In recent years scientists have taken huge steps towards the bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots (1). The plant-robot interactions through cyborg plants have been investigated in an effort to apply lessons from plants to robots, which provided another role for these organisms other than being a food source or decoration items. There are several joint experimental, numerical and robotic studies conducted in this newly developed area. One of the examples includes a flower robot made by Korean engineers which has the appearance of a common flower with petals, stem and leaves (2). The flower robot has sensing ability, moving mechanism, and home appliance function. It can recognize environmental conditions such as room temperature, pressure, voice and light intensity and can imitate the blooming of a flower, the bending of the stem and the stirring of the leaves in the wind. Other than these, the flower robot functions as a humidifier, a vision/voice recording system and an illumination device. For example, when flower robot receives light, it senses the intensity of the light and blooms. On the contrary, when it is dark, as the flower robot starts fading away and its illumination device turns on to flash the room.

Plantas nomadas, made by Mexican artist Gilberto Espaza, is another example of cyborg plants. It uses dirty water to live. It is a miniature eco-system consisting of plants and micro-organisms within a robotic shell. Each of the components symbiotically relies on the others: the plant provides the perfect environment for the microbe, and the microbe (in a microbial fuel cell) transforms nutrients in dirty water into energy to power the robotic components, and the robotic components provide mobility (3).

A team from Switzerland has been working on a project that endows a robot with the ability to react in response to environmental stress of a plant in order to maintain the state of the plant. The robotic devices monitor the changes in morphology and electrical activity of the avocado plants. According to these parameters, it classifies the drought level and triggers irrigation when necessary (4).

Some of the artists like James Stone, who is a Media Artist specializing in digital technologies and fabrication, are interested in seeing if plants are prone to act in certain ways, show preference and possibly display other traits such as emotion. Artists are specifically curious as to what would happen when a plant is augmented with technology but also given full control over such technology to do with it whatever it chooses (5). To see the results of such systems that provides a means for the plant to interact with people or things will surely be fascinating. A study in this line of research is done by a group of researchers in mobile robotics at ETH Zürich, whose long-term research goal is also to bestow machines with the ability to gain and employ knowledge from the universe to improve their intelligence, by building a prototype called iRobot Create. This cyborg plant consists of a computer running Linux, a normal plant and additional sensors and lives its own life, following its internal needs of water, sunlight and electrical energy (6). The cyborg stays away from obstacles using ultrasonic sensors, finds the best light spot using light sensors and goes to a recharge and to a mock-up water station using iRobot’s infrared sensor. Moreover, its sensors pick up noise caused by people moving around nearby, allowing cyborg plant to react by moving out of the way, to prevent themselves from getting underfoot (7).

It is very important to improve the ability of robots to work successfully in a complex and harsh environment, which would increase their usages. In one of those efforts exploring the use of biological systems to control robots under changing environmental conditions, Dr. David Hu and his group from Georgia Institute of Technology (8) used the Mexican jumping bean, Laspeyresia saltitans, which consists of an empty seed housing a moth larva. Heating by the sun stimulates movements by the larva which rolls, jumps and flips by the bean. They explored this unique means of rolling locomotion and recorded bean trajectories across a series of terrain types, including one-dimensional channels and planar surfaces of varying inclination by Time-lapse videography. They found that the shell encumbers the larva’s locomotion, decreasing its speed on flat surfaces by three-fold. Interestingly, they also showed that the two-dimensional search algorithm of the bean resembles the run-and-tumble search of bacteria. When they tested this search algorithm using both an agent-based simulation and a wheeled Scribbler robot, they demonstrated that the algorithm succeeds in propelling the robot away from regions of high temperature. It is amazing that from a study that involves a plant seed, a moth larva and a robot, scientists may develop applications in biomimetic micro-scale navigation systems.

The hi-tech devices that have been inspired by biological systems are not limited by the ones stimulated with plants. The insect world also represents a huge and original database for future bio-inspired systems, vehicles, and micro-vehicles (9). For example, the process of motion detection system in the fly’s eye is a good example of a neural circuit that was used for robot automatic piloting. Recently, a novel bat-like unmanned aerial vehicle inspired by the morphing-wing mechanism of bats has been presented (10). Other than that, body undulation used by snakes and the physical structure of the body of a snake may offer major advantages over typical legged or wheeled locomotion designs in certain types of scenarios, therefore a large number of research groups have developed snake-inspired robots to make use of these benefits (11). Caenorhabditis elegans, a roundworm which has similar motions with snakes but with a simpler structure, was also selected to develop a small crawling robot with a thermal shape memory alloy, a homogeneous mixture or solid solution of two or more metal, as an actuator (a type of motor for moving or controlling a mechanism or system) due to the similarities of its properties to C. elegans muscles. (12).

Not only multicellular organisms but also unicellular (single-celled) organisms are utilized for generating cyborgs; for example, scientists used circuits prepared from Physarum polycephalum, amoeboid plasmodia of the slime mold, to control an omni-directional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical characteristics of intracellular information processing and the response from the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robot’s actuators(1).

In addition, a new biorobotic system using human neuroblastoma cultures was introduced in 2011 by a Spanish engineering group (13). Multielectrode Arrays Setups have been designed for direct culturing neural cells over silicon or glass substrates. The main objective of this work is to run a robot using this biological neuroprocessor and the final system could be used for many things such as testing how chemicals influence the behavior of the robot.

In summary, manipulation of robots that use living organisms as an interface to perceive the environment and transfer their responses into functions seem to have endless applications as well as challenges. Biologically-inspired technologies represent an emerging and promising field of interdisciplinary areas composed of engineering, computer sciences, chemistry, biology, physics and even art. In nature there are so many living and non-living elements designed by God to help us develop and improve robots to make our lives easier, better and more productive. Even a flower can offer us with something more than color and scent, and that is if we start thinking outside the box like so many people mentioned above have done.

Safiye Arslan is a Research fellow in the area of molecular biology in Nevada.

