Keynote Speakers

Powering Nanorobots: An Engineering Challenge - Prof. R. K. Mittal

Prof. R. K. Mittal

A scheme for an Embodied Artificial Intelligence - Dr. Rory C. Flemmer

Dr. Rory C. Flemmer

Recent Advances in Memetic Algorithms for Evolutionary Optimization - Dr Kay Chen Tan

K.C. Tan

What is Quantum Computing, and Does It Have Any Future in Robotics? -
Associate Professor Mel Siegel

Associate Professor Mel Siegel

Prof. R. K. MittalProf. R. K. Mittal

R.K.Mittal is Deputy Director (Administration) and Professor of Mechanical Engineering and Computer Science at Birla Institute of Technology and Science, Pilani (BITS Pilani), India, which is an all-India Institute for higher education to provide the highest quality technical education, at three tiers to students from all over India. He began his academic career at BITS in 1975, moving from lecturer to professor in 1995, as well as serving as Unit Chief, Dean and member/chair of several academic and administrative committees. R.K.Mittal’s career at BITS Pilani is spanned over 33 years now, with executive responsibilities in Engineering, Finance, and Information Technology. During this period he participated and led the team in stream of disruptive computing technologies – from punch cards to the Web – to cater to the in-house administrative computing needs of the university. He has pioneered introduction of several new courses in emerging and interdisciplinary areas.

R. K. Mittal received B. E. (Hons.) Mechanical Engineering, M. E. Mechanical Engineering (with Practice School) and Ph.D. (Software Engineering) degrees from the Birla Institute of Technology and Science, (BITS), Pilani, India, in 1973, 1975, and 1992, respectively. He obtained the highest rank in order of merit in M.E. and was awarded the Institute’s Gold Medal. He has been teaching undergraduate and postgraduate courses, has guided several M. E. Dissertations and five Ph.D. students in Robotics and Software Engineering areas. Three students have completed Ph.D. His research interests includes robust robot designs, two-/three-dimensional robot-path planning, microelectromechanical systems (MEMS), microrobots and nanorobots, nanotechnology, software engineering, and software testing. He is the founding member of the Centre for Robotics and Intelligent Systems (CRIS) created from scratch in 1992 and was its Coordinator until 2000. A team of students have developed the first humanoid in India, named AcYut, which participated in World RoboGames 2008 held at San Francisco, California, USA.

He is also the Dean, Academic Registration and Counselling Division since 1995 and was the first Unit Chief of Computer Assisted Housekeeping Unit (CAHU), from 1987 until 2006. Dr. Mittal is member of IEEE and is the Branch Counselor for the IEEE Students Branch, BITS. He was instrumental in establishing BITS Alumni Association (BITSAA) in 1989 and is the President of the BITSAA.

He has coauthored two textbooks: Robotics & Control (New Delhi, India: McGraw-Hill, 2003) and Elements of Manufacturing Processes (New Delhi, India: Prentice-Hall, 2003); editor of two conference proceedings: EMTM2N-2007 (Research Publishing, Chennai, India) and ISSS-MEMS-2007 (CD Proceedings); numerous in-house course notes, lab manuals and monographs. He has authored or co-authored over 35 papers in international and national peer reviewed journals and conferences. He was Programme Chair of a highly successful International Conference on Emerging Mechanical technology-Macro to Nano, EMTM2N-2007, 16-18 February 2007, BITS Pilani and was joint organizer for 2nd ISSS National Conference on MEMS, Microsensors, Smart Materials, Structures and Systems, ISSS-MEMS2007, November 16-17, 2007, CEERI Pilani.

Powering Nanorobots: An Engineering Challenge

ICARA 2009 Keynote Address - Abstract

Nanorobotics is a fast emerging field of engineering concerned with creating miniaturized robots of the size of few hundred nanometers and below consisting of components of nanoscale or molecular size and with functionalities of their macro-counterparts. There is an all around development in nanotechnology towards realization of nanorobots in the last two decades. Nanorobots will work either in vacuum or in a fluid as flying or swimming machines. Propulsion of nanometer sized robot through a fluid, where friction dominates and motion invariably is overdamped, calls for design strategies very different from the macroscopic world.

Propulsion requires expenditure of energy, transduction of energy and transmission of energy. For nanorobots, the small size and complexity of issues like energy storage and utilization of energy in efficient manner is challenging to engineers. The issues in propulsion have been addressed by scientists and engineers since the advent of research on nanorobotics. The queue has been taken from nature where biology has come up with a large number of concepts ranging from active polymerization of gel network, molecular motors moving on tracks formed by protein filaments, to rotating and beating flagellar mechanisms.

