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Professor Mandyam Veerambudi Srinivasan (Srini) was interviewed in 2011 for the Interviews with Australian scientists series. By viewing the interviews in this series or reading the transcripts and extracts, your students can begin to appreciate Australia's contribution to the growth of scientific knowledge and view science as a human endeavour. These interviews specifically tie into the Australian Curriculum strand Science as a human endeavour and its two sub-strands ‘Nature and development of science’ and ‘Use and influence of science’.
The following summary of Professor Srinivasan’s career sets the context for the extract chosen for these teachers’ notes. The extract discusses the mechanism of linking bee vision with the development of self-flying, unmanned aircraft. Use the focus questions that accompany the extract to promote discussion among your students.
Mandyam Veerambudi Srinivasan was born in Poona, India on 15 September, 1948. His school days were spent between Poona, Calcutta and Delhi before his family finally settled in Bangalore. After finishing school in 1962, Srini enrolled in a five year undergraduate degree in engineering at Bangalore University (1962-1967), where, in between marching for the national cadet corps, he learnt the many facets of electrical, mechanical and civil engineering. Srini then completed a Master’s degree in Applied Electronics and Servomechanisms at the Indian Institute of Science (1970). He developed a model of the human eye movement control system, which first sparked an interest in using physics, mathematics and engineering to understand biology. Srini then travelled to Yale University (USA) to embark on a Masters of Philosophy in Engineering and Applied Science (1973) and a PhD in Engineering and Applied Science (1976). It was here at Yale where Srini had his first introduction to insect vision, through his research on movement perception in flies.
After completing his PhD, Srini moved to Canberra to take up a postdoctoral position at the Departments of Neurobiology and Applied Mathematics at the ANU (1978-1982). During this period he studied how neurons in the fly’s brain analyse the pattern of motion that is experienced by the eyes as it flies through the environment. In 1982 Srini secured a research position in Zurich, Switzerland to work on insect behaviour. There he learnt two more new languages (taking the total to six) and learnt an important skill that was to prove pivotal to his future research - how to train and work with honeybees.
In 1985 Srini returned to the ANU, and commenced setting up an interdisciplinary research group within the Research School of Biological Sciences (RSBS). His group focused on unravelling how bees use their vision to successfully navigate through narrow tunnels and make precise landings. This work influenced others to develop self-navigating robots, and lead Srini’s group to receive international funding for the development of intelligent unmanned aerial vehicles. In the process, Srini’s group corrected the previous findings of a Nobel Laureate, through discovering that bees use their vision to accurately calculate distance, and not by measuring the amount of energy that they had consumed. In 2007 Srini headed north to the University of Queensland to work at the Queensland Brain Institute and the School of Information Technology and Electrical Engineering, where he is currently a Professor of Visual Neuroscience. His research focuses on vision, perception and cognition in animals with simple nervous systems, and on how these might be used in machine vision and robotics.
Professor Srinivasan has received numerous prestigious awards recognising his contributions to science. Some of these include the Inaugural Federation Fellowship and Australasian Science Prize in 2001, an Australian Centenary Medal in 2003, the Australia Prime Minister’s Science Prize in 2006, a Queensland Smart State Premier's Fellowship in 2007, the U.K. Rank Prize for Optoelectronics in 2008, and the Distinguished Alumni Award of the Indian Institute of Science in 2009.
Professor Srinivasan received a Doctor of Science in Neuroethology from the Australian National University in 1994 and an Honorary Doctorate from the University of Zurich in 2002. Other honours include Fellowship of the Royal Society of London (2001), Inaugural Australian Federation Fellowship award of the Australian Research Council (2001) and Fellowship of the Academy of Sciences for the Developing World (2006), and the Membership of the Order of Australia (AM, 2012) Professor Srinivasan was elected to the Fellowship of the Australian Academy of Science in 1995.
Robots that see the world through the eyes of a bee
Could you talk a little about linking your knowledge of vision with robotics?
All of these have been sort of accidental observations. In fact, it was not something that we set out to do. That is what is amazing about science, it’s so serendipitous. That is why I think we shouldn’t even plan to do something; you should just get your hands dirty, so to speak, and see what happens. For example, we were curious to see how bees fly safely through narrow passages. We had them coming into our lab. We found that they came through a hole in the window and we found that, when they flew through this hole, they flew rather precisely through the middle of the hole. I asked myself, ‘How are they doing this, despite the fact that they don’t have any stereovision to measure distances to various edges and so on?’ It turned out—we showed—that they were doing this by actually measuring the speed of motion of the images of the two edges with the two eyes and positioning themselves so that they stayed in the middle of this hole. So, if one edge is basically moving faster, it means that you are closer to that edge and you move away from that edge. You balance the visual flow on the two sides and that allows you to steer down gorges, tunnels or corridors in a very simple way, which the robotics people hadn’t realised. After we published this work on bees, a number of labs—robotics labs—started to produce robots that went down corridors using the same principle. It was something that we hadn’t thought of ourselves, but it led to this.