References

1. Tsuda, S., Zauner, K. P., & Gunji, Y. P. (2006). Robot Control: From Silicon Circuitry to Cells, Biologically Inspired Approaches to Advanced Information Technology (pp. 20-32). Osaka, Japan: Springer.

2. H. K. Park, S. H. Park, J. O. Park, (2007) “A study on the Moving Mechanism for Flower Robot,” International Conference on Control, Automation and Systems.

3. http://m.ammoth.us/blog/2010/09/a-cyborg-arboretum/

4. http://www.cyborgplant.com/

5. http://www.manofstone.com/cyborgplants/

6. Stocker, J., Veillat, A., Magnenat, S., Colas, F., Siegwart, R. (2011). Towards Adaptive Robotic Green Plants. TAROS 2011: 422-423

7. http://www.newscientist.com/article/mg21128305.900-robotassisted-plants-find-their-place-in-the-sun.html

8. West, D. M., Lal, I. K., Leamy, M. J., & Hu, D. L. (2012). Locomotion of Mexican jumping beans. Bioinspiration & Biomimetics, 7(3), 036014. doi:10.1088/1748-3182/7/3/036014

9. http://www.ercim.eu/EU-NSF/Bionics.pdf

10. Colorado, J., Barrientos, A., Rossi, C., & Parra, C. (2012). Inertial attitude control of a bat-like morphing-wing air vehicle. Bioinspiration & Biomimetics, 8(1), 016001. doi:10.1088/1748-3182/8/1/016001

11. Hopkins, J. K., Spranklin, B. W., & Gupta, S. K. (2009). A survey of snake-inspired robot designs. Bioinspiration & Biomimetics, 4(2), 021001. doi:10.1088/1748-3182/4/2/021001

12. Yuk, H., Kim, D., Lee, H., Jo, S., & Shin, J. H. (2011). Shape memory alloy-based small crawling robots inspired by C. elegans. Bioinspiration & Biomimetics, 6(4), 046002. doi:10.1088/1748-3182/6/4/046002

13. Ferrández, J. M., Lorente, V., de Santos, D., Cuadra, J. M., de la Paz, F., Alvarez, J. R., & Fernández, E. (2011). Human neuroblastoma cultures for biorobotics. Conference proceedings : … Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2011, 6672-5. doi:10.1109/IEMBS.2011.6091645

Robots that “care” are no longer merely science fiction …

Producing machines that look and behave like people seems to be a human project with a long history. Mention of a Jewish Rabbi producing an instance of the legendary golem (a creature understood to possess an active human-like body, while lacking a soul) appeared as early as the 4th century CE. The celebrated 13th-century Muslim engineer Ibn al-Razzaz al-Jazari undoubtedly designed, and may have constructed, what has been described in present-day terms as “the first programmable human-like robotic device” – a spectacular artifact featuring four robotic musicians performing on a floating boat (Nicks 2010). Inspired by animated life-like figures reportedly created by an ancient Greek named Ctesibus, Leonardo da Vinci – around the time in the 1400s at which he began painting his famous Last Supper – also designed a human-like robot resembling a knight in armor. Fascination with the idea of crafting convincing imitations of people appears to have been part of human history for millennia.

In more recent times, though, modern computers – and with them, research introducing so-called “artificial intelligence” (AI) – have begun to give this long-standing fascination some significant new dimensions. Perhaps the most widely recognized contemporary human-like (or, nowadays, “humanoid”) robot is a product of Japanese science and technology named “ASIMO.” Resembling a short (4 ft 3 in) astronaut wearing a backpack, ASIMO represents the fruit of several decades of research and development conducted by the Honda Motor Company. Videos on the company’s official web site show ASIMO climbing stairs, jogging, balancing on one foot, visually recognizing people by name, and serving a tray of beverages to restaurant patrons. Similar examples of this impressive humanoid robot technology exist in other countries as well – e.g., Turkey (Today’s Zaman 2010), United Arab Emirates (Fahad Inc. 2008), and South Korea (Impactlab.net 2008).

Investment by business enterprises in the significant cost and engineering effort required to design and build these curiously humanoid machines constitutes one of the “new dimensions” previously mentioned. Historical figures such as Al-Jazari and da Vinci, after all, were not responding to global marketing prospects with their robotic creations. In contrast, a current Honda Motor Company web site tells us that ASIMO was intended to be more than an attention-catching novelty from the beginning; in fact, it was “created solely to perform tasks to assist people, especially those lacking full mobility” (Honda Robotics 2011). Similarly, the president of a Robotic Industries Association reports that South Korea is “taking the lead in promoting the use of robots for service applications such as elder care” (Burnstein 2009). A former GM of the Microsoft Robotics Group has identified such assistive care as the market that “intrigues” him the most, citing approaching increases in senior populations – and, consequently, heavier burdens upon healthcare systems – as factors that may “present the ‘killer app’ for personal robots” (Foley 2009). A 2009 online report titled “Robot Nurses to Care for Japanese Elderly within Five Years” reports that Warwick University, in England, has undertaken a “three year 2.7 million dollar project to develop a robot nurse,” predicting that “nurses could be delegating tasks to robotic colleagues by 2020” (Zygbotics 2009).

It is important to note that such robotic “colleagues” of human nurses commonly are intended to be suited for fairly intimate kinds of social interactions with people. One finds, for instance, references to robotic assistance in recreation and with feeding, grooming, walking, bathing, etc. (Babyboomercaretaker.com 2007). Accordingly, we encounter another new dimension. Robotic arms have welded and painted in our automobile factories for decades, but the repetitive activities of these familiar industrial robots are profoundly different from interaction with a humanoid machine that helps one’s aging grandmother eat her dinner and take her medicine (perhaps even chatting and playing a card game with her). Moreover, the latter type of robot no longer is mere science fiction; design and construction of machines to perform these kinds of personal human-robot interactions are taking place now.