Energetics in the assay of nanorobot propulsion presents hitherto impregnable situation but the continuing attempts by scientists and engineers towards realization of nanorobots are conclusive indications of a solution imminent in near future. Various energy storage possibilities (Gravitational, Mechanical, Chemical, Electrical, Magnetic and Nuclear) and compatible transducing mechanisms to mechanical motion have been explored and are available in literature. For nanorobots, onboard volume is a precious and limited commodity. Energy stored per unit volume (joules/m3) is an appropriate figure of merit for nanoscale energy storage devices. Most of the experimental investigations on energy usage by a nanorobot are done through external excitations and technology for on-board power device is still a challenge to engineers. The continuity of power supply is another issue in energetics of nanorobots as refueling is beyond practical proposition. The key to nanorobot power supply is the efficient conversion of energy from one form to another. Biologicals in nano-domains obtain the continuous power supply from surrounding medium through ATP reduction. The thermal energy content of environment of a nanorobot is abundant and presents a plausible source but its utilization is denied by second law of thermodynamics in ordinary equilibrium processes. Theory does predict that at non-equilibrium fluctuations, thermal content of surrounding medium manifesting as Brownian motion of environmental molecules may be tapped for rectified motion of nanorobots. In a nanorobot, a mechanomechanical transducer needs to be developed to convert environmental Brownian motion into mechanical energy for internal storage or immediate utilization.


Dr. Rory C. FlemmerDr. Rory C. Flemmer

Rory Flemmer is a Senior Lecturer in the School of Engineering and Advanced Technology (SEAT) at Massey University, Palmerston North, New Zealand.

He received a Masters degree in Mechanical Engineering in 1975 and a PhD in Chemical Engineering in 1978 from the University of Natal in South Africa. As an Associate Professor at that university, his research areas included hypersonic flow with mixing and chemical reaction, ultrafiltration, reactors, fluidization, two-phase flow, fractal analysis, high temperature gas heating and artificial intelligence/ artificial vision. He then spent three years as Professor in the department of Mechanical and Aerospace Engineering at the University of West Virginia where he continued his research into artificial intelligence/ artificial vision, fluidization and electrostatic field mechanisms in pneumoconiosis.

From 1989 to 2004, Rory developed an American automation company specializing in robotic and artificial vision systems for Fortune 500 companies such as Corning, Sony, Bausch and Lomb, Union Carbide, Briggs and Stratton, General Motors and Siemens. Projects included the automated high-speed packing of hardwood flooring, precision laser cutting of television tubes, automation of processes for PCB inspection, lumber mills, eyewear, glass and ceramic processes. He acted as Bausch and Lombís international technical consultant for their facilities in the USA (New York, Maryland and Texas), Ireland, Hong Kong, Brazil and India. He developed the Nimbl line of innovative robots.

In 2005 Rory moved to New Zealand. His current research areas are artificial intelligence, artificial vision, automated fruit picking and packing, data sonification and development of a novel wheel chair. He supervises five PhD students and 2 Masterís students. He has published 54 papers and holds 7 patents with 3 patents pending.

A scheme for an Embodied Artificial Intelligence

ICARA 2009 Keynote Address - Abstract

This address discusses the question of building artificial intelligence into a humanoid robot. The approach is rather that of machine builders than analysts and presents a fuzzy blueprint of what is intended to be done over the next two years to produce a humanoid robot which is capable of learning and manipulating in a general environment.

The literature on embedded artificial intelligence is voluminous and all the important questions have been perceived and discussed for 50 years. However the exemplars reported are, on the spectrum of achievement, closer to a fridge light rather than to R2D2 or Terminator III.

The paradigm which is laid out is nothing if not grandiose (though unkind persons might use the word preposterous).

  • The keynote address reports on the development of a technique in artificial vision which allows general objects to be learned, recognized and oriented in six space. (x, y, z, φ1, φ2, φ3). This will be fleshed out and validated by experimental data in papers in the special session on “Embodied Artificial Intelligence”.

  • The presenter argues, on the basis of paleontological evidence, that intelligence and vision have developed simultaneously over evolutionary time and, further, that intelligence and vision are fundamentally concerned with objects. Any sentence in any language is also concerned with objects and the use of language as a paradigm for intelligence follows naturally.

