 mission patch, with the team member names and the robot in lower left.

Pawel Sawicki is exploring the barren landscape of Mars and testing out critical new technologies through a one-of-a-kind experience here on Earth. Welcome to the Mars Desert Research Station, an...

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��ý�Ļ��Ʒ, industry partner on space docking and satellite AI research

Anonymous — Mon, 03 Jun 2024 15:00:58 +0000

��ý�Ļ��Ʒ, industry partner on space docking and satellite AI research Anonymous (not verified) Mon, 06/03/2024 - 09:00

Jeff Zehnder

Hanspeter Schaub standing in front of a vacuum chamber in his lab that will be used in the the research with In Orbit Aerospace.

Docking with a satellite orbiting Earth is delicate business, with one wrong move spelling disaster. A team of industry and University of Colorado Boulder researchers is trying to make it easier.

The work is part of two major business-university grant partnerships that include the lab of Hanspeter Schaub, a professor and chair of the Ann and H.J. Smead Department of Aerospace Engineering Sciences.

“The goal with these grants is very much tech transfer,” Schaub said. “We’re combining university research with business goals and initiatives to develop a product or service.”

The first project is a U.S. Space Force Small Business Technology Transfer grant with In Orbit Aerospace Inc. The goal is to use electro adhesive forces to ease docking between satellites, future space cargo vehicles, or orbital debris. Electro adhesion uses short-range strong electric fields to hold together adjacent bodies, even if they are not made of magnetic materials.

“Docking in space is surprisingly difficult. If servicer bumps target vehicle in an unexpected manner, it’s going to bounce off and fly away. Electro adhesion has been used a lot already with manufacturing on Earth. With electric fields, you can create attractive forces to grab stuff. They’re not huge forces, but they’re nice,” Schaub said.

The team completed early work on the project last year and has now advanced to a second stage, which began in May.

Schaub’s portion of the grant is worth about $500,000 over 18 months, and includes numerical modeling and atmospheric experiments as well as the creation of samples to test in the lab’s vacuum chamber that approximates orbital conditions.

It is not the only business development grant in Schaub’s lab. He and Associate Professor Nisar Ahmed are also in the process of setting up a contract with Trusted Space, Inc. on a U.S. Air Force STTR grant to advance autonomous satellite fault identification. ��ý�Ļ��Ʒ’s portion of this project is worth roughly $300,000 over 18 months.

Like all electronics and machines, satellites sometimes fail. The goal of the effort with Trusted Space is to develop an AI that can automatically identify likely sources of errors.

“If a satellite isn’t tracking in orbit, maybe something bumped into it, maybe the rate gyroscope is off, maybe everything is fine but a sensor is giving bad information. There might be 10 different reasons why and we’re trying to down select in an automated way so a human doesn’t have to scour through datasets manually,” Schaub said.

The team has completed proof of concept work on a Phase 1 grant and is now advancing to Phase 2, modeling dozens of potential errors.

Both grants make extensive use of Basilisk, a piece of software developed by Schaub’s lab to conduct spacecraft mission simulations.

Although many of Schaub’s grants are directly with government agencies or multi-university initiatives, he said conducting work with a business partner offers unique opportunities for advancing science and additional potential for students.

“Students get exposure to industry and are excited because suddenly people outside the research community are interested in what they’re doing,” Schaub said. “They attend meetings and see how projects are run, what challenges industry is trying to solve. It helps influence their dissertations and gives more focus. I see a lot of benefits and companies also often want to hire the students.”

Docking with a satellite orbiting Earth is delicate business, with one wrong move spelling disaster. A team of industry and University of Colorado Boulder researchers is trying to make it easier. The work is part of two major business-university grant partnerships that...

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Ahmed discusses artificial intelligence systems with Aerospace America

Anonymous — Tue, 02 Jan 2024 21:06:28 +0000

Ahmed discusses artificial intelligence systems with Aerospace America Anonymous (not verified) Tue, 01/02/2024 - 14:06

Nisar Ahmed was interviewed for a new feature in Aerospace America magazine.

A publication of the American Institute of Aeronautics and Astronautics (AIAA), the Q&A article discusses challenges and opportunities in artificial intelligence and machine learning for aerospace systems.