… and these robots that “care” invite some questions

Considered only as machines meant to assist overburdened nurses with their care of older people, the types of humanoid robots just described might initially be categorized simply as useful new tools. We have reasons to wonder, though, how long those who will be interacting regularly with these life-like robots can be expected to perceive them merely as tools. So-called “animaloid” robots, such as the robotic dog AIBO that was marketed in recent years by the Sony Corporation, admittedly represent a somewhat different class of robotic artifact than the more complex contemporary humanoids such as ASIMO. Nevertheless, empirical studies of human-robot interaction even with AIBO have uncovered some relevant thought-provoking surprises. Not long ago, for example, numerous online postings by owners of AIBO began appearing on Internet forums. One study of these postings noted the following confession by an AIBO owner:

The other day I proved to myself that I do indeed treat him as if he were alive, because I was getting changed to go out, and [AIBO] was in the room, but before I got changed I stuck him in a corner so he didn’t see me! (Friedman, Kahn, and Hagman 2003, 278)

Regardless of whether this posted confession was altogether truthful, its expressed thought of needing modesty in this case clearly alerts us to the potential psychological potency of human interaction with such machines. Abrahamic religions, through their shared accounts of the Garden of Eden, have long recognized appropriateness of modesty between even the primordial man and woman – but application of that sentiment to our dealings with a battery-operated dog suggests how plastic human notions of personhood might be!

For that matter, professional testimony of such plasticity for the specific case of humanoid robots is available in a frequently-quoted set of observations by Professor Sherry Turkle, Director of the MIT Initiative on Technology and Self, at the Massachusetts Institute of Technology. One of her MIT colleagues, widely-recognized roboticist Rodney Brooks, is among the many people who have cited Turkle’s report of her first encounter with his experimental humanoid robot, Cog; note carefully Sherry’s candid description of the experience:

Cog “noticed” me soon after I entered its room. Its head turned to follow me and I was embarrassed to note that this made me happy. I found myself competing with another visitor for its attention. At one point, I felt sure that Cog’s eyes had “caught” my own. My visit left me shaken – not by anything that Cog was able to accomplish but by my own reaction to “him.” For years whenever I had heard Rodney Brooks speak about his robotic “creatures,” I had always been careful to mentally put quotation marks around the word. But now, with Cog, I had found the quotation marks had disappeared. Despite myself and despite my continuing skepticism about this research project, I had behaved as though in the presence of another being. (Brooks 2003, 149)

Professor Turkle’s testimony is consistent with an entire literature of contemporary research in human-robot interaction that suggests a deep human predisposition progressively to accept as peers various machines that convincingly mimic human appearance and autonomous behavior. Her reference to discovering herself behaving as though she were “in the presence of another being” points, in turn, toward some questions that invite our reflection.

First, one might inquire whether (and why) it could matter that humans seem so inclined to regard convincingly humanoid machines as peers. For some people, it apparently does not matter. From his perspective as a practicing Zen Buddhist, for example, robotics engineer Masahiro Mori has argued against insisting upon any profound distinction between persons and robots, noting that there “must also be buddha-nature in the machines and robots that my colleagues and I make” (Mori 1999, 174). In contrast, though, a pilot study has suggested that Abrahamic theistic belief in creation of individual human souls by a personal deity may be related to disapproval of human-robot interaction “with life-like personal robots that requires human acceptance of the robots at intimate levels” (Metzler and Lewis 2008, 22). This finding resonates with a respected voice in modern Christian theology. Paul Tillich, in Volume Three of his monumental Systematic Theology, addresses “objects that are produced by the technical act,” warning that “by virtue of producing and directing mere things” one can lose one’s “character as an independent self” and “become a thing” (74). Again, Jewish theologian and philosopher Martin Buber, widely remembered for his distinction between “I – Thou” and “I – It” relations, issues a similar warning in I and Thou:

And in all the seriousness of truth, hear this: without It man cannot live.

But he who lives with It alone is not a man. (34)

Apparently, we have reasons to expect that individuals belonging to Abrahamic religious traditions may especially feel troubled when they find themselves treating humanoid machines as though they were peers.

Within the Abrahamic religious family, after all, human beings historically have been regarded as spiritually special, and understood as belonging to a category fundamentally different from any technological artifacts that they might construct for amusement, or as tools. Anglican priest (and physicist) John Polkinghorne has emphasized significance of “the mystery of the human person,” which involves “our embodied nature, embedded in the physical world but transcending a merely reductive physicality” (Polkinghorne 1998, 80). Both the mystery and the transcendence that Polkinghorne mentions are punctuated clearly, as well, in the Holy Qur’an: And they will ask thee of the Spirit. SAY: The Spirit proceedeth at my Lord’s command: but of knowledge, only a little to you is given (The Night Journey – Sura 17:85). The theistic perspective of this family of religions tends to link the human person, as a free moral agent, with a spiritual level of reality that is not completely expressible in terms of everyday (macro-level) entities such as rocks and trees – and machines.

It may be pertinent at this point to inquire whether the spiritual level of reality envisioned by these religious faiths might arguably be represented even in current science. To be sure, the robotic and AI technologies upon which we have focused in this essay are discussed almost entirely nowadays with so-called “macro-level” accounts of discrete, individualized entities. Computer scientists typically view all “information processing” executed by contemporary computers as reducible to operations of the celebrated Turing Machine formalism, which imagines an abstract machine successively “reading” well-defined symbols (0 or 1) on an external tape, comparing them with its current internal “state,” and then implementing clearly prescribed (albeit possibly null) changes on the tape and its own internal state. Physicists working with quantum mechanics, however, have discovered a quite different level of reality that requires a so-called “quantum-level” description. The description is expressed mathematically in terms of complex numbers (incorporating an imaginary unit equal to the square root of negative one) and it explores a reality in which individualized entities of the macro-level (this table, that book, etc.) simply are no longer present. An atom may be understood to contain four electrons, but – in principle – one cannot select and track, say, the changing locations over time of a specific individual electron among the four. Pondering this strange new reality, mathematical physicist Roger Penrose has argued (via his Shadows of the Mind) that human consciousness cannot be modeled in terms of the Turing Machine formalism, requiring, instead, the resources of an advanced quantum physics. If the emerging technology of “quantum computers” eventually could yield a machine consistent with Roger Penrose’s understanding of how the human brain operates when we experience consciousness, future robots incorporating such computers might open possibilities for exciting new dialogue between religion and science.

