Application of AI in Robotics and its opportunities in India: Researches in BARC

Anup Sharma Third Year B.Sc. Student, Department of Computer Science. Vivekananda Education Society’s College of Arts, Science and Commerce. Chembur, Mumbai - 400071. India. Email:anups.mailme@gmail.com

Abstract - Artificial intelligence is a theory. The base object is the agent who is the "actor". It is realized in software. Robots are manufactured as hardware. The connection between those two is that the control of the robot is a software agent that reads data from the sensors decides what to do next and then directs the effectors to act in the physical world. The aim of this paper is to provide basic, background information on two emerging technologies: artificial intelligence (AI) and robotics and their scope in India. According to the Department of Trade and Industry (DTI), it is important to consider these emerging technologies now because their emergence on the market is anticipated to ‘affect almost every aspect of our lives’ during the coming decades (DTI, 2002). Thus, a first major feature of these two disciplines is product diversity. In addition, it is possible to characterize them as disruptive, enabling and interdisciplinary. Keywords- AI concept, robotics, software I. INTRODUCTION Many researchers now feel that the goal of mimicking the human ability to solve problems and achieve goals in the real world the so-called ‘strong AI’ is neither likely nor desirable because a long series of conceptual breakthroughs is required AI systems are generally embedded within larger systems-applications can be found in video games speech recognition, and in the ‘data mining’ business sector. The field of robotics is closely linked to that of AI, although definitional issues abound. ‘Giving AI motor capability’ seems a reasonable definition, but most people would not regard a cruise missile as a robot even though the navigation and control techniques draw heavily on robotics research. AI and robotics are likely to continue to creep into our lives without us really noticing. Unfortunately, many of

Mrunali Parab Third Year B.Sc. Student, Department of Computer Science. Vivekananda Education Society’s College of Arts, Science and Commerce. Chembur, Mumbai - 400071. India. Email:mrunal25_p@yahoo.co.in the applications appear to be taking place amongst agencies, particularly the military that do not readily respond to public concern, however well articulated or thought through. II. BASICS AI has been one of the most controversial domains of inquiry in computer science since it was first proposed in the 1950s. The ultimate aim is to make computer programs that are capable of solving problems and achieving goals in the world as well as humans Today, successful AI applications range from custom-built expert systems to mass produced software and consumer electronics. Robotics, on the other hand, may be thought of as ‘the science of extending human motor capabilities with machines’ (Trevelyan, 1999). However, a closer look at this definition creates a more complicated picture. For example, a cruise missile, although not intuitively referred to as a robot, nevertheless incorporates many of the navigation and control techniques explored in the context of mobile-robotics research. This report, however, considers robotics research as the attempt to instill intelligent software with some degree of motor capability. Since many of the major areas of AI research play an essential role in work on robots, robotics will be considered here as a sub-section of AI. Many of those in industry do not use the term ‘artificial intelligence’ even when their company’s products rely on some AI techniques. III. RESEARCH AREAS AI, based upon the capabilities of digital computers to manipulate symbols, is probably not sufficient to achieve anything resembling true intelligence. This is because symbolic AI systems, as they are known, are designed and programmed rather than trained or evolved. AI software designers are beginning to team up with cognitive psychologists and use cognitive science concepts. Another example centers upon the work of the ‘connectionists’ who draw attention to