  • Once this paradigm is enunciated, the presentation will go into the details of the following questions:
    • Instinct
    • Memory
    • Logic
    • Teleological planning
    • Play
    • Volition and behaviour
    • “Is there something out there?”
    • Emotion
    • Consciousness

  • The presentation takes the form of a how-to-do discussion of each of these aspects with the notion that only those schemes are proposed which can be implemented and will work.

K.C>Tan Dr Kay Chen Tan

Kay Chen TAN is currently an Associate Professor in the Department of Electrical and Computer Engineering at the National University of Singapore, Singapore. He is actively pursuing research in computational and artificial intelligence, with applications to multi-objective optimization, scheduling, automation, data mining, and games.

Dr Tan has published over 80 journal papers, 100 papers in conference proceedings, co-authored 5 books including Multiobjective Evolutionary Algorithms and Applications (Springer-Verlag, 2005), Modern Industrial Automation Software Design (John Wiley, 2006; Chinese Edition, 2008), Evolutionary Robotics: From Algorithms to Implementations (World Scientific, 2006), Neural Networks: Computational Models and Applications (Springer-Verlag, 2007), and Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms (Springer-Verlag, expected in 2009), co-edited 4 books including Recent Advances in Simulated Evolution and Learning (World Scientific, 2004), Evolutionary Scheduling (Springer-Verlag, 2007), Multiobjective Memetic Algorithms (Springer-Verlag, expected in 2009), and Design and Control of Intelligent Robotic Systems (Springer-Verlag, expected in 2009).

Dr Tan has been invited to be a keynote/invited speaker for many international conferences. He served in the international program committee for over 80 conferences and involved in the organizing committee for over 20 international conferences, including the General Co-Chair for IEEE Congress on Evolutionary Computation 2007 in Singapore and the General Co-Chair for IEEE Symposium on Computational Intelligence in Scheduling 2009 in Tennessee, USA. Dr Tan is currently the Chairman of Evolutionary Computation Technical Committee in IEEE Computational Intelligence Society and a member of Board of Directors in Evolutionary Programming Society. Dr Tan currently serves as an Associate Editor / Editorial Board member of 10 international journals, such as IEEE Transactions on Evolutionary Computation, IEEE Transactions on Computational Intelligence and AI in Games, European Journal of Operational Research, Journal of Scheduling, and International Journal of Systems Science.

Dr Tan received the Recognition Award (2008) from the International Network for Engineering Education & Research (iNEER) for outstanding contributions to

engineering education and research. He was also a winner of the NUS Outstanding Educator Awards (2004), the Engineering Educator Awards (2002, 2003, 2005), the Annual Teaching Excellence Awards (2002, 2003, 2004, 2005, 2006), and the Honour Roll Awards (2007).

Recent Advances in Memetic Algorithms for Evolutionary Optimization

ICARA 2009 Keynote Address - Abstract

Memetic algorithms (MAs), the synergy of evolutionary or any population-based approaches with separate individual learning or local improvement procedures, represent one of the recent growing areas of research in computational intelligence. In the literature, MAs are also referred to as hybrid evolutionary algorithms (EAs), Baldwinian EAs, Lamarckian EAs, cultural algorithms, or genetic local search. With the help of local improvement procedures or synergy between different computational frameworks, MAs are reported to be capable of obtaining high quality solutions more efficiently than conventional EAs across a wide range of application domains. In this talk, issues and recent advances of memetic algorithms for evolutionary optimization will be discussed. The application of these algorithms to a few practical problems will also be presented, such as solving the NP-hard multi-objective routing and scheduling problems, which often involve different competing specifications in a large and highly constrained search space.


Associate Professor Mel SiegelAssociate Professor Mel Siegel

Associate Research Professor
Director, Sensor, Measurement, and Control Lab
The Robotics Institute – School of Computer Science
Carnegie Mellon University
Pittsburgh PA 15213 USA


• Sensing, sensors and instruments, measurement science, system modelling
• AI methods for data fusion, analysis, presentation, and system control
• Sensor fusion for context aware computing / human computer interaction
• 3D-stereoscopic display system concepts, optics, coding, and psychophysics
• Robots and sensors for remote explosives and drug detection, and aircraft inspection
• High-fidelity tele-operation for remote and space–based science
• Innovative sensors and sensor fusion methods for future vehicles and driver safety
• Large networks of small sensors, e.g., to initialize global-scale weather models
• Teaching outreach and program innovation; Technology Peace Corps