Under present circumstances, though, we can discern the outlines of potential difficulties in the not-so-distant future. Specifically, elderly members of the Abrahamic faiths may find themselves increasingly conflicted in responding to robotic “caregivers.” On one hand, following natural predispositions, they will be inclined to accept the machines as caregivers (dropping the skeptical quotation marks, as Professor Turkle did during her encounter with Cog). At the same time, they may retain their religious worldviews and resist accepting the machines as persons. Will they feel authentically comforted, then, by machines programmed to display “artificial empathy”? Will they discover resolution of their conflict in the following conjecture by noted roboticist Hans Moravec?

So, it may be appropriate to say “God” has granted a soul to a machine when the machine is accepted as a real person by a wide human community. (Moravec 1999, 77)

Indeed, in perhaps the next ten years or so, how will people be using quotation marks to distinguish what they consider authentic from mere “make-believe”? Will they be describing new robot nurses as persons – or as “persons”? Will they decide that the machines care for people – or “care” for people? Will the artifacts be considered capable of moral behavior – or “moral” behavior? Will some older people still understand the granting of souls to be determined by God – or by “God”?

For some of us, these already are important questions.

Theodore Albert Metzler is the Director of Darrell W. Hughes Program for Religion and Science Dialogue, Oklahoma City University.

References

• American Honda Motor Co. Inc. 2010. “Asimo, The World’s Most Advanced Humanoid
• Robot.” Accessed December 21, 2010. http://asimo.honda.com/ .
• Babyboomercaretaker.com. 2007. “Robotics in Nursing.” Accessed January 4, 2011.
• http://www.babyboomercaretaker.com/assistive-technology/robotic-technology/Robotics-In-
• Nursing.html .
• Brooks, Rodney A. 2003. Flesh and Machines: How Robots Will Change Us. New York:
• Vintage Books.
• Buber, Martin. 1987. I and Thou. New York: Macmillan Publishing Company.
• Burnstein, Jeff. 2009. “Robotics and the Big Trends.” Robotics Online. Accessed January 3,
• 2011. http://www.robotics.org/content-detail.cfm/Industrial-Robotics-Feature-
• Article/Robotics-and-the-BigTrends/content_id/1709 .
• Fahad Inc. 2008. “REEM-B: UAE’s First ‘Home-Grown’ Humanoid Robot.” Accessed
• December 21, 2010. http://www.fahad.com/2008/06/reem-b-uaes-first-home-grown-
• humanoid.html .
• Foley, Mary Jo. 2009. “‘Partner bots: The next killer robotics app? (And will Microsoft bite?).”
• ZDNet. Accessed January 3, 2011. http://www.zdnet.com/blog/microsoft/partner-bots-the-
• next-killer-robotics-app-and-will-microsoft-bite/2828 .
• Friedman, Batya, Peter H. Kahn, Jr., and Jennifer Hagman. 2003. “Hardware Companions? –
• What Online AIBO Discussion Forums Reveal about the Human-Robotic Relationship.” CHI
• 2003. ACM. CHI Letters 5.1: 273-280. doi: 10.1145/642611.642660.
• Honda Robotics. 2011. “ASIMO.” Accessed January 3, 2011. http://dreams.honda.com/robotics-
• mobility/ .
• Impactlab.net. 2008. “Mahru II – South Korea’s Humanoid Robot.” Accessed December 21,
• 2010. http://www.impactlab.net/2008/10/14/mahru-ii-south-koreas-humanoid-robot/ .
• Moravec. Hans. 1999. Robot: Mere Machine to Transcendent Mind. New York: Oxford
• University Press.
• Nicks, Victoria. 2010. “History of Robots – Robotics Technology in Automata by Al-Jazari.”
• Suite101.com. Accessed December 10, 2010.
• http://www.suite101.com/content/history-of-robots-robotics-technology-in-automata-by-al-
• jazari-a253819 .
• Metzler, Ted, and Lundy Lewis. 2008. “Ethical Views, Religious Views, and Acceptance of
• Robotic Applications: A Pilot Study.” Technical Report WS-08-05. Menlo Park, CA: AAAI
• Press: 15-22.
• Mori, Masahiro. 1999. The Buddha in the Robot: A Robot Engineer’s Thoughts on Science and
• Religion. Tokyo: Kosei Publishing Co.
• Penrose, Roger. 1994. Shadows of the Mind: A Search for the Missing Science of Consciousness.
• New York: Oxford University Press.
• Polkinghorne, John. 1998. Belief in God in an Age of Science. Binghamton: Vail-Ballou Press.
• Tillich, Paul. 1971. Systematic Theology: Three volumes in one. Chicago: The University of
• Chicago Press.
• Today’s Zaman. 2010. “Meet SURALP, Turkey’s first humanoid robot.” Accessed December
• 21, 2010.
• http://www.todayszaman.com/news-224330-meet-suralp-turkeys-first-humanoid-robot.html .
• Zygbotics. 2009. “Robot Nurses to Care for Japanese Elderly within Five Years.” Accessed May
• 13, 2009. http://www.zygbotics.com/2009/03/27/robot-nurses-to-care-for-japanese-elderly-
• within-five-year/ .

Programs and documents on the computer are held in two areas: software and hardware. For scientists, one of many goals is to make the processors or chips, which are like the human brain that consists of nerves, much smaller, but still powerful enough to process many more calculations. There are many differences between the current chips and earlier ones. Chips which will be produced in the future will be smaller and probably process more calculations more quickly.