The other thing, for example, that came as a complete surprise—it probably would not have come if we had looked at it as straight engineers—was how insects do a smooth landing on a horizontal surface. As you know, they don’t use radar, laser beams or anything like that. All they seem to do, if you analyse the data, is move in such a way that the velocity of the image of the ground is held constant as they approach it. So, if you keep the image velocity of the ground constant as you get closer and closer to the ground, this automatically ensures that you are flying slower and slower. Finally, when you are close enough to touch down, you are moving at almost zero speed, so you don’t burn your feet as you make contact. It’s a beautiful biological autopilot for landing. With a system like this, you don’t need to know how far away you are from the ground and you don’t need to know how rapidly you are approaching it. All that you need to do is look at the ground and adjust your speed so that the ground appears to be moving at the same speed as you come towards it. It’s a beautiful biological auto pilot. That is something that we are putting into aircraft now.
Future directions: unmanned aerial vehicles and mine-detecting bees
What do you see as the future of these lines of research?
In one sense, the low-level vision and navigation research will continue to play a role in building intelligent unmanned aerial vehicles that people can use for reconnaissance, surveillance and planetary exploration, because there aren’t going to be any GPS satellites, for example, put up for a long time. Instead, you really have to rely on your own senses and behave like a bird or an insect. That is where this low-level vision and navigation research can play a role.
The other aspect is that, by looking at the cognitive aspects of bees, which are very smart creatures, we might be able to learn how some of these fairly sophisticated computations happen in creatures with small brains. For example, learning to solve a maze or breaking camouflage. You can train bees to see through camouflaged objects, which they normally would not be able to see. There is a lot of clever things that they do. We don’t know exactly how they do it yet; but I think that the brain of the bee, being a fairly simple entity with fewer neurones, might give us some leads on this.
I understand that they are training bees to work for customs agents.
Oh yes; that is a very interesting application. You can train bees. I don’t know how well it will work in a public area or scenario. But another related area, which is turning out to be quite promising, is detecting hidden mines. What you can do is train a hive of bees to feed from a sugar water source that is laced with some of the odorous chemicals that are exuded by a mine. Then you take this hive and place it near an area where you think these mines might be around and apparently you find that these bees will settle in a clump over where the mine is. They don’t detonate the mine, because they are very light. Then, of course, you can send something to safely detonate the mine—and it is similar in customs for picking up people with illegal things that they are trying to traffic.
An edited transcript of the full interview can be found here.
Focus questions
[Students may need access to a science reference book, dictionary or the internet to answer some of these questions.]
Select activities that are most appropriate for your lesson plan or add your own. These activities align with the Australian Curriculum strands ‘Science Understanding’, ‘Science as a Human Endeavour’ and ‘Science Inquiry Skills’, as well as the New South Wales syllabus Stage 6 Senior Science outcome 9.3.1 and Stage 6 Biology outcome 9.5.6. You can also encourage students to identify key issues in the preceding extract and devise their own questions or topics for discussion.
Australian Academy of Science
Scientific American Frontiers, USA
Other resources featuring Srini and his research:
Research:
Bees follow polarised light through a maze
1 February 2011 (by Wendy Zukerman)
http://www.newscientist.com/article/dn20058-bees-follow-polarised-light-through-a-maze.html
Pessimistic bees forgo life's pleasures
3 June 2011 (By Branwen Morgan)
http://www.abc.net.au/science/articles/2011/06/03/3234845.htm
Flying, flocking, and squirming robots at IROS
11 October 2011 (By MacGregor Campbell)
http://www.newscientist.com/blogs/onepercent/2011/10/flying-flocking-and-squirming.html
Birds sense speed to avoid crashing
31 October 2011 (By Stuart Gary)
http://www.abc.net.au/science/articles/2011/10/31/3349583.htm
How birds fly fast through narrow spaces
3 November 2011 (By Liz Williams)
http://www.australiangeographic.com.au/journal/how-birds-fly-fast-through-narrow-spaces.htm
Robot aircraft learn the way ‘up’
13 December 2011 (By The Vision Centre)
http://www.sciencealert.com.au/news/20111212-22936.html
UAVs navigate with insect-like vision
14 December 2011 (By Anna Salleh)
http://www.abc.net.au/science/articles/2011/12/14/3390667.htm
Flight of the Honeybee
1 December 1 2011 (By Richard Grant)
http://the-scientist.com/2011/12/01/flight-of-the-honeybee/
velocity
bees
vision
robots
neuron
navigation
surveillance
cognition
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