computer architecture, arguing that the arrangement of most symbolic AI programmers is fundamentally incapable of exhibiting the essential characteristics of intelligence to any useful degree. As an alternative, connectionists aim to develop AI through artificial neural networks (ANNs). The emergence of ANNs reflects an underlying paradigm change within the AI research community and, as a result, such systems have undeniably received much attention of late. However, regardless of their success in creating interest, the fact remains that ANNs have not nearly been able to replace symbolic AI. AI researchers have a variety of learning methods at their disposal. However, as alluded to above,ANNs represent one of the most promising of these. There are many advantages of ANNs and advances in this field will increase their popularity. Their main value over symbolic AI systems lies in the fact that they are trained rather than programmed: they learn to evolve to their environment, beyond the care and attention of their creator (Hsuing, 2002). Other major advantages of ANNs lie in their ability to classify and recognize patterns and to handle abnormal input data, a characteristic very important for systems that handle a wide range of data. As a result, they are best used when the results of a model are more important than understanding how the model works. To this end, these systems are often used in stock market analysis, fingerprint identification, character recognition, speech recognition, and scientific analysis of data (Stottler Henke, 2002). The following chains of reasoning, considered in isolation without supporting argument, all exhibit the Fallacy of the Giant Cheesecake: • A sufficiently powerful Artificial Intelligence could overwhelm any human resistance and wipe out humanity. [And the AI would decide to do so.] Therefore we should not build AI. • A sufficiently powerful AI could develop new medical technologies capable of saving millions of human lives. [And the AI would decide to do so.] Therefore we should build AI. Once computers become cheap enough, the vast majority of jobs will be performable by Artificial Intelligence more easily than by humans. A sufficiently powerful AI would even be better than us at math, engineering, music, art, and all the other jobs we consider meaningful. [And the AI will decide to perform those jobs.] Thus after the invention of AI, humans will have nothing to do, and we'll starve or watch television. IV. ALGORITHMS AND GENETIC PROGRAMMING An algorithm is defined as a ‘detailed sequence of actions to perform to accomplish some task’. One branch of algorithm theory, genetic programming, is

currently receiving much attention. This is a technique for getting software to solve a task by ‘mating’ random programs and selecting the fittest in millions of generations. Khan elaborates: ‘Genetic algorithms use natural selection, mutating and crossbreeding within a pool of sub-optimal scenarios. Better solutions live and worse ones die – allowing the program to discover the best option without trying every possible combination along the way.’ V. APPLICATIONS. A. Intelligent simulation systems These applications are commonly used in a number of different scenarios. First, an Intelligent Simulation System (ISS) may be generated to learn more about the behavior of an original system, when the original system is not available for manipulation. The modeling of climate systems is a good example. Second, the original system may not be available because of cost or safety reasons, or it may not be built yet and the purpose of learning about it is to design it better. Third, an ISS might be employed for training purposes in anticipation of dangerous situations, when the cost of real-world training is prohibitive. Such technologies are particularly well advanced in military applications through the simulation of war ‘games’. Another very big business in the realm of ISSs is the videogame market, comparable to the film business in size. AI systems have become fundamental to this industry because, unlike in film, it is often up to a computer or game console to create a sense of reality for the game-player. Such standards of realism are going up all the time. B. Intelligent information resources Intelligent systems must be able to provide including visual and audio data, in addition to commonplace structured databases. One development in this area that is receiving much attention is ‘data mining’, the extraction of general regularities from online data. This area is becoming increasingly important due to the fact that all types of commercial and government institutions are now logging huge volumes of data and require the means to optimize the use of these vast resources. C. Sensors Sensors are the perceptual interface between robots. On the one hand we have passive sensors like cameras, which capture signals that are generated by other sources in the environment. On the other hand we have active sensors (for example sonar, radar, laser) which emit energy into the environment. This energy is reflected by objects in the environment. These reflections can then be used to gather the information needed. Generally active sensors provide