Programs, which can be seen as being the mechanical counterpart of the human mind, bring the above-mentioned improvements into daily life. New programs boost the capability of the computer in parallel with the capability of their chips. Without these programs, computers would be no more than ordinary electronic machines.

Developed technologies in fields like industry, communication, or the military bring us face to face with new developments and have made the computer an undeniable part of our lives. Mobile phones equipped with new features, medical machines which can easily make a large number of analyses and provide ease in diagnosis and treatment, robots that can operate with minimum error and have a low cost when used in production, and weapons that automatically focus on the target are all part of this progress.

With time, software and hi-tech sensors have enabled computers to communicate with people; there are now systems that are controlled by the voice, which are able to recognize a person from their iris or fingerprints, control systems which are carried out by touching a screen, etc. Such systems are operated with the help of special sensors or by some signals that carry messages from the person or the environment to the computer. The most important feature of these sensors is that the signals produced at the output are very weak and there are few differences between them. An ATM can recognize a particular person’s iris, thanks to the ability of its computer to compare the signals from the ATM’s iris scanner with previously recorded data. In this process, the computer uses the small differences that one person’s iris has to another’s. In this or similar systems, complicated programs are used, called “expert systems” or “artificial intelligence”. These programs imitate human senses, but they aim to operate with an even keener sensitivity and clearer criteria.

A question that is a subject of fiction comes to mind; “Will computers vie with or even fight with human beings?” In the mid-term, the rapid development of technology will create computers which can communicate with humans, which can understand them, and put forward ideas. A negative outcome of such a situation depends, once again, on man. Such a horrific situation could be the result of technology that can cause environmental disasters; this technology is almost identical to the one that we have described above. If we are able to establish an understanding of “civilization” which does not ignore human values for the sake of technological development, then such fears will be groundless.

Artificial Nervous Systems

As we all know, people have imitated nature in many of their inventions. In a way, artificial nervous systems imitate how a nerve cell learns and how it works. Fuzzy systems however imitate how the judgment of a human being works, rather than the nerve cells of the brain. In these systems people try to form a decision making criterion by assuming that there are endless grey tones between white and black or by assuming that there are infinite values between zero and one.

The purpose of the research on artificial nervous systems is to understand how the brain operates, then to make a system that imitates it and carries out the same operations. Artificial nervous systems are made of simple nerve cells which are bound in parallel, called process elements; these allow for real objects to be seen as if they were biological systems.

Here, the program that resembles the nerve cell operates in the same way as a nerve cell. The main part of a nerve cell is formed from the body, called a “soma”, an “axon” that is bound to the body and many “dendrites”. There are many “roots”, or synapses, on the dendrite of a cell which make contact with the dendrites of other cells. A nerve cell either transmits the electrical stimulus that comes through the axon to the other nerve cells through the synapse, or it does not transmit it, depending on whether or not the signal is over or below the threshold value. So a nerve works by itself, but its activity becomes meaningful when working as a part of a nervous system. It would be useful if we consider how the learning process occurs here. It is thought that the required data are stored in the memory center and this fact is taken as a model for some artificial nervous system software that has been successfully developed to date.

A nerve cell and the process of transporting signals from one cell to another can be written as software. It is clear that a natural nerve cell is more complex and that it is bound to more cells than an artificial one can be. The number of communication ports (synapses) of a natural nerve can vary from between 1,000 to 10,000.

An artificial cell produces output if the input value is over the cell’s threshold value; if this is not the case then there is no production. If there is output – as in natural cells – then this output is transported to the next cell group. Each cell produces its output as an input for the next cell.

A cell is separated into three groups: input, the hidden layer and output. Each group is considered to be made up of one layer, while the hidden layer can consist of more than one, according to the complexity of the job. As can be seen, the placement of the layers is similar in the process of the human body. We can compare the cells on the input layer with human senses. In this way we can teach a robot to avoid heat and cold, we can make them see and act according to this information. (Do not forget that a robot is in fact a computer.) It is natural that some sensors must be bound to the cells on the input layer. For instance, a sensor which is sensitive to heat can make the robot react to heat when the temperature is over the limit value or when the temperature is dramatically low it can move closer to a heat source. Or if pictures received from a video-camera are similar to an object that has been fed into the robot such data input can cause the robot to move to that object.

Artificial nervous systems are not only used in robot applications. They are commonly used in making clinical diagnoses, determining market-customer profiles, recognizing voices or pictures, classifications such as determining micro-structures, like germs and cell materials, economic profiles, energy sources, the futures of market shares, some predictive sciences, such as weather forecast, zipping data for computers, process control in industry, checking resources and some other matters in technological areas. As can be seen, there are many application areas for artificial nervous systems, all of which differ from one another.

The Basic Features of Artificial Nervous Systems

The features of artificial nervous systems can be simplified as follows: firstly, they can learn how to solve problems. In order to do this they use sample data and learning styles and while doing this they do not require any special help. Secondly, they can recognize important features and relations to help them distinguish different data forms.

When an artificial nervous system is operated, the first thing to be carried out is the training process. In order to do this, the program needs to have two alternating operations. It may obtain information concerning some results to be achieved, using results that come from the user, or the program is itself asked to produce some results. These two types of learning are not very different from how a human learns. One shows a young child an animal, and repeats the name. Now the child has learned the name of the animal and correlates it with the picture of the same. If no one teaches a child what a bird is, the child will all the same classify all animals that have wings and beaks and that have a certain physical shape, maybe even creating a name for the animal by him/herself. The difference between the computer and the human in this process is that a human has the ability to judge, while computers classify the animals according to their shapes and groups them thus. Naming and giving a naming feature to the computer is again a decision that a human will make. When the training process is finished, the data can be entered into the computer and the desired results can be attained.

Artificial nervous systems are changing and developing day by day. With each new development they become closer to the human nervous system; they are able to recognize different characteristics of different people and they are learning to make sorting decisions, even limited judgments. Whether or not these machines may one day enact a nightmare scenario, taking over from us is not a great threat, as whatever they are capable of doing is up to us to decide, as their “masters”. We should not fear these systems, but try to develop more of them; such systems help us in every day tasks, from drawing money out of the bank to our annual check-up at the doctor’s.

