On April 5 in Chicago, The 2017 Engelberger Robotics Award will be presented to Dr. Gill Pratt, chief executive officer of the Toyota Research Institute (TRI), and Dr. Daniela Rus, professor of electrical engineering and computer science and director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT). The award dinner, held in conjunction with the Automate 2017 Exhibition and Conference and the International Symposium on Robotics, will be held at the Adler Planetarium.
Rus’ research group, the Distributed Robotics Lab, has developed modular and self-reconfiguring robots, systems of self-organizing robots, networks of robots and sensors for first-responders, mobile sensor networks, techniques for cooperative underwater robotics and new technology for desktop robotics. Companies such as iRobot and Boeing have commercialized tech drawn from Dr. Rus’ research and she is the first woman to serve as director of CSAIL.
We spoke to Rus prior to the Engelberger Robotics Award event, discussing various topics ranging from how she got her start in the field to the biggest misconceptions she sees about her work.
Control Design: What does the Engelberger Award symbolize to you, in terms of achievement or recognition?
Dr. Daniela Rus: It is an extraordinary honor to be recognized at such a high magnitude. It’s also humbling to receive this recognition right now when robotics is such a hot topic and the world has such great hopes for robotics. I cherish the award as a symbol of hope and optimism for my work and for a future with robots pervasively integrated into the fabric of life.
CD: What got you interested in the field of robotics? Was it early on or something you developed through your studies/career?
Rus: I’ve loved robots all my life. I grew up watching Lost in Space and the like but I hadn’t thought about making and studying robots until I was an undergraduate student. At the time, I listened to a talk that John Hopcroft gave about the future of computing. In that talk John said that a lot of the classical graph algorithm problems in computing were solved. And it was time for the grand applications. Robotics was such an exciting grand application. That talk really captured my imagination. I was given the great opportunity to work on robots with John and I eagerly went for it!
CD: What recent robotics projects are you most proud of and why?
Rus: It’s not possible to pick because every project has its own special knowledge nugget it brings to the world. Each project I worked on was joyful because of the wonderful students with whom I was privileged to work. Altogether, our contributions are to the science of autonomy—especially in the context of multiple robots working together and with people. I am also working towards a future of pervasive robots. Everything we do is a piece of the puzzle towards the future of pervasive future and the science of autonomy. Every one of our results that advances the science of autonomy gives us pride.
CD: What do you think machine builders can do to get others – particularly the next generation of—interested and invested in robotics?
Rus: We have to embrace the idea that computing is part of digital literacy at this point in time. I would like to see mandatory computing and making curriculum for K-12 education. The kids who know how to make things and how to control the things they make by programming have a certain kind of super power. They are able to imagine anything and make it happen.
CD: What do you think is the biggest misconception about robotics?
Rus: It’s that the robots are going to take over. Robots are tools. They are incredibly powerful tools that are not inherently good or bad, they are what we choose to do with them. And I believe we can do some incredible things for many different industries and many people. One day I hope the technology will be developed to the point where everybody could benefit from it. The capabilities of robots are rooted in our current understanding of the science of autonomy and the science of intelligence. But robots have limitations. We have to understand the limitations and what the tool is good for. For example, today we do not have the technology necessary to deliver level 5 self-driving vehicles, but we have technology to deliver autonomous driving at low speeds, in closed and simple (uncrowded) environments, if the weather is good. We continue to develop the technology needed for autonomous vehicles for more general situations – for example driving in snow or in intense congestion are unsolved today but at some point in the future I believe we will have a solution.
CD: Industry is using robots in collaborative applications on the factory floor. What are some future uses of robots in the home beyond the robo-vacuum?
Rus: We have a really effective use of machines in manufacturing, medicine, and transportation. I’m very optimistic about the possibility of using robots to provide safe mobility on demand to many people—especially for those who are not able to drive.
While we don’t have products yet, I believe we will see the products before too long. Our CSAIL research team together with the team at Toyota Research Institute led by Dr. Pratt, (who is the co-winner of the Engelberger award this year), are developing the technology for parallel autonomy in support of safe driving. The idea is to have an in-car system we call the guardian angel that will watch what the driver wants to do and what the road looks like and prevent the drive from making unsafe maneuvers. If the human wants to do something that is unsafe, the car will make the correction just like an ABS system is able to make a correction today. The parallel autonomy system will have broad knowledge and situation awareness about the road and help the driver to ensure general safe driving, for example, safe speeds on mountain switchbacks and safe overtaking maneuvers.
CD: What is the next big thing in robotics?
Rus: I’m excited about the pervasive integration of robots into the fabric of everyday life where robots become common, useful, and usable by many people. We’re not there. We have to improve the agility and dexterity of robots and their abilities to figure things out. We need to speed up how we make robots by developing tools for automated design and fabrication. And we need to make the human-robot interaction much more intuitive. These are the challenges I’m excited about right now. I have projects in each of these different areas.