• Negative ion structures (laser photo detachment photoelectron spectrometry)
• Ion-atom/molecule collisions (double differential cross-section measurements)
• Atomic hyperfine structure (magnetic resonance in hex pole-focused beams)
• Space, analytical, process, and isotopic mass spectrometry (high pressure ionizers)
• Biotechnology process control (rule-based characterization and decision)
• Piezoelectric and optical tactile sensors (identification and manipulation by robots)
• Solid state gas sensor characterization and mixture analysis (neural networks)
• Analytical and numerical modelling of optical devices and instruments (photons, ions)
• Mobile robots for remote and automated skin inspection of aging aircraft
• Zoneless 3D-autostereoscopic display system


IEEE: Instrumentation and Measurement Society Administrative Committee and Treasurer, IMTC Program Committee, VIMS Program Committee and General Chair, Transactions on Instrumentation and Measurement Associate Editor, chair of Technical Committees in Instrumentation and Measurements Society and Robotics and Automation Society, Senior Member Advancement Panel.


Fellow of the IEEE, cited for contributions to the field of sensors, measurement and robotics.
IR-100 awards for “100 most significant inventions of the year” for inventions in mass spectrometry (2 awards), particle detection, and semiconductor-based gas sensors.
Best paper of the year award, Robotic Assistants for Aircraft Inspectors, Industrial
Robot (MCB University Press).

What is Quantum Computing, and Does It Have Any Future in Robotics?

ICARA 2009 Invited Speaker- Abstract

The field of quantum mechanics has its roots in the early 1900s, its fundamental aspects were well-developed by the 1920s, and spectacularly accurate results were routine by the 1930s.  But the relevance of quantum mechanics to computing was not appreciated until the 1980s, and until very recently work in quantum computing – and in the closely-related quantum information and quantum communication fields – has been entirely theoretical.  Now promising proof-of-principle experimental results are being published with increasing frequency, and several companies are advertising – though it is not clear that they can actually deliver product – quantum communication devices for tamper-proof and eavesdrop-proof transfer of cryptographic keys.  Almost all of this work has been done in the physics community rather than the computer science community, partly perhaps because quantum mechanics can be a mind-boggling topic that requires many years of immersion for it to be internalized, and partly perhaps because the computer science community has plenty of interesting things they can do with rapid successive generations of more and more capable commercial CMOS devices.

The aim of my talk is to introduce the robotics community to what quantum mechanics is and why it seems to be important for the future of computing, and to suggest some problem areas in robotics where new computing opportunities might offer answers where there are now none.  My underlying aim is to get my colleagues in robotics – you – thinking about the possibilities for applications in your own research areas.  Your first challenge is to understand the premises and formalism, and internalize the actual correctness, of quantum mechanics.  What is so hard about it?  It is that the rules of quantum mechanics, the laws of physics before which we could not correctly describe and predict the structure, behavior, and interaction of atoms, electrons, and photons – dictate that these objects, and systems made of them, act in unintuitive ways.  Quantum mechanical behaviors are so different from everyday experience with macroscopic – called “classical” – objects and systems that we find them illogical.  But that is just the way it really is: no theory in any field at any time in history has ever predicted reality – the outcome of actual experiments – with precision that comes anywhere near  quantum mechanics.

So who can argue with success like that?  Most notably Einstein, who famously said – in German, so translations vary and the speaker's actual intent is possibly subject to speculation – “god doesn't play dice with the universe” and “god is subtle but not malicious” arguing against the correctness of quantum mechanics based on correct – according to quantum mechanics – but objectionable – according to Einstein – conclusions that can be drawn from it.  For example, that the outcome of a simple measurement on a system initialized as completely as nature will allow can be predicted no better than to say the result will be one several discrete values whose probabilities the formalism shows  how to calculate.  Or that the act of making such a measurement on a system here can instantaneously affect the probabilities of the allowed outcomes of a measurement on a similar system on Mars.

What does all this physics have to do with information, computation, and communications?  Classical computing is based on classical bits, idealizations of physical objects that can exist in either of two distinct states that we conveniently label 0 and 1; quantum computing is based on quantum bits, idealizations of physical objects that can be observed in either of two distinct states that we conveniently label 0 and 1. But in the absence of actually making said observation they can exist in a mixed state such that when actually observed at a later time there will be predictable probabilities that 0 vs. 1 will be seen.  Sufficiently clever arrangements of several quantum bits thus provide the possibility of massively parallel computing by very small systems – small in size and small in number of quantum bits – as well as powerful new concepts for efficient and secure communication.  In my talk I will try to explain the “thus” in the previous sentence, and connect it to prospects for future robot intelligence.