For every normal human being, there is awareness of himself and of a world outside. Through a learning process a child recognizes the existence of different types of colours and shapes around him. Example: there are some red apples which his mother has just washed and put on the table; he recognizes their likeness to the ball his father bought him to play with: the likeness is one of outward form, roundness and some degree of firmness or solidity. His sight and touch of the objects in question suffice for him to attain the general concepts of a colour called ‘red’ and a shape called ‘sphere’. But is there ‘red’ for a child who is blind? And if the blind child also has an impaired sense of touch, what is the meaning of ‘red’ or ‘round’ or ‘solid’? Few of us who do not ourselves suffer, or have direct contact with, such disability spend much time reflecting on its consequences for perception and understanding.

If the child in our example could understand what it means to be blind or to have impaired sense of touch, he would be inclined to ask: Is the red that I see inside or outside me? Is the roundness that I see and touch inside or outside me?

At school most of us are taught that a red apple is made of atoms which have neither the quality of redness nor of roundness. We are also learning from recent developments in studies of the brain that neither light nor sound reaches our brain: what the brain receives is certain electrical quantities produced by our eyes, ears or other senses. [1] It, the brain, then processes these electrical quantities into meaningful sense-impressions like colour and shape. If we stimulate the brain with an artificial electrical source, it soon becomes apparent that the brain cannot distinguish between a real or artificial stimulus. Using this technique we can make the brain ‘see’ wholly imaginary pictures which it processes and responds to as if they were wholly real. During brain surgery some patients can be excited by artificial impulses and ‘see’ quite unreal pictures (something like what we see in dreams) and even, having seen, giggle at them. To return to the child of whom we said, he sees red apples. What, in fact, does he see? What is the meaning of the reality of the red apples? Are they there outside him, or do his senses play a trick on him, or is the world presented to him in some other way?

Throughout history most scientists and philosophers have started from the assumption that space and time are absolutes, as defined by Aristotle [2] and formulized by Newton [3]. According to this assumption, the space we inhabit existed before us and will continue to exist after us, and time flows over and through it at a uniform rate. However, developments over the last hundred years, particularly Einstein’s relativity theory [4], have undermined that assumption. Time and space are not absolute; they exist with us, in part because we ourselves invest them with reality and meaning.

Now, with the latest developments in computer and multimedia technology, we are able to understand the relativity of time and space much better. We are able to make a human brain believe that it is experiencing the real world by exciting the five senses attached to it. The excitement to the brain is provided by a computer of the latest techniques of simulation and modelling can almost handle all five of our human senses. How is this done? And what are its implications?

It is done, essentially, by applying advanced forms of imaging familiar from 3D virtual reality games like DOOM and Heretic. In order to train F16 pilots, LCD-masks or helmets have been designed that show the pilot a three-dimensional picture of the aircraft such that, as he moves his head up and down, it feels to him as if he were really in the aircraft. With the addition of a perfect sound system and a seat that moves in sensitive accord to what is represented through the LCD-helmet, all the thrills and sensations of flying can be ‘experienced’ by the trainee pilot. [4,5]

A current PhD project in Manchester is experimenting with virtual reality imaging using a robot 40 miles away from the laboratory [6]. The robot’s ‘hand’ is equipped with sensors to read temperature, pressure and humidity. It is wired to send, via a fast communication net, the data it obtains to a glove worn by a technician/operator in the lab. The operator wearing the glove ‘feels’ what the robot ‘feels’. The system is communicative both ways: the operator can send commands to the robot and cause the robot ‘hand to move by moving the glove. Also, through two video cameras positioned in the robot’s ‘eyes’, the operator can see whatever the robot ‘sees’. So, when the operator wants to touch an object near the robot, he needs only to move the glove to the image of the object: this movement sends a command to the robot’s ‘hand’ which grabs the object. As before, the operator really feels the object as the robot-hand’s sensors pass on the relevant data in real time. Once the robot touched a hot object and the operator’s hand felt the burn.

This robot-hand, cameras and glove combination is being developed for medical applications. When the technique is perfected, it is hoped that a surgeon in Houston will be able to operate on a patient in St Mary’s Hospital in Manchester. In this research project there is a real robot obtaining and relaying data about a real patient or other real objects around the patient. The operator receives that data and the associated images and sensations thanks to a computer programme. But it is entirely possible for the computer programme to generate the data, images and sensations without reference to a real robot or real objects. In other words, if the computer sends to the glove temperature, pressure and humidity data (just as the robot ‘hand’ did), the operator wearing the glove will be none the wiser. He or she will operate as if there were a real robot at a certain location communicating real data through its real hand’. In fact, everything would be not real at all, but only ‘virtual’: the surgeon in Houston could thus be made to perform a life-saving operation in Manchester, to undergo all the tension and drama thereof, whereas in fact only a virtual life, not a real one, would be saved if the operation was successful.

In the Manchester research project, only the hand communicates a virtual world through the glove worn by the operator. Scientists are now studying the feasibility of extending the idea to a garment that would cover the whole body. Suppose that I put on such a garment, with the attached LCD-helmet and a perfect sound system, and go to a place (underwater, for example) where there is no gravitational force. Since every part of my body is covered by the garment, every part of it will feel the virtual world as generated and managed by the computer. For example, when the LCD-helmet shows me that there is a nail sticking up on the ground and I tread on it, the sensor worn under my foot will actually feel pain. I will start responding to and behaving in my virtual world as my helmet commands me to: any outsider seeing me underwater will think me crazy, as I will be making strange movements that make no sense. However, within the virtual world, all my movements are perfectly sensible and rational.