Ahmed is an associate professor of aerospace and Smead Faculty Fellow at ��ý�Ļ��Ʒ and an expert in collaborative human and autonomous robot vehicle systems. He is also the ��ý�Ļ��Ʒ director for the Center for Autonomous Air Mobility and Sensing, a multi-university National Science Foundation Initiative.

In the article, he outlined difficulties faced by researchers as they seek to design AI systems that can understand situations that come easily to human operators.

"When we talk about autonomy, we mean the ability to make your own decisions, usually under uncertainty or without complete information, and being able to intelligently respond to the circumstances and situations around you. The problem is that these meanings are very fuzzy and flexible to us as people, and we know what we mean when we say that, but when you tell the computer, you have to tell it exactly what to do in those situations," Ahmed said.

Read the full piece at Aerospace America...

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Video: Autonomous Systems and the Cooperative Human-Robot Intelligence Lab

Anonymous — Tue, 18 May 2021 20:43:44 +0000

Video: Autonomous Systems and the Cooperative Human-Robot Intelligence Lab Anonymous (not verified) Tue, 05/18/2021 - 14:43

Nisar Ahmed is developing collaborative human and autonomous robot vehicle systems and machine learning and artificial intelligence for aerospace applications. An assistant professor in Ann and H.J. Smead Aerospace Engineering Sciences at ��ý�Ļ��Ʒ, Ahmed's work is advancing how people and robots interact and work with eachother.

[video:https://www.youtube.com/watch?v=DWPXNs_2k8Y]

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Seminar: Cooperative Bayesian Intelligence for Aerospace Autonomy - Sept. 18

Anonymous — Fri, 11 Sep 2020 19:49:48 +0000

Seminar: Cooperative Bayesian Intelligence for Aerospace Autonomy - Sept. 18 Anonymous (not verified) Fri, 09/11/2020 - 13:49

Nisar Ahmed
Assistant Professor, Smead Aerospace
Friday, Sep. 18 | 12:30 P.M. | Zoom Webinar - Registration Required

Abstract: As imperfectly designed agents in an uncertain world, autonomous systems will never work “out of the box” exactly as desired. By taking on tasks that push the technological limit, autonomous systems will encounter unexpected situations that go beyond their immediate capabilities. Autonomous systems must therefore be able to continuously and independently gather, process, and act on imperfect information. They must also be cognizant of what they can and cannot accomplish on their own and know when/how to seek help. In aerospace applications and beyond, scalable human-machine and machine-machine interactions will be essential for reinforcing the core perception, planning, learning, and reasoning algorithms that make machine autonomy on any one platform possible.

This talk will discuss innovative Bayesian algorithmic approaches developed by the COHRINT Lab at ��ý�Ļ��Ʒ that enable autonomous systems to opportunistically leverage different available kinds of human-machine and machine-machine interaction while performing challenging tasks in the presence of complex uncertainties. I will focus in detail on our group’s work on probabilistic modeling, inference, and optimization techniques for augmenting autonomous state estimation and decision-making algorithms running onboard autonomous systems with inputs from human teammates, task assistants and supervisors. I will describe how our approaches connect rigorous statistical modeling and learning techniques with “plug-and-play” semantic interfaces that can readily adapt to a variety of applications and users. Results from aerospace applications such as unmanned air/ground reconnaissance, missile defense, and space robotics will show how our methods allow human-machine systems to “cut knots and fill in gaps” in fundamentally novel ways for challenging problems.

Time permitting, two other related areas of fundamental work being spearheaded by the COHRINT Lab will also be briefly highlighted: algorithmic competency self-assessment for managing human trust in autonomy; and decentralized data fusion (DDF) for large-scale cooperative vehicle tracking and navigation in challenging environments.

Bio: Nisar Ahmed is an Assistant Professor in the Smead Aerospace Engineering Sciences Department at the University of Colorado Boulder, and holds a courtesy appointment in the Computer Science Department. He is a member of the Research and Engineering Center for Unmanned Vehicles (RECUV) and directs the Cooperative Human-Robot Intelligence (COHRINT) Lab.