more information than passive sensors. But they also consume more power. This can lead to a problem on mobile robots which need to take their energy with them in batteries. We have three types of sensors (no matter whether sensors are active or passive). These are sensors that either record distances to objects or generate an entire image of the environment or measure a property of the robot itself. Many mobile robots make use of range finders, which measure distance to nearby objects. A common type is the sonar sensor. Alternatives to sonar include radar and laser. Some range sensors measure very short or very long distances. Close-range sensors are often tactile sensors such as whiskers, bump panels and touch-sensitive skin. The other extreme are long-range sensors like the Global Positioning System (GPS). The second important class of sensors is imaging sensors. These are cameras that provide images of the environment that can then be analyzed using computer vision and image recognition techniques. The third important class is proprioceptive sensors. These inform the robot of its own state. To measure the exact configuration of a robotic joint motors are often equipped with shaft decoders that count the revolution of motors in small increments. Another way of measuring the state of the robot is to use force and torque sensors. These are especially needed when the robot handles fragile objects or objects whose exact shape and location is unknown. Imagine a ton robot manipulator screwing in a light bulb. D. Effectors Effectors are the means by which robots manipulate the environment, move and change the shape of their bodies. To understand the ability of a robot to interact with the physical world we will use the abstract concept of a degree of freedom (DOF). We count one degree of freedom for each independent direction in which a robot, or one of its effectors can move. As an example lets contemplate a rigid robot like an autonomous underwater vehicle (AUV). It has six degrees of freedom, three for its (x;y;z) location in space and three for its angular orientation (also known as yaw, roll and pitch). These DOFs define the kinematic state of the robot. This can be extended with another dimension that gives the rate of change of each kinematic dimension. This is called dynamic state. Robots with non rigid bodies may have additional DOFs. For example a human wrist has three degrees of freedom – it can move up and down, side to side and can also rotate. Robot joints have 1, 2, or 3 degrees of freedom each. Six degrees of freedom are required to place an object, such as a hand, at a particular point in a particular orientation. The manipulator shown in Figure1 has exactly six degrees of freedom, created by five revolute joints (R) and one prismatic joint (P). Revolute joints

generate rotational motion while the prismatic joints generate sliding motion. If you take your arm as an example you will notice, that it has more than six degrees of freedom. If you put your hand on the table you still have the freedom to rotate your elbow. Manipulators which have more degrees of freedom than required to place an end effector to a target location are easier to control than robots having only the minimum number of DOFs. Mobile robots are somewhat special. The number of degrees of freedom does not need to have corresponding actuated elements. Think of a car. It can move forward or backward, and it can turn, giving it two DOFs. But if you describe the car’s kinematic configuration you will notice that it is three-dimensional. On a flat surface like a parking site you can maneuver your car to any (x;y) point, in any orientation. You see that the car has 3 effective DOFs but only 2 controllable DOFs. We say a robot is nonholonomic if it has more effective DOFs than controllable DOFs and holonomic if the two numbers are the same. Holonomic robots are easier to control than nonholonomic (think of parking a car: it would be much easier to be able to move the car sideways). But holonomic robots are mechanically more complex. Most manipulators and robot arms are holonomic and most mobile robots are nonholonomic. [1]

Computer science AI researchers have created many tools to solve the most difficult problems in computer science. Many of their inventions have been adopted by mainstream computer science and are no longer considered a part of AI. Finance Banks use artificial intelligence systems to organize operations, invest in stocks, and manage properties. In August 2001, robots beat humans in a simulated financial trading competition. Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation.

Heavy industry Robots have become common in many industries. They are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading. Japan is the leader in using and producing robots in the world. In 1999, 1,700,000 robots were in use worldwide. For more information, see survey about artificial intelligence in business.

Figure 1 Automobile Body designing using robotic

machinery Online and telephone customer service

Figure 2 An automated online assistant providing customer service on a web page. An automated online assistant providing customer service on a web page. Artificial intelligence is implemented in automated online assistants that can be seen as avatars on web pages. It can avail for enterprises to reduce their operating and training cost. A major underlying technology to such systems is natural language processing. Similar techniques may be used in answering machines of call centres, such as speech recognition software to allow computers to handle first level of customer support, text mining and natural language processing to allow better customer handling, agent training by automatic mining of best practices from past interactions, support automation and many other technologies to improve agent productivity and customer satisfaction.

Transportation Fuzzy logic controllers have been developed for automatic gearboxes in automobiles (the 2006 Audi TT, VW Toureg and VW Caravell feature the DSP transmission which utilizes Fuzzy logic, a number of

Škoda variants (Škoda Fabia) also currently include a Fuzzy Logic based controller).

