In this episode, Audrow Nash interview Magnus Egerstedt, Professor at the Georgia Institute of Technology, about a way for anyone interested in swarm robotics to test their ideas on hardware, called the Robotarium. The Robotarium is a 725-square-foot lab at the the Georgia Institute of Technology that houses nearly 100 rolling and flying robots. To test their ideas, people can write their own programs, upload them to the Robotarium, and then watch the machines carry out their commands.
In this interview, Egerstedt speaks about the kinds of robots used in the Robotarium, design decisions in making the Robotarium, the differences between doing research in simulation and on hardware, and about lessons learnt and the challenges of building the Robotarium.
Magnus Egerstedt
Dr. Magnus Egerstedt is the Steve W. Chaddick School Chair and Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He holds secondary appointments in the Woodruff School of Mechanical Engineering, the School of Interactive Computing, and the Guggenheim School of Aerospace Engineering, and has previously served as the Executive Director for the Institute for Robotics and Intelligent Machines at Georgia Tech. He received the M.S. degree in Engineering Physics and the Ph.D. degree in Applied Mathematics from the Royal Institute of Technology, Stockholm, Sweden, the B.A. degree in Philosophy from Stockholm University, and was a Postdoctoral Scholar at Harvard University. Dr. Egerstedt conducts research in the areas of control theory and robotics, with particular focus on control and coordination of complex networks, such as multi-robot systems, mobile sensor networks, and cyber-physical systems. Magnus Egerstedt is a Fellow of the IEEE and has received a number of teaching and research awards, including the Ragazzini Award from the American Automatic Control Council, the Outstanding Doctoral Advisor Award and the HKN Outstanding Teacher Award from Georgia Tech, the Alumni of the Year Award from the Royal Institute of Technology, and the CAREER Award from the U.S. National Science Foundation.
Links
If you follow the robotics community on the twittersphere, you’ll have noticed that Rodney Brooks is publishing a series of essays on the future of robotics and AI which has been gathering wide attention.
His articles are designed to be read as stand alone essays, and in any order. Robohub will be featuring links to the articles as they come out. They are worth the read.
Steps Toward Super Intelligence IV, Things to Work on Now published on July 15, 2018.
Steps Toward Super Intelligence III, Hard Things Today published on July 15, 2018.
Steps Toward Super Intelligence II, Beyond the Turing Test published on July 15, 2018.
Steps Toward Super Intelligence I, How We Got Here published on July 15, 2018.
Bothersome Bystanders and Self Driving Cars published July 4, 2018
The Origins of “Artificial Intelligence” published April 27, 2018
Time Traveling Refugees published March 17, 2018
The Productivity Gain: Where Is It Coming From And Where Is It Going To? published February 25, 2018
My Dated Predictions published January 1, 2018
AI/ML Is Not Uniquely Powerful Enough To Need Controlling published on December 23, 2017
What If There Were Men On The Moon Today? published December 18, 2017
The Seven Deadly Sins of Predicting the Future of AI published on September 7, 2017.
Domo Arigato Mr. Roboto published on August 28, 2017.
Machine Learning Explained published on August 28, 2017.
Will a robot take my job?
Media headlines often speculate about robots taking our jobs. We’re told robots will replace swaths of workers from taxi drivers to caregivers. While some believe this will lead to a utopian future where humans live a life of leisure provided for by robots, the dystopian view sees automation as a risk to the very fabric of society. Such hopes and fears have preceded the introduction of new technologies for centuries – the Luddites for example destroyed weaving machines in the 19th century to protest the automation of their sector. What we see, time and time again, is that technology drives productivity and wealth, which translates to more and better jobs down the line. But can we expect the same to happen with robots, or is this time different?
What do the numbers say?
Studies looking at the impact of robots on the job market have contradictory findings. A paper released by the National Bureau of Economic Research concludes that every robot introduced between 1990 and 2007 coincided with the elimination of 6.2 jobs within the commute area and a slight drop in wages. The International Federation of Robotics however found that from 2010 to 2015, the US industry installed around 135,000 new industrial robots, mainly in the car industry. During this same period, the number of employees in the automotive sector increased by 230,000, which suggests a positive impact on jobs.
Examples of this can also be seen in Amazon warehouses where the introduction of more than 100,000 warehouse robots did not lead to a dip in human labor. In fact, Amazon has added 113,500 people to its company worldwide in the past year.
Other studies have tried to estimate the number of jobs that could be automated in the future, and there again, the numbers vary widely. An Oxford report from 2013 estimated that 47% of U.S. jobs were at risk of automation. The OECD however has said that “14% of jobs in developed countries were highly automatable, with a further 32% likely to experience significant changes to the way they were carried out.”
So which is it, do robots create or destroy jobs? The answer may be “it’s complicated”. Certain professions may disappear in a local community, while the overall number of jobs may increase globally. In any case, the nature of work will most likely change.
