Category Archives: Computer Science

How many robots does it take to screw in a light bulb?

As technology continues to improve over the coming years, we are beginning to see increased integration of robotics into our daily lives. Imagine if these robots were capable of receiving general instructions regarding a task, and they were able to learn, work, and communicate as a team to complete that task with no additional guidance. Our guest this week on Inspiration Dissemination, Connor Yates a Robotics PhD student in the College of Engineering, studies artificial intelligence and machine learning and wants to make the above hypothetical scenario a reality. Connor and other members of the Autonomous Agents and Distributed Intelligence Laboratory are keenly interested in distributed reinforcement learning, optimization, and control in large complex robotics systems. Applications of this include multi-robot coordination, mobile robot navigation, transportation systems, and intelligent energy management.

Connor Yates.

A long time Beaver and native Oregonian, Connor grew up on the eastern side of the state. His father was a botanist, which naturally translated to a lot of time spent in the woods during his childhood. This, however, did not deter his aspirations of becoming a mechanical engineer building rockets for NASA. Fast forward to his first term of undergraduate here at Oregon State University—while taking his first mechanical engineering course, he realized rocket science wasn’t the academic field he wanted to pursue. After taking numerous different courses, one piqued his interest, computer science. He then went on to flourish in the computer science program eventually meeting his current Ph.D. advisor, Dr. Kagan Tumer. Connor worked with Dr. Tumer for two of his undergraduate years, and completed his undergraduate honors thesis investigating the improvement to gauge the intent of multiple robots working together in one system.

Connor taking in a view at Glacier National Park 2017.

Currently, Connor is working on improving the ability for machines to learn by implementing a reward system; think of a “good robot” and “bad robot” system. Using computer simulations, a robot can be assigned a general task. Robots usually begin learning a task with many failed attempts, but through the reward system, good behaviors can be enforced and behaviors that do not relate to the assigned task can be discouraged. Over thousands of trials, the robot eventually learns what to do and completes the task. Simple, right? However, this becomes incredibly more complex when a team of robots are assigned to learn a task. Connor focuses on rewarding not just successful completion an assigned task, but also progress toward completing the task. For example, say you have a table that requires six robots to move. When two robots attempt the task and fail, rather than just view it as a failed task, robots are capable of learning that two robots are not enough and recruit more robots until successful completion of the task. This is seen as a step wise progression toward success rather than an all or nothing type situation. It is Connor’s hope that one day in the future a robot team could not only complete a task but also report reasons why a decision was made to complete an assigned task.

In Connor’s free time he enjoys getting involved in the many PAC courses that are offered here at Oregon State University, getting outside, and trying to teach his household robot how to bring him a beer from the fridge.

Tune in to 88.7 FM at 7:00 PM Sunday evening to hear more about Connor and his research on artificial intelligence, or stream the program live.

Rise of the Robots

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Image from: http://www.stuff.co.nz/technology/2403589/Artificial-intelligence-the-future-of-robots

Tonight at 7pm Aswin Raghavan will join us on Inspiration Dissemination. Tune in at 88.7 KBVR Corvallis or stream live here to learn about his project preparing for the robotic revolution (imagine household robots and self-driving cars)! Aswin isn’t worried about these machines coming to conquer humanity, in fact he’s hoping that increased use of Artificial Intelligence can make many aspects of human society more efficient.

As a fifth year PhD student  in computer science working under Dr. Tadepalli, Aswin doesn’t build robots or focus much on what the specific application of his A.I. will be- he works on ‘automated planning’. This means that Aswin develops algorithms used by computers in decision making processes. Computers running these decision making programs can more efficiently manage many human affairs, everything from coordinating traffic lights in your home town to running a loading dock full of multiple automated cranes.

From helping your local fire station more efficiently dispatch vehicle to “smart cities” that manage the provision of utilities to millions, artificial intelligence is on the rise! Join us tonight to find out how!

Giving the Cold Soul of a Machine a Burning Desire to Teach Your Children Well:

Tonight at 7 pm Pacific time on 88.7 KBVR Corvallis, Beatrice Moissinac comes into the studio at Inspiration Dissemination to talk about Artificial Intelligence and fire safety training. If you’re curious how those two subjects are related, tune in live or stream the episode here!

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Illustration: Christine Daniloff/MIT, http://newsoffice.mit.edu/2013/center-for-brains-minds-and-machines-0909

A PhD student in Oregon State’s Computer Science program, Beatrice works underneath Prasad Tadepalli and collaborates with Enterprise Risk Services to design computer programs which guide students through a virtual fire safety training experience.

What kind of virtual training? As it turns out, Oregon State has an entire virtual campus dedicated to it in the online game Second Life (a virtual world that may or may not use more energy than some South American countries). Using one of the dorms in the second life version of OSU, Beatrice designs a training program that responds to individual students’ needs. Students are then immersed in a fully interactive virtual world where they learn what to do in the event that their dorm were to catch fire.

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http://www.zdnet.com/article/indoor-navigation-tracks-firefighters-in-blazing-buildings/

By analyzing what knowledge has not been learned, and by determining the best way to challenge the student, the artificial intelligence program is intended to provide a perfectly matched learning environment. This is crucial for training in something like fire safety, or other natural disasters, since training scenarios in real life could not be safely (or economically) constructed.

Beatrice is also the co-program manager for ChickTech Corvallis, a local chapter of the national non-profit group that organizes science and technology outreach and communications projects for high school girls. As a woman in computer science, a program that (at OSU) is still less than 10% female, Beatrice understands that the gender gap in science and technology studies is still very real in the United States. With here interests in both teaching and computer science combined, Beatrice continues to work for the academic benefit of the next generation. If she isn’t teaching a computer to teach people, then she’s teaching them herself!