His research interests are in modeling, estimation and control of intelligent autonomous systems, especially for problems involving human-robot interaction, distributed sensor and information fusion, and decision-making under uncertainty. He received his B.S. in Engineering from Cooper Union in 2006, and Ph.D. in Mechanical Engineering from Cornell University in 2012 through an NSF Graduate Research Fellowship. He was a postdoctoral research associate in the Cornell Autonomous Systems Lab from 2012 to 2014.

He was awarded the 2011 AIAA Guidance, Navigation, and Control Conference Best Paper Award; and an ASEE Air Force Summer Faculty Fellowship in 2014; and the 2018 Aerospace Control and Guidance Systems Committee (ACGSC) Dave Ward Memorial Lecture Award. His work has been supported by the Army, Air Force, DARPA, Navy, NASA, and multiple industry sponsors, and he has also organized several international workshops and symposia on autonomous robotics, sensor fusion, and human-autonomy interaction. He is a Member of the IEEE and the AIAA Intelligent Systems Technical Committee, and he is the CU Co-Site Director of the NSF IUCRC Center for Unmanned Aerial Systems (C-UAS).

As imperfectly designed agents in an uncertain world, autonomous systems will never work “out of the box” exactly as desired. By taking on tasks that push the technological limit, autonomous systems will encounter unexpected situations that go beyond their immediate capabilities. Autonomous systems must therefore be...

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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

University of Colorado Boulder 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 University of Colorado Boulder.

Ahmed is serving as principal investigator at ��ý�Ļ��Ʒ 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 ��ý�Ļ��Ʒ 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.”

University of Colorado Boulder 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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In push to deep space, human-robot teaming will be key

Anonymous — Fri, 30 Aug 2019 16:44:28 +0000

In push to deep space, human-robot teaming will be key Anonymous (not verified) Fri, 08/30/2019 - 10:44

NASA’s robotic space exploration missions are highly choreographed and rehearsed. Built around duplicate systems and repeated simulations, no detail is left unplanned for. The idea is to lower the risk to highly valuable and Irreplaceable equipment thousands of miles from physical support.

But if humans are going to travel further into space – to places like Mars and beyond – the robotic systems involved will have to become more autonomous, shedding costly teams of handlers on Earth and relying more on the astronauts for missions lasting six or more years. This dynamic, known as human-machine teaming, is a growing area of interest for aerospace researchers in the college and around the world.

Steve McGuire recently received his PhD from the Smead Department of Aerospace Engineering Sciences on this topic through a NASA Space Technology Research Fellowship. His work was done in conjunction with Michael Furlong and the NASA Ames Intelligent Robotics Group.

McGuire’s thesis, titled “Autonomous Online Learning of Assistant Selection Policies for Fault Recovery,” explores how machine learning can enable space robots to best ask human crew members for assistance when recovering from failures.

Essentially, what does an automated system do when things break in ways humans can help with? What happens with “soft failures,” like when a robot can’t pick up a rock specimen on its own?

“Think of the self-checkout at grocery store when an unexpected item hits the bagging area. It throws its hands up and says it needs a human,” McGuire said. “That is how we run fault recovery with robots. We just want someone who can get that system back in action. My thesis asks: ‘how do we do that more intelligently?’ Not all humans are equally positioned to work on that kind of task, so how do we decide which one would be the right person to solve an issue encountered in deep space exploration?”

That decision would be made based on factors like the physical state of the astronauts as well as past experiences about how to get the best outcome. Adaptive decision-making is key because with longer and larger missions, the plans made in preparation for the launch and the people involved will all be different by the time you actually launch and as you travel. That includes physical changes that may happen along the way to the astronauts, as well as increased familiarity and experience those humans will get with the system itself.

McGuire’s adviser, aerospace Assistant Professor Nisar Ahmed, elaborated on this: “You don’t know what you don’t know in a mission until you get there”

There are some things you could not simulate with autonomous space robots on Earth, even if you wanted to, because of the gravity well, for example. By its very definition, space exploration means that human-robot teams will run into the uncertain, unexpected and unknown.

“That is why we have autonomy, because it takes the decision-making burden off the human. But understanding how and why those decisions are made is just as important, and that modeling side is a big part of this work,” Ahmed said. “There is a chain-of-reasoning aspect to this that goes along with the astronaut’s trust in the system.”