Robots perform tasks, not jobs
Most jobs require workers to have more than one skill. Building a fully automated solution would therefore require a robot that masters many different tasks. Making robots is hard however, so they tend to be highly specialised. Imagine all the tasks a cleaner can do, yet it took Dyson 12 years of research just to make a vacuum cleaning robot. The reality is that robots perform tasks, not jobs. It therefore makes sense to think of robots as tools that can be used by people in their workplace, ideally helping with the dull, dirty, or dangerous tasks and boosting productivity. This has spurred a new area of collaborative robots, or cobots, that are easy to work with. ColRobot for example is a European project focussed on building an integrated system for collaborative robotics.
Skills for the new economy
The jobs of today are different from the ones of tomorrow. There is a pressing need to train a new generation of roboticists. This workforce will need to be diverse to ensure the best tools are being built for everyone. Inspiring the future generation is the goal of the European Robotics Week, which hosts more than 1000 events all over Europe. Training is further needed at all levels from school for young children to graduate education programs. But not everyone needs to be a roboticist, being technology literate is the first step towards building environments where humans and robots can work together. And while robots help us with the menial tasks, we have a chance to be “more human”. A carebot won’t replace a caregiver, it will give the caregiver time to have a coffee with their patient. Ultimately, we have the opportunity to focus on the jobs we enjoy most. Creative sectors, and those requiring emotional intelligence and empathy will also be in high demand in the future.
Technology that benefits all
One risk with automation is that wealth is concentrated in the hands of those that design or have access to the technology. Such a winner-takesall scenario would lead to growing inequality between large technology companies and workers. Wages have also stagnated, even though productivity has increased, which is another marker of inequality. At the same time these technologies are becoming increasingly accessible, meaning that non-experts should feel empowered to use them in their own industries and lives. The European Union and individual European governments are actively preparing for a change in labour markets with dedicated commissions and reports, as well as ground work to ensure the robot revolution benefits all. Solutions discussed include taxing automation, providing for a universal basic income, or boosting education, research, and entrepreneurship.
This article is part of a series of briefing documents published on www.eu-robotics.net/sparc. This project has received funding from the European Union’s Horizon 2020 Programme under grant agreement n° 688441
This week’s hot story was again from Amir at The Information and there is even more detail in the author’s Twitter thread.
The short summary: Amir was able to find a fair number of Waymo’s neighbours in Chandler, Arizona who are getting frustrated by the over-cautious drive patterns of the Waymo vans. Several used the words, “I hate them.”
A lot of the problems involve over-hesitation at an unprotected left turn near the Waymo HQ. The car is just not certain when it can turn. There is also additional confirmation of what I reported earlier, that operation with no safety driver is still very rare, and on limited streets.
Unprotected turns, especially left ones, have always been one of the more challenging elements of day-to-day driving. You must contend with oncoming traffic and pedestrians who may be crossing as well. You may have to do this against traffic that is moving at high speed.
While I am generally not surprised that these intersections can be a problem, I am a little surprised they are one for Waymo. Waymo is the only operating car which features a steerable, high resolution long range LIDAR on board. This means it can see out 200m or more (in a narrower field of view.) This lets it get a good look at traffic coming at it in such situations. (Radar also sees such vehicles but with much less resolution.)
For Waymo, this is not a problem of sensors but one of being too timid. One reason they are operating in Phoenix is it’s a pretty easy area to be timid in. The instinct of all teams is to avoid early risks that lead to early accidents. That became even stronger in Arizona after the Uber fatality, which used up a lot of the public’s tolerance for such errors. As such, the “better safe than sorry” philosophy which was already present in Waymo and most teams has been strengthened.
The problem is, it needs to eventually be weakened. Timid drivers won’t make it in the real world. They won’t make it far at all in the non-tame places like Boston. Thus you look at a nasty trade-off:
That leaves only a few options. The other drivers must adapt better to a timid driver, or the public must get more tolerant of a slightly higher (but still better than human) accident risk.
Hype around self-driving cars has pushed some into the public to expect computerized perfection. That’s not coming.
Believe it or not, it is not as impossible to change the behaviour of other drivers as you might think. In Manhattan not that may years ago, two things were very common. Endless honking, and gridlock. Both were the result of well ingrained aggressive habits of New York drivers. The city decided to crack down on both, and got aggressive with fines. It worked, and those things are both vastly reduced.
It’s less possible to adjust the patterns of pedestrians. Some recent articles have gotten a lot of attention from people suggesting this must happen. I think some of it will happen, but much less than hoped, and that will be the subject of another article.
A robocar should eventually get very good at driving decisions which involve physics, because computers are very good at physics. Unlike humans which have difficulty precisely timing when an oncoming car will get to them, robots could in theory do it with a very frightening precision, making turns through gaps that seem tiny to humans. This would frighten other drivers and cause problems, so it’s not something we’ll see today.
This isn’t the last story we’ll see of robocars frustrating other drivers. That’s particularly true if we unwisely keep them at the speed limit. My long term belief is that most of the traffic code should be eliminate for robocars and be replaced by, “it’s legal if you can do it safely and without unfairly impeding traffic.” The whole idea of a traffic code only makes sense for humans. With robots, since there will never be more than a few dozen different software stacks on the road, you can just get all the designers together in a room and work out what should be done and what is safe. Traffic codes and other laws are there to deal with humans who can’t be trusted to know the rules or even obey the rules they know. While companies can’t be trusted to do anything but look after their own interests, you can easily make it in their interests to follow the rules.