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Monthly Archives: December 2014

Robotics – here’s to the crazy ones

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In the early 1970s the UK Government commissioned a special report Artificial Intelligence: A General Survey authored by James Lighthill on behalf of the Science & Engineering Research Council (the infamous Lighthill Report) which damned A.I. and was “highly critical” of basic research in foundational areas such as robotics. The report recommendations led to the withdrawal of research funding from all but three UK universities. The same kind of official doubts which the Lighthill Report made explicit in the UK lay behind a less extreme slow down in research funding in the US. This is sometimes referred to generically as the “first A.I. winter.”

This was changed, some ten years later, in the late 1980’s under, the then, Prime Minister Margaret Thatcher after the publication of The Alvey Report; Britain’s strategic computing initiative, recommended putting a lot of money into A.I. research, which they renamed Knowledge Based Systems. Robotics, closely associated with A.I., was also a recipient of the new flow of government support, which was meant to help improve Britain’s lagging fortunes against the growing success of the Japanese economy. Folklore tells us that despite her agreement to proceed with the funding Mrs. Thatcher still considered the scientists and engineers, or the “Artificial intelligentsia,” to be seriously deranged.

However the investment flows were not significant on a global scale. As a result in the second decade of the 21st century, despite the promises of a robot revolution, there are still less than approximately 1.3 million industrial robots in active service worldwide, and, whilst we are seeing some progress in ‘soft’ A.I., most notably products such as Google Now and Siri along with IBM’s Watson, Peter Thiel, known for investing in several A.I. companies, such as UK based DeepMind (sold to Google for circa US$ 500 million) and Vicarious wrote in his Founder’s Fund manifesto:

While we have the computational power to support many versions of A.I., the field remains relatively poorly funded, a surprising result given that the development of powerful A.I.s (even if they aren’t general A.I.s) would probably be one of the most important and lucrative technological advances in history.

Things do however appear to have changed. Investments in robotics and A.I. seem to be surging once again, the US National Science Foundation has invested at least US$ 89 million in robotics labs in the last few years and earlier this year the European Commission formally announced the world’s largest investment into Robotics. Other countries and businesses are also investing heavily into the sector.

On the 9th December I attended the robotics Brokerage Day held by euRobotics in Brussels, Belgium. The Brokerage day was essentially an education and networking day aimed at assisting Robotic research labs and industry partner up to apply for grants under one of the EU’s grant calls (ICT 2015), where a total grant budget of 561 million Euros is available. Around 300 participants from 30 countries attended the event with over 50 teaser presentations given.

Health care

The area of health care robotics, including robots to help the elderly and disabled was particularly prominent.

Research Professor Dr. Sven Behnke of the University of Bonn discussed his labs work on ‘Cognitive robots,’ which he believes represents the “next step in the fusion of machines, computing, sensing, and software to create intelligent systems capable of interacting with the complexities of the real world.” This included smart mobile manipulation of every day care duties, such as cleaning the floor or handling a bottle.

Several research labs and companies such as Antonio Frisoli of Wearable Robotics from Italy and Volkan Patoglu, of Sabanci University, İstanbul, Turkey discussed work on exoskeleton’s to provide people with the ability to be mobile after losing a limb or other disability.

Enrico Castelli of the Children’s Hospital in Rome presented their pioneering work on exoskeleton’s for children with neurological disorders.

Elvan Gunduz spoke of SciRobots approach to building care robots to help people with dementia, helping sufferers live a ‘good life.’

Hazardous environments

Other researchers outlined their work on providing robots to work in hazardous environments, think fire fighting, underground mining or nuclear disasters.

Cloud robotics

It was very clear that labs and industry shared a common goal that: “No robot is an island.” Believing that advances in artificial intelligence and robot software can be greatly enhanced by the ability of researchers and robots to access a local network to improve self-driving cars, logistics and factory planning.

Child like curiosity, not deranged 

Mrs. Thatcher may have been impressed with the advances on display although the child-like curiosity by so many adult robot enthusiasts, me included, may not have changed her mind about how crazy one needs to be to believe you can change the world with robotics – she may not have been familiar with Steve Jobs toast to the crazy ones, who see things differently and make a difference in the world through their visions and creations.

What was clear in this child like derangement, roboticists genuinely believe they are building some of the most important tools of the 21st century – I agree.

Photo credit: Dr. Sven Behnke of the University of Bonn 

Why Your Employees Should Be Playing With Lego Robots

Two years ago, Swedish communications technology giant Ericsson found itself looking for a way to explain the value it saw in the Internet of Things. Rather than publish another whitepaper on the topic, the company struck on a different communication tool: Legos. More specifically, Lego robots.