One of the biggest benefits of better teaming is reduced costs in system duplication and human oversight, McGuire said.

“Right now, there is a dedicated team of about 30 engineers that are monitoring the single Mars Science Laboratory rover Curiosity Rover on Mars. That ratio just isn’t sustainable when you start to scale up to more rovers,” he said. “As we expand and have greater presence in universe, need to get that ratio down to single digits – one human to one robot. Ideally, even to one human for five or more robots. Considering that an hour of an astronaut’s time runs about $50,000, small reductions of work through better teaming – even in the five-minute range during the mission – can add up to large savings and better efficiency.”

Now that his thesis defense is complete, McGuire is serving as a postdoctoral researcher on the ��ý�Ļ��Ʒ team competing in the DARPA Subterranean Challenge. His goal is to obtain a faculty position in space robotics.

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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

��ý�Ļ��Ʒ 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 University of Colorado Boulder 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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��ý�Ļ��Ʒ partner adds unclassified development space to Remote Sensing Data Lab

Anonymous — Fri, 25 Aug 2017 21:02:03 +0000

��ý�Ļ��Ʒ partner adds unclassified development space to Remote Sensing Data Lab Anonymous (not verified) Fri, 08/25/2017 - 15:02

The Space and Missile Systems Center’s Remote Sensing Systems Directorate (RS) held a ribbon-cutting ceremony today to unveil the addition of an unclassified development environment to the existing Tools, Applications, and Processing (TAP) Lab. This open environment will allow more third-party developers to create capabilities using unclassified remote sensing data without the time and cost of acquiring government security clearances. These new capabilities will have the potential to transition from development to operations rapidly in support of both military and civil applications.

The TAP Lab opened in April of 2016 and offers academia, industry, and other government agencies access to remote sensing infrared and weather data in a research and development environment. It promotes applied research and agile development of algorithm improvements, data storage and dissemination, user experience, and data fusion. However, the lab was only available to users with a Secret level security clearance until now.

“When we created the TAP Lab we invited developers without prior missile warning experience to use their own development tools in the lab’s open frame work to build new and innovative applications,” said Col Kerri Mellor, Chief of the RS Future Ground and Exploitation Capabilities Division. “We’ve had a fantastic turn out, but it was limited to those with security clearances. This new unclassified development environment opens up these opportunities to a much broader third-party developer base, and the Air Force will benefit from having the best minds work on these projects with much easier access to data.”

Prototype applications have the potential for test and evaluation by end users. Capabilities receiving positive assessment will be considered for transition, via appropriate acquisition programs, into operational applications in the Space Based Infrared Systems Mission Control Station and Overhead Persistent Infrared Battlespace Awareness Center at Buckley Air Force Base, Colorado. To date, 151 white papers have been received resulting in 18 proposal requests by RS.

The Lab is managed by the Remote Sensing Systems Directorate at the U.S. Air Force Space and Missile Systems Center, El Segundo, California. The Unclassified development space was created in conjunction with the University of Colorado-Boulder, Lockheed Martin Space Systems Company, Sunnyvale, California, and Colorado-based small businesses Net-Centric Design Professionals (NDP) and Cosmic AES. Register at boulderlab.org for all events, solicitation notification, or to sign up for a tour.

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Nisar Ahmed News

Designing autonomous robots for use on Mars and closer to home

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����������ý�Ļ���Ʒ, industry partner on space docking and satellite AI research

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Ahmed discusses artificial intelligence systems with Aerospace America

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Video: Autonomous Systems and the Cooperative Human-Robot Intelligence Lab

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Seminar: Cooperative Bayesian Intelligence for Aerospace Autonomy - Sept. 18

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Solving AI’s (over)confidence problem

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In push to deep space, human-robot teaming will be key

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CU is diving into the field of autonomous submarines

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����������ý�Ļ���Ʒ partner adds unclassified development space to Remote Sensing Data Lab

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��ý�Ļ��Ʒ, industry partner on space docking and satellite AI research

��ý�Ļ��Ʒ partner adds unclassified development space to Remote Sensing Data Lab