Category Archives: Engineering

Robots with a delicate touch

whitesgroup demoCan a robot pick up an egg or a baby cactus without damaging either? If it is a conventional ‘hard’ robot then the answer is almost certainly ‘no’. But if it is a ‘soft’ robot then the answer is definitely ‘yes’. They can pick ripe tomatoes from the plant, too. And play the piano with a light touch.

These are all examples used by Professor George Whitesides to illustrate the capability of soft robots during a lecture that I attended last week. The occasion was a scientific discussion meeting on Bio-inspiration of New Technologies which was held to celebrate 350 years to publishing the Philosophical Transactions of the Royal Society. While I was in London listening live to Prof Whitesides and the other eight speakers, other people were listening via video links to Bangalore, India and Sao Paulo, Brazil.

Professor Whitesides’ ingenious robots have ‘fingers’ built from the same soft rubber that is used in implants. They are constructed with a solid layer on one face that is curled around the object being picked up by the inflation of compartments on the reverse face. The inflation of the compartments on the reverse face cause the face to lengthen and the ‘finger’ bends to accommodate the change in length. Careful design of the inflated compartments allows the fingers to conform to the shape being picked up and the use of microfluidics ensures it is not damaged.

Professor Whiteside identified star fish as the source of inspiration for the design of his soft robots. I don’t feel that this short piece has done justice to his work. If, nevertheless, you feel inspired to work for him then there’s probably a queue and since he is professor at Harvard it is almost certainly a long one. His research group has also spun out a company, Soft Robotics Inc. so you could buy some soft robots and explore their capabilities…

Engineers are slow, error-prone…

Professor Kristina Shea speaking in Munich

Professor Kristina Shea speaking in Munich

‘Engineers are slow, error-prone, biased, limited in experience and conditioned by education; and so we want to automate to increase reliability.’  This my paraphrasing of  Professor Kristina Shea speaking at a workshop in Munich last year.  At first glance it appears insulting to my profession but actually it is just classifying us with the rest of the human race.  Everybody has these attributes, at least when compared to computers.  And they are major impediments to engineers trying to design and manufacture systems that have the high reliability and low cost expected by the general public.

Professor Shea is Head of the Engineering Design and Computing Laboratory at ETH Zurich.  Her research focuses on developing computational tools that enable the design of complex engineered systems and products.  An underlying theme of her work, which she was talking about at the workshop, is automating design and fabrication processes to eliminate the limitations caused by engineers.

Actually, I quite like these limitations and perhaps they are essential because they represent the entropy or chaos that the second law of thermodynamics tells us must be created in every process.  Many people have expressed concern about the development of Artificial Intelligence (AI) capable of designing machines smarter than humans, which would quickly design even smarter machines that we could neither understand nor control.  Chaos would follow, possibly with apocalyptic consequences for human society.  To quote the British mathematician, IJ Good (1916-2009), “There would then unquestionably be an ‘intelligence explosion’, and the intelligence of man would be left far behind. Thus the first ultra-intelligent machine is the last invention that man need ever make.”  Stephen Cave in his essay ‘Rise of machines’ in the FT on March 20th, 2015, citing James Barrat  suggested that “artificial intelligence could become super-intelligence in a matter of days, as it fixes its own bugs, rewriting its software and drawing on the wealth of information now available online”.

The decisions that we make are influenced, or even constrained, by a set of core values, unstated assumptions and what we call common sense which are very difficult to express in prose never mind computer code.  So it seems likely that an ultra-intelligent machine would lack some or all of these boundary conditions with the consequences that while  ‘To err is human, to really foul things up you need a computer.’  To quote Paul R. Ehrlich.

Hence, I would like to think that there is still room for engineers to provide the creativity.  Perhaps Professor Shea is simply proposing a more sophisticated version of the out-of-skull thinking I wrote about in my post on March 18th, 2015.

Sources:

Follow the link to Kristina Shea’s slides from the workshop on International Workshop on Validation of Computational Mechanics Models.

Stephen Cave, Rise of the machines, Essay in the Financial Times on 21/22 March, 2015.

James Barrat, ‘Our Final Invention: Artificial Intelligence and the End of the Human Era‘, St Martins Griffin, 2015

Cow bladders led to modern strain measurement

 

softball figureSir David Brewster was a prolific experimentalist who published seven papers in the Philosophical Transactions of the Royal Society during 1815 and 1816. In his report dated October 22nd, 1814 that was published by the Royal Society one hundred years ago in January 1815, he described his observations on the depolarisation in more than fifty materials as diverse as sulphur and the bladder of a cow. He followed this with a series of experiments on glass sheets subject to various loads and reported his observations in the of photographic plates that show photoelastic fringe patterns which would become instantly recognisable to generations of engineers. Two hundred year later, digital technology has revolutionised photoelasticity so that it is no longer necessary to generate fringes that can be ‘seen’, as in Brewster’s experiments. Instead, digital sensors allow us to measure changes in light intensity that are undetectable to the naked eye and digital computers permit the processing of arrays of tens of thousands of measurements in less than the blink of an eye to yield maps of strain magnitude and direction in complex components. However, the principles employed in digital photoelasticity are the same as those first elucidated by Brewster and involve collecting images at multiple rotational steps of one or more of the polarising elements in a polariscope and then using Fourier analysis or matrix algebra to solve the equations describing the stress-optic law, i.e. the relationship between the applied stress and the observed change in transmitted light intensity. A polariscope is the term given to the series of polarisers and quarter-waveplates used by almost every photoelastician since Brewster to observe photoelastic fringes. One of Brewster’s other great inventions was the kaleidoscope of which there is an early example in the Science Museum in London. Recently, the concept of the kaleidoscope has been combined with a polariscope to create the poleidoscope that allows the multiple images required for digital photoelasticity to be acquired simultaneously, which is useful for dynamic applications such as in the impact example shown in the picture. These advances allow digital photoelasticity to be used not only by laboratory-based stress analysts but also in quality assurance procedures, for instance to monitor in real-time the stresses induced in float glass during production, or to investigate the residual stress in silicon wafers using infra-red light.