Ericsson used Lego Mindstorm robots in a demonstration at the 2012 Mobile World Congress to bring to life its vision of how connected machines might change the way we live. A laundry-robot sorted socks by color and placed them in different baskets while it chatted with the washing machine. A gardening-robot watered the plants when the plants said they were thirsty. A cleaner-robot collapsed and trashed empty cardboard coffee cups that it collected from the table, and a dog-like robot fetched the newspaper when the alarm clock rang.

Social Networking for LEGO Mindstorms Robots

Rather than merely talking or writing about its vision, Ericsson saw robots as a perfect medium for explaining its ideas. This is more than just a smart marketing campaign. As a variety of researchers have argued, it may offer a way to better equip workers with the skills they need to succeed in the 21st century. Training programs that encourage the use of robots to achieve goals – not just by playing with them, but by building them — encourage participants to use their creativity and natural curiosity to overcome problems through hands-on experiences.

Lego’s Mindstorm robots (or education and innovation kits as they are sometimes known) were developed in collaboration with MIT Media Lab as a solution for education and training in the mid to late 90’s. The work was an outcome of research by Professor Seymour Papert, who was co-founder of the MIT Artificial Intelligence Lab with Marvin Minsky. Papert later co-founded the Epistemology and Learning Group within the MIT Media Lab. Papert’s work has had a major impact on how people develop knowledge, and is especially relevant for building twenty-first century skills.

Papert and his collaborators’ research indicates that training programs using robotics influences participants’ ability to learn numerous essential skills, especially creativity, critical thinking, and learning to learn or “metacognition”. They also emphasize important approaches to modern work, like collaboration and communication.

This form of learning is called constructionism, and it is premised on the idea that people learn by actively constructing new knowledge, not by having information “poured” into their heads. Moreover, constructionism asserts that people learn with particular effectiveness when they are engaged in “constructing” personally meaningful artifacts. People don’t get ideas; theymake them.

Papert’s influential book Mindstorms: Children, Computers and Powerful Ideas as well as extensive scientific research into fields such as cognition, psychology, evolutionary psychology, and epistemology illustrate how this pedagogy can be combined with robotics to yield a powerful, hands-on method of training.

In training courses that use robotics, the program leader sets problems to be solved. Teams are presented with a box of pieces and simple programs that can run on iPads, iPhones, or Android tablets and phones. They are given basic training in the simple programming skills required and then set free to solve the problem presented.

Problems can be as ‘simple’ as building a robot to pass through a maze in a certain time frame, which requires trial and error and lots of critical thinking. What size wheels to use for speed and maneuverability, what drain on battery power, which sensors to use for guidance around walls. One team may decide to build a small drone to view and map out the terrain of the maze, this would require theorizing on the weight of the robotic drone and relaying data filmed to a mapping system which the on-ground robot could use to negotiate through the maze.

It is an entirely goal-driven process.

Participants get to design, program, and fully control functional robotic models. They use software to plan, test, and modify sequences of instructions for a variety of robotic behaviors. And they learn to collect and analyze data from sensors, using data logging functionalities embedded in the software. They gain the confidence to author algorithms, which taps critical thinking skills, and to creatively configure the robot to pursue goals.

Participants from all backgrounds gain key team building skills through collaborating closely at every stage of ideation, innovation, deployment, evaluation and scaling. At the end of the training teams are required to present their ideas and results, building effective communication skills.

It is quite astonishing to see how teams have developed robots to achieve tasks such as solving Rubik’s cubes in seconds, playing Sudoku and drawing portraits, creating braille printers, taking part in soccer and basketball games. These robots have even been used for improving ATM security.

Using robots in training programs to overcome challenges pushes participants out of their comfort zone. It deepens their awareness of complexity and builds ownership and responsibility.

The array of skills and work techniques that this kind of training offers is more in need today than ever, as technology is rapidly changing the skills demanded in the workplace.

Instead of programming people to act like robots, why not teach them to become programmers, creative thinkers, architects, and engineers? For companies seeking to develop these skills in their employees, hands-on goal-focused training using robots can help.

This post initially appeared on Harvard Business Review

Is package delivery using drones feasible?