Telecommunications Many telecommunications companies make use of heuristic search in the management of their workforces, for example BT Group has deployed heuristic search in a scheduling application that provides the work schedules of 20,000 engineers.

Toys and games The 1990s saw some of the first attempts to mass-produce domestically aimed types of basic Artificial Intelligence for education, or leisure. This prospered greatly with the Digital Revolution, and helped introduce people, especially children, to a life of dealing with various types of AI, specifically in the form of Tamagotchis and Giga Pets, the Internet (example: basic search engine interfaces are one simple form), and the first widely released robot, Furby. A mere year later an improved type of domestic robot was released in the form of Aibo, a robotic dog with intelligent features and autonomy. AI has also been applied to video games.

Music The evolution of music has always been affected by technology. With AI, scientists are trying to make the computer emulate the activities of the skillful musician. Composition, performance, music theory, sound processing are some of the major areas on which research in Music and Artificial Intelligence are focusing.

Aviation The Air Operations Division AOD, uses AI for the rule based expert systems. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries. The use of artificial intelligence in simulators is proving to be very useful for the AOD. Airplane simulators are using artificial intelligence in order to process the data taken from simulated flights. Other than simulated flying, there is also simulated aircraft warfare. The computers are able to come up with the best success scenarios in these situations. The computers can also create strategies based on the placement, size, speed, and strength of the forces and counter forces. Pilots may be given assistance in the air during combat by computers. The artificial intelligent programs can sort the information and provide the pilot with the best possible maneuvers, not to mention getting rid of certain maneuvers that would be impossible for a sentient being to perform. Multiple aircraft are needed to get good approximations for some calculations so computer simulated pilots are used to gather data. These computer simulated pilots are also

used to train future air traffic controllers. The system used by the AOD in order to measure performance was the Interactive Fault Diagnosis and Isolation System, or IFDIS. It is a rule based expert system put together by collecting information from TF-30 documents and the expert advice from mechanics that work on the TF-30. This system was designed to be used to for the development of the TF-30 for the RAAF F-111C. The performance system was also used to replace specialized workers. The system allowed the regular workers to communicate with the system and avoid mistakes, miscalculations, or having to speak to one of the specialized workers. The AOD also uses artificial intelligence in speech recognition software. The air traffic controllers are giving directions to the artificial pilots and the AOD wants to the pilots to respond to the ATC’s with simple responses. The programs that incorporate the speech software must be trained, which means they use neural networks. The program used, the Verbex 7000, is still a very early program that has plenty of room for improvement. The improvements are imperative because ATCs use very specific dialog and the software needs to be able to communicate correctly and promptly every time. The Artificial Intelligence supported Design of Aircraft, or AIDA, is used to help designers in the process of creating conceptual designs of aircraft. This program allows the designers to focus more on the design itself and less on the design process. The software also allows the user to focus less on the software tools. The AIDA uses rule based systems to compute its data. This is a diagram of the arrangement of the AIDA modules. Although simple, the program is proving effective.In 2003, NASA’s Dryden Flight Research Center, and many other companies, created software that could enable a damaged aircraft to continue flight until a safe landing zone can be reached. The software compensates for all the damaged components by relying on the undamaged components. The neural network used in the software proved to be effective and marked a triumphfor artificial intelligence. The Integrated Vehicle Health Management system, also used by NASA, on board an aircraft must process and interpret data taken from the various sensors on the aircraft. The system needs to be able to determine the structural integrity of the aircraft. The system also needs to implement protocols in case of any damage taken the vehicle.

Figure 3 An Aircraft that uses AI

News and publishing

The company Narrative Science makes computer generated news and reports commercially available, including summarizing team sporting events based on statistical data from the game. It also creates financial reports and real estate analyses.

Other Various tools of artificial intelligence are also being widely deployed in homeland security, speech and text recognition, data mining, and e-mail spam filtering. Applications are also being developed for gesture recognition (understanding of sign language by machines), individual voice recognition, global voice recognition (from a variety of people in a noisy room), facial expression recognition for interpretation of emotion and non verbal queues.