The picture shows a sequence of maps of photoelastic fringe order (right) showing the stress induced in an epoxy resin block when impacted by a soft ball falling under gravity (left). The maps were obtained using a precursor to the poleidoscope and a high-speed digital camera recording 4000 frames per second for the 10x10mm area shown by the white box in the schematic.

For more a little more on photoelasticity see http://www.experimentalstress.com/basic_experimental_mechanics/photoelasticity.htm

Sources:

Brewster, D., Experiments on the depolarisation of light as exhibited by various mineral, animal , and vegetable bodies, with a reference of the phenomena to the general principles of polarisation, Phil. Trans. R. Soc. Lond. 105:29-53, 1815. http://rstl.royalsocietypublishing.org/content/105/29.full.pdf+html

Brewster, D., On the communication of the structure of doubly refracting crystals to glass, muriate of soda, fluor spar, and other substances by mechanical compression and dilatation, Phil. Trans. R. Soc. Lond. 106:156-178, 1816. http://rstl.royalsocietypublishing.org/content/106/156.full.pdf+html

Ramesh, K., Kasimayan, T., Neethi Simon, B., Digital photoelasticity – a comprehensive review, J. Strain Analysis, 46(4):245-266, 2011. http://sdj.sagepub.com/content/46/4/245.abstract

www.sciencemuseum.org.uk/online_science/explore_our_collections/objects/index/smxg-3823?agent=smxg-52657

Lesniak, J.R., Zhang, S.J., Patterson, E.A., The design and evaluation of the poleidoscope: a novel digital polariscope, Experimental Mechanics, 44(2):128-135, 2004.

Hobbs, J.W., Greene, R.J., Patterson, E.A., 2003, A novel instrument for transient photoelasticity, Experimental Mechanics, 43(4):403-409, 2003.

Seeing the invisible

Track of the Brownian motion of a 50 nanometre diameter particle

Track of the Brownian motion of a 50 nanometre diameter particle in a fluid.

Nanoparticles are being used in a myriad of applications including sunscreen creams, sports equipment and even to study the stickiness of snot!  By definition, nanoparticles should have one dimension less than 100 nanometres, which is one thousandth of the thickness of a human hair.  Some nanoparticles are toxic to humans and so scientists are studying the interaction of nanoparticles with human cells.  However, a spherical nanoparticle is smaller than the wavelength length of visible light and so is invisible in a conventional optical microscope used by biologists.  We can view nanoparticles using a scanning electron microscope but the electron beam damages living cells so this is not a good solution.  An alternative is to adjust an optical microscope so that the nanoparticles produce caustics [see post entitled ‘Caustics’ on October 15th, 2014] many times the size of the particle.  These ‘adjustments’ involve closing an aperture to produce a pin-hole source of illumination and introducing a filter that only allows through a narrow band of light wavelengths.  An optical microscope adjusted in this way is called a ‘nanoscope’ and with the addition of a small oscillator on the microscope objective lens can be used to track nanoparticles using the technique described in last week’s post entitled ‘Holes in liquid‘.

The smallest particles that we have managed to observe using this technique were gold particles of diameter 3 nanometres , or about 1o atoms in diameter dispersed in a liquid.

 

Image of 3nm diameter gold particle in a conventional optical microscope (top right), in a nanoscope (bottom right) and composite images in the z-direction of the caustic formed in the nanoscope (left).

Image of 3nm diameter gold particle in a conventional optical microscope (top right), in a nanoscope (bottom right) and composite images in the z-direction of the caustic formed in the nanoscope (left).

Sources:

http://ihcp.jrc.ec.europa.eu/our_activities/nanotechnology/jrc-scientists-develop-a-technique-for-automated-three-dimensional-nanoparticle-tracking-using-a-conventional-microscope

‘Scientists use gold nanoparticles to study the stickiness of snot’ by Rachel Feldman in the Washington Post on October 9th, 2014.

J.-M. Gineste, P. Macko, E.A. Patterson, & M.P. Whelan, Three-dimensional automated nanoparticle tracking using Mie scattering in an optical microscope, Journal of Microscopy, Vol. 243, Pt 2 2011, pp. 172–178

Patterson, E.A., & Whelan, M.P., Optical signatures of small nanoparticles in a conventional microscope, Small, 4(10): 1703-1706, 2008.