Amazon Prime Air Drone

Co-founder of Kiva Systems Robotics indicates drone delivery could be as low as 20 cents per package.*

*Updated Friday 5th December after email correspondence with Professor D’Andrea

In the early summer I wrote about the economics of Amazon’s drones, the post highlighted the cost of logistics to Amazon and some back of the envelope calculations about the likely costs of drone delivery. In the article I indicated that Amazon would require pilot’s for their drones, especially in the early years of operation, it seems far fetched that we will have fully autonomous delivery drones in our cities without some sort of human oversight, at least in the next ten years or so. Backing up my calculations a recent job advert by Amazon indicates that they are looking for drone pilots, whilst similar jobs attract annual salaries of approximately $100,000 per year.

Earlier this year Helen Greiner CEO of CyPhy Works outlined her vision of delivery drones in 5 years. Meanwhile DHL have started testing the use of delivery drones to transport medicine to a small the North Sea island of Juist.

So is it economically feasible to deliver packages by drones?

Professor of robotics and autonomous vehicles Raffaelo D’Andrea of ETH Zurich, who is responsible for the Flying Machine Arena (“a space where flying robots live and learn”), and co-founder of Kiva Systems (robotics company acquired by Amazon, Inc. for US$ 775 million in cash), thinks it is economically feasible to deliver small packages by drone.

In a guest editorial for IEEE Automation Science and Engineering (Pdf), Professor D’Andrea detailed some calculations he had previously used to assess the costs of drone delivery for Matternet whose ‘vision was to create a transportation network based on flying machines, and to initially address niche markets such as medicine delivery in underdeveloped and hard to reach areas,’ and also compared to those that they had previously used for Kiva systems “business plan for the total cost of delivery.”

To assess the costs Raff initially uses two assumptions:

  • Payload of up to 2 kg.
  • Range of 10 km with headwinds of up to 30 km/h.

In his calculations, to arrive at the likely costs of drone delivery, D’Andrea analyzes the power consumption in kW, payload mass of 2 kg; a vehicle mass of 4 kg (battery weight of 2kg); the lift-to-drag ratio; 
power transfer efficiency for motor and propeller; power consumption of electronics, in kW, electricity costs and cruising velocity, in km/h, air speed and headwinds.

After analyzing the weight of the drone, payload (parcel) drag, headwinds, etc. Professor D’Andrea states:

“So, is package delivery using flying machines feasible? From a cost perspective, the numbers do not look unreasonable: the operating costs directly associated with the vehicle are on the order of 10 cents for a 2 kg payload and a 10 km range. I compare this to the 60 cents per item that we used over a decade ago in our Kiva business plan for the total cost of delivery, and it does not seem outlandish.”

Updated — Via email correspondence, D’Andrea points out that the ten cent cost described in the IEEE guest editorial was for energy (including battery replacement), and not for the amortized cost of the vehicles and vehicle maintenance. Assuming a vehicle cost of $1000 per unit (this is reasonable if Amazon is buying in the thousands), adding 20% per year for maintenance, and amortizing this over 5 years, this would amount to an additional $400/per year, or roughly $1/day. If each vehicle ran 10 missions per day, that’s an additional 10 cents per package on top of the 10 cents in energy costs calculated previously, for a total cost of about 20 cents per package.

20 cents per delivery is far less than what Amazon is currently paying. According to shipping-industry analysts Amazon typically pays between about $2 and $8 to ship each package, and the possible cost of drone delivery as laid out by Professor D’Andrea would go a long way to reducing Amazon’s annual losses of $3.538 billion related to shipping costs they incurred in 2013 and US$ 8.829 billion in cumulative shipping losses between financial year ended 2011 and financial year ending 2013.

Professor D’Andrea also outlines the obstacles to drone delivery, in addition to regulatory hurdles, privacy concerns, etc., indicating that additional automation research is needed to address three main challenges:

  • vehicle design,
  • localization navigation,
  • vehicle coordination.

Answering these points he provides a very good overview of the obstacles:

Vehicle design encompasses creating machines that are efficient, (most probably) can hover, can operate in a wide range of conditions, and whose reliability rivals that of commercial airliners; this is a significant undertaking that will require many iterations, and the ingenuity and contributions from folks in diverse areas.

Localization and navigation may seem like solved problems because of the many GPS-enabled platforms that already exist, but delivering packages reliably, in different operating conditions, in unstructured and changing environments, will require the integration of low-cost sensors and positioning systems that either do not yet exist, or are still in development.

Finally, thousands of autonomous agents in the air, sharing resources such as charging stations, will require robust co-ordination which can be studied in simulation.

He expects that delivery by drones is a real probability and concludes his opinion piece by writing that for better or for worse ‘goods being delivered by flying machines will result in packages flying above our heads in the not so distant future.’