DEFENCE The apparent success of high technology

weaponry in the recent wars is indicative that the war is undergoing a profound transformation. The opportunities offered by these new or emerging technologies are boundless. There is a need to concentrate on those technologies that are important to the Indian Army for its modernization requirements.

The Indian Army remains committed to self-reliance through indigenous developmental efforts. Indian industry over a period has grown in strength and today has the financial capability and the potential to become a partner in defence research and production so that it leads to a self-reliant defence industrial and technological base for the country. An overview of Indian Army’s futuristic technology requirements are covered in the succeeding paragraphs. The requirements are dynamic in nature and this list needs to be viewed as an outline guide only. Artificial Intelligence (AI)

AI is an inescapable need for numerous military applications. Some possibilities are in the following areas:- (a) Imagery Interpretation. Image interpretation for target identification and classification. Artificial Intelligence techniques could automate the extraction of low-level map features from imagery. (b) Expert Systems. Expert systems for diagnosis and maintenance of sophisticated weapon systems such as radars and missiles. (c) Intelligent Evaluation of Kill Zone. Missile – target range and trajectory analysis for evaluation of kill zones and launch time and simulation to assist in qualifying missile performance in various environments.

Robotics Robotic applications for the Indian Army are as under:- (a)Robots can be used to assist troops in combat for tasks such as surveillance, reconnaissance, anti mine and anti IED role, urban area combat, casualty extraction etc. (b)Robotic equipment can be used to provide precision targeting support, carriage of ammunition and accuracy. Camera equipped and shock-resistant platforms to fire the guns remotely are possible applications. (c)Robotic vehicles equipped with cameras and weapons can be used to perform tasks such as limited / spot surveillance and reconnaissance etc. (d) Robotic Military Vehicles. These vehicles are required for a variety of high risk jobs such as mine / IED clearance, obstacle breaching and route opening. Man portable, light weight robotic systems would be required for reconnaissance, surveillance and target acquisition missions for sub-terrain/ urban operations. Robotic vehicles are also needed for mine detection/clearing, obstacles breaching, clearing wire obstacles, placing explosives, tactical deception, direct fire and communication relay. [2]

[10]

Figure 4 Kitano’s PINO – “The humanoid robot”

MEDICINE Medical schools in India produce the largest

number of doctors than anywhere else in the world, corresponding to the rapid proliferation of medical colleges in the last two decades, especially within the private sector. WHO has reported that by 2015, 36% of the medical manpower is going to be produced by India.

Over the last few years there has been increasing interest and activities in medical education reflecting the underlying needs and desire to improve. The enthusiasm and momentum generated among the medical educators need to be sustained and supported to bring about meaningful reforms in medical education. Expenses incurred by the Indian government on healthcare are the highest amongst developing countries. India’s expense on healthcare sector comprises 5.25% of the GDP.

The introduction of practical surgical robotic devices has opened a new perspective on minimal access surgery in all surgical endeavours. In recent years, robot-assisted surgeries have become the preferred approach in developed countries such as the United States and the United Kingdom, have attracted considerable attention in many other parts of the world. There are about 1171 da Vinci surgical systems installed worldwide, including 863 in the United States and in Europe3.

Figure 5 Robot assisted medical checkup in case of non-availability of Doctor

By handling control of surgical instruments

through robots and positioning Surgeons at comfortable console with 3D or high resolution display at up to 20 times magnification, surgery of vital organs can be accomplished with precision and accuracy, minimizing damage to tissues or loss of blood. Robotic wrists provide much more freedom of movement and articulated motion inside the abdominal cavity. Computer interfacing allows for