Let us now suppose two such garments. I wear one, and my friend the other. If the programmes running in our helmets communicate, we can speak to each other, even shake hands. Although I cannot really see my real friend underwater, I can, while wearing that special garment see him virtually, as my helmet shows him to me: the programme running in the helmet communicates to me what my friend is wearing and what he is saying and how, and the conditions and changes in our environment, etc. But the computer could also introduce me to other, imaginary friends in the helmet-run world. If it did so, it would not be easy for me to distinguish the real from the virtual beings. Actually, it would be impossible. Let us take the example further. Imagine a shepherd who is asleep on a mountainside near his flocks. Let us go to him and, without waking him up, dress him in that special garment. Then, let us simulate every person and object the shepherd has a relationship with in his real world of the sun, the mountains, his flocks, family, friends, and so on. Our programme starts by waking the shepherd up. When he wakes, he looks around and is seeing his flocks, the mountain side, the sun, etc. all virtually. Everything seems to him quite normal. In fact, of course, the flocks, the mountain-side, the sun, etc. have all been produced by our computer, the shepherd is nowhere near his flocks, he is in our underwater laboratory, wearing the special garment. And in that virtual world, he duly goes home, sees his virtual wife, and lives his life normally, as before. It is assumed that a normal brain stores at least 1018 bits and processes information at about 1015 bits per second [7].

This is how the shepherd”s brain can easily handle a time adjustment done by the programme running in the helmet. The shepherd, let us say, spends one our in the lab but thinks in his virtual world that he has lived a year. He truly believes he has aged whereas he has hardly been absent long enough for even his sheep to notice. We simply simulate a world for him, and if we do it well enough, he must think it real. He sees his sheep, touches them, smells the odour coming from them, hears them bleat, even tastes their milk — all virtually. He looks up and sees the sun simulated by the helmet and thinks it real. He sees the shadows of the trees shrink or lengthen and he thinks the sun makes them do so. As the programmers of the computer running in his helmet, we know that in fact the shadows of trees and the sun are drawn quite independently of each other, but the programme displays them according to the familiar cause-effect rules so that the shepherd will not be worried. Otherwise, if in designing the programme we had forgotten those familiar rules, if we had forgotten the sun-shadow relationship we are used to, the shepherd would start to think he was growing crazy, seeing trees without shadows, or shadows without trees, etc. Here, a particularly relevant Qur’anic verse (25.45) comes to mind: Have you not seen how your Lord spread the shadow — if He willed He could have made it still — thus We have made the sun its guide. The meaning of the verse is that as the sun rises towards midday, the shadow shrinks, then begins to lengthen again as the sun declines. Here, it leads us to affirm that the whole of our real world in all its complexity and fullness and actuality is created, not by itself, but by One hidden from it, outside of it and other than it.

As long as, in the shepherd”s virtual world, the virtual sun and the virtual shadows of trees are designed perfectly, the shepherd will believe that he is living in a real world. Of course we do not, perhaps cannot ever, design our simulation perfectly or completely — the shepherd”s body has its internal mechanisms and, to put it bluntly, the shepherd could not live very long on virtual food (the only kind we could supply him within the virtual world) even if we could make his brain believe that he had really eaten. If our shepherd said that the sun in his world created the shadows of the trees, causing them to shrink or lengthen, we would know for certain that the shepherd was wrong. Because we know that the trees and the sun are merely images drawn by our computer. The shepherd”s statement is as incorrect as if he had said the shadows created the sun or the mountians created his flocks of sheep. It is only the perfection of our designing into the programme the rules of light and shadow that lead the shepherd to believe that it is the sun that creates the shadow. We can make the shepherd understand the meaning of the light-and-shadow rules written into the programme by ordering the programme to stop generating shadows. Underwater, the shepherd has only the capability of willing. He can want something to happen or not happen according to the terms and within the limits of the computer programme. For example, if he wants to throw a stone at the mountain, he only wills it and the computer generates the necessary images and sensations: he thinks and feels as if he sees and picks up and then throws a stone.

Of course, he in fact only throws virtually: all he really does is to make some strange-looking movements underwater. Again, a verse of the Qur’an (8.17) comes to mind for its striking relevance to our discussion: You killed them not, but God killed them. And you threw them not when you did throw, but God threw — that He might test the believers by a fair trial from Him. Surely God is All-Hearing, All-Knowing. While the shepherd is still under the control of our programme, let us apply a test to him. Let us design a virtual person and send him into the shepherd”s virtual world with this mission: to explain to the shepherd that he is not really living his real life now but, instead, living a virtual life in a laboratory; that the programmer who designed the virtual world he is living in desires him to conduct his life according to certain rules — for example, the shepherd must not commit any crimes such as theft — and if he transgresses these rules, he will be punished directly there and then or, after the programme is stopped, at the discretion of the programmer. Clearly. it would be a major mistake on the shepherd”s part to deny the virtual messenger we have sent to him: if he denies the possibility of any such event as the whole programme terminating, or denies the existence of a programmer who could or would take him to task for transgressing the programmers rules, none could rescue the shepherd from any punishment we may decide for him. We may have powerful, irresistible guards obedient to our commands, ready to lay hold of the shepherd, should we command it. Or we might so amend the programme that the virtual sun will not rise on another virtual morning, and the shepherd is left in the darkness of a perpetual virtual night.

It is reasonable to imagine that, after the programme is shut down, we can explain and demonstrate to the shepherd that he has been living in a virtual world which we projected for him. Then, no doubt, he would accept that the virtual messenger we sent to him was telling him nothing except the truth, that, behind the virtual world that seemed so real to him, there really was a programmer with a will who could, at his choice, invite or compel the shepherd”s obedience. Finally, two verses from the Qur’an (6.71; 2.28) which show that our speculations on virtual reality have led us to the conclusion that our experiences of the reality of this real world are not so different from the shepherd”s in the virtual world underwater: Say: “Tell me, if God made night perpetual for you until the Day of Resurrection, who is a god beside God who could bring you light? Will you not then pay heed? How can you reject faith in God? Seeing that you were without life and He gave you life; then He will cause you to die and will bring you again to life; and to Him you will return?