remote control surgery, for precise manipulations by downscaling the surgeon’s motions. Surgeons around the world are using sophisticated robots to perform surgical procedures. The da Vinci surgical system was released in April 1997 and received FDA approval in 2000 for laparoscopic surgeries. Robotic technology provides fundamental advantages to the operating Surgeon, particularly for those who are trained in laparoscopy. Robotic surgery is an evolution of traditional laparoscopy with a special tool offering the surgeon more mobile instruments and better vision. With increased experience, more and more indications will be performed robotically, with significant benefit for our patients. Because of the advantages (significantly less pain, less blood loss, fewer complications, less scarring, a shorter hospital stay and a faster return to normal daily activities), robotics is here to stay. The present principal drawback remains the cost (a daVinci Robot costs Rs 8 crores). The acquisition of robots in India has been started by government initiative with two installations at the All India Institute of Medical Sciences, New Delhi, but is yet to enter the mainstream. In Bangalore there are about 120 urologists; among them only 3–5 urologists do an advanced laparoscopy In USA, there are 17,000 urologists for 300 million people and in Brazil, 4000 urologists for 200 million people. However, in India only 2500 urologists for 1 billion people. There is an increased work load on urologists in India. Comparison of the number of urologists versus robotic facilities in different countries in Asia clearly shows India is lagging behind.

There is also an advantage in surgical learning curve with the robots over open or laparoscopic surgeries. We need to do 100 cases to be proficient in open surgery and 50 cases to be proficient in conventional Laparoscopy. However, for robot-assisted Laparoscopy 12 cases are needed to be proficient.[3]

Figure 6 A laparoscopic robotic surgery machine

AUTOMOBILE INDUSTRY Artificial Intelligence till date was ‘foreign’ to Indians. The imagination of a car alerting the driver when the tyres are low on pressure or about the traffic block ahead can now be seen coming true. Automotive Research Association of India (ARAI) is getting ready to put an Indian label to it. ARAI is currently working on AI-based Engine Control Unit (ECU) – something that will provide more safety on Indian roads. The use of AI-driven systems comes in handy for a driver with regard to security such as averting a accident or reducing impact of an accident. ECUs with specific functions can be set up and can address security concerns of the drivers and passengers. [8]

COMMUNICATION INDUSTRY IBM has reportedly started a worldwide initiative to develop artificially intelligent mobile interfaces, which could collect data based on user behavior and skill level. Considering the huge scope for mobile market growth in India, IBM has decided to start the pilot project at the India Research Lab with a budget of $100 million and a time span of 5 years. The pilot project is reportedly part of the 60 to 80 research projects targeted on the mobile platform, proposed to be launched globally. Apparently the rapidly growing Indian market, at the rate of 10 million users every few months and the innovative research breakthrough from the local service centres, has provided a major boost in choosing India Research Lab for the pilot project. The AI programs proposed for future mobile interfaces find their applications in understanding user behavior, monitoring the statistics of usage and determining the popularity of an advertisement by measuring the number of clicks, apart from assisting investors in making the right decisions and tracking fraudulent transactions. If all the pieces of this massive project fall in place, it could mean the revolution of mobile computing, originating in India. [6]

BEGINNING OF RESEARCH WORK IN AI AND

ROBOTICS IN INDIA

Work in Artificial Intelligence began in India in the early 1980's. The Management Information Systems (MIS) Group at the Indian Institute of Management, Calcutta has been actively involved in Artificial Intelligence (AI) research since the early 1980s. The AI work in India got a significant boost with the UNDP funded Knowledge Based Computing Systems (KBCS) project. This project started in November 1986 with a view to building institutional infrastructure, keeping abreast of the state-of-the-art