References

1. The Brain Tumor Foundation of Canada. http://oncolink.upenn.edu/disease/brain/btfc/pchp3.html
2. Aristotle, METAPHYSICS, 350 BC, translated by W. D. Ross, http://paul.spu.edu/—hawk/aristotle.html
3. Isaac Newton, http://www-groups.dcs.st-and.ac.uk/–history/ Mathematicians/Newton.html
4. The Virtual Reality Store, http://www.thevrstore.com/ main.htm
5. Information about 3D-MAX, http://www.threed-max.udac.se/Info/infoindex.html
6. Kocak, Osman Ph.D Project, 1996, Salford University.
7. Adam, J. A., Bert Kasko., IEEE Spectrum, February 1996.

The word ‘robot’ was first used in the 1922 play R.U.R. by the Czech playwright Karel Capek: the title is an acronym for Rossum’s Universal Robots which become so sophisticated that they take over the world. ‘Robot’ is compounded from the Czech words ‘robota’ or work, and ‘robotnik’ or serf (Capek. 1923).

The use of industrial robots, first clearly identified in the 1960s, along with computer aided design (CAD) and computed aided manufacturing (CAM) systems, characterizes the latest trends in the automation of the manufacturing process (Roth, 1983). These technologies arc leading industrial automation through another transition, the scope of which is still unknown.

Growth of the robotics market has slowed compared to the early 1980s. The use of industrial robots is at present concentrated in rather simple, repetitive tasks which do not to require high precision. However, manufacturing market analysis predicts that early next century industrial robots will become increasingly viable in applications which require more precision and sensory sophistication such as assembly tasks. The automotive industry, where robots have been economically justified since the 1970s, will continue to be the leading user. However, the major growth of the US robot population will occur in non-automotive industries.

2. Robot classes and characteristics

Robots can be classified in many ways. To establish a generic classification system, we shall refer to dimensions or degrees of freedom or DOF.

The DOF of a mechanical system refers to the number of physical axes through which motion can occur. In robotics, DOF can often be equated with the number of joints in the robot.

Typical present-day industrial robots have from one to six-DOF, although more are certainly possible. For example, a wrist can be made more flexible by adding rotation to the twisting already in that joint. Similarly, a fourth DOF can be added to the shoulder, where the arm joins the base to allow additional rotation of the arm. Industrial robots are also classified by the mechanical configuration of the individual elements of the arm and actuators. Theses classifications are: rectangular class (X,Y,Z): cylindrical class (R,?,Z): spherical class (R,?,?); and jointed class (?1,?1,?). This classification begins with simple movements in a rectangular co-ordinate system such as the x-y co-ordinate system.

3. World’s robot population

More than 610.000 industrial robots are now at work according to a new annual publication by the secretariat of the United Nations Economic Commission for Europe (UN/ECE) and the International Federation of Robotics (IFR).

The world’s robot population grew by about 6% in 1993 compared with 8% the year before. These growth rates fall significantly short of those of 16-23% recorded in the booming late 1980s and early 1990s. However, in view of the deep recession which commenced at the end of 1990 in robot-using countries and resulted in large reductions in investment and industrial employment, growth in the robot stock of 6%-8% is still quite impressive. 

Japan accounts for more than half of the world robot stock. However, the net increase in Japanese robot stock fell sharply in both 1992 and 1993. In 1993, the net increase in the robot stock was only about a third of the record year 1990, underscoring the depth of the Japanese recession.

With 325 robots for every 10.000 persons employed in manufacturing, Japan has by far the world’s highest robot density followed by Singapore with 109, Sweden with 73, Italy with 70 and Germany with 62. As a result of falling employment in the manufacturing industry in 1992-1993, robot density increased rapidly in many countries even though the robot stock increased only modestly.

In most countries, welding is the predominant application area for robots, particularly for major motor vehicle producing countries, accounting for more than 20% of the total robot stock. In a few countries machining was the largest application area. Assembly was the largest application area in Japan, accounting for 40% of the total stock of robots. It is worth noting that in Japan assembly accounted for 50% of the net increase in stock while welding only had a share of 9%.After a solid recovery in 1994, the robot market is forecast to boom in the period up to 1998. Based on macroeconomics forecast of the development of world economics the UN/ECE and IFR forecast that the world stock of industrial robots will increase from some 610,000 units at the end of 1993 to over 830.000 units at the end of 1997. As the number of personnel employed in industry is falling, the density of robots measured as the number of robots per 10.000 workers will continue to surge. In terms of units, shipments are estimated to increase from about 54.000 units in 1993 to over 103,000 units in 1997.

While the robot market was expected to be somewhat hesitant in Japan in 1994 and 1995, it was expected to boom in the United States, Western Europe and the dynamic Asian economies. If growth and world trade gain momentum as predicted from 1995, the prospects for the robotics business seem extremely bright.

The potential for expansion of robotics is enormous. If other industrialized countries were to approach the robot densities of Japan and if industry in general were to reach only half the robot density of the motor vehicle sector, the robot stock would increase manifold, and this is not counting the potential for robots in the service industries. The following example gives an illustration of the potential: if industry in France and the United Kingdom were to achieve a robot density half that of the motor vehicle industry in those countries, the robot stock would more than double; if it reached half the density of the Japanese motor vehicle industry, the robot stock in those countries would increase more than 20 times.

4. Summary

The emphasis in this article has been on industrial robots and techniques currently used in that environment. The future of robotics depends on improvements in many technologies to reduce cost and increase the range of performance so that robots become effective in more environments. These technologies include motors, actuators, contact sensors, non contact sensors, mechanisms, lubrication, electronics, computers and artificial intelligence.

References 

• CAPEK. K. (1923) R.U.R.. Samuel French. London.
• ROTH. B. (1983) Principles of Automation, in Future Directions in Manufacturing Technology, based on the Unilever Research and Engineering Division Symposium held at Port Sunlight, April 1983. Unilever Research. UK