technology, training scientific manpower and undertaking R&D in certain specific socio-economic areas that are amenable to this technology. The project has been highly successful in spreading research and application of different techniques of Artificial Intelligence to not only most Universities and research institutes in India but also across large sections of India's very successful software industry. Under the umbrella of the Computer Society of India (CSI), India's national body of IT professionals, a Special Interest Group in AI (SIGAI) has been formed recently, to consolidate the AI activities going on in the country. It will provide a forum for the interaction amongst the researchers. The SIGAI of India will link to SIGAI of ACM and do similar kind of functioning within the country. The activities of SIGAI are envisaged to be: Publication of newsletters, organizing an annual meet of Indian research scholars working in AI related areas, providing support for members to attend conferences, giving grants to prospective authors of AI related books, Supporting high quality AI conferences in the country. A number of organizations are involved in active AI research in India: Indian Institute of Technology, Chennai Indian Institute of Technology, Delhi Indian Institute of Technology, Kanpur Indian Institute of Technology, Kharagpur Indian Institute of Technology, Mumbai Indian Institute of Science, Bangalore Indian Institute of Management, Kolkata Indian Statistical Institute, Kolkata Tata Institute of Fundamental Research, Mumbai National Centre for Software Technology, Mumbai International Institute of Information Technology, Hyderabad Central Electronics Engineering Research Institute (CEERI), Pilani University of Hyderabad HP Labs India IBM India Research Lab(IRL) Tata Infotech, Mumbai Tata Research Development & Design Centre, Pune CSI Special Interest Group in Artificial Intelligence (CSI-SIGAI) Technology Development in Indian Languages (TDIL).[7]

RESEARCH WORK BY CENTRE FOR ARTFICIAL INTELLIGENCE AND ROBOTICS

The Centre for Artificial Intelligence and Robotics (CAIR) is a laboratory of the Defence Research & Development Organization (DRDO). Located in Bangalore, Karnataka, involved in

the Research & Development of high quality Secure Communication, Command and Control, and Intelligent Systems. CAIR is the primary laboratory for R&D in different areas of Defence Information and Communication Technology (ICT).CAIR, established in October 1986,had its research focus, initially in the areas of Artificial Intelligence (AI), Robotics, and Control systems. In November 2000, R&D groups working in the areas of Command, Control, Communications & Intelligence(C3I) systems, Communication and Networking, and communication secrecy in Electronics and Radar Development Establishment (LRDE) were merged with CAIR. CAIR, which was operating from different campuses across Bangalore has now moved to a new unified sprawling campus.

AI and Neural Networks

CAIR is currently developing a number of Data Mining tools using Artificial Intelligence & Neural Networks and is building software libraries to create a Data miner’s toolbox.

Semantic Web is a new paradigm proposed to make the World Wide Web (WWW) more machine tractable so as to establish a foundation for Agent based technologies. The large amount of information contained in languages used by humans necessitate development of technologies to process the information automatically. Human language processing technologies are being implemented using Commercial off- the- shelf (COTS) computers with huge memories and high processing speeds. CAIR has so far been developing technologies for processing human language inputs namely, information extraction, shallow Natural Language Processing (NLP), Semantic Web tools and techniques, and Semantic Web as a knowledge representation structure for human languages. Decision Support System Shell architecture named AADARSHA that makes use of Object Oriented concepts has been developed by CAIR. It meets several objectives such as lean and thin shell for easy maintenance, universal interface, easy incorporation of new algorithms into inference engine etc.

Robotics

CAIR has developed a variety of controllers and manipulators for Gantry, SCARA and other types of robots. These were supplied to Public Sector Units such as HAL and sister DRDO labs. CAIR has gone on to develop a prototype Unmanned Ground Vehicle (UGV) with the aim of attaining autonomous

capability. This involved in-house construction of mobile robot platforms, integration of infrared sensors with the vehicle, and the development and integration of path planning software. An useful offshoot of this work was the development of an intelligent wheelchair that would help physically challenged people both in hospitals and homes. One version of the wheelchair could be operated using human voice commands. Another was equipped with a camera system to get information about the surrounding space for its path planning. Other robots developed by CAIR are for Non-destructive testing, Ammunition loading, and Hot slug manipulation. Both wheeled and legged miniature mobile robots have been developed.[5]

RESEARCH WORK BY BHABHA ATOMIC RESEARCH CENTRE,MUMBAI Brief description of at most three projects that were in progress in 2006: 1. Laser based Mobile Robot Navigation & Mapping: BARC wishes to develop software for mapbuilding and localization over a wide (40m x 40m) indoor area with the help of range data from Laser Range Finder. We have in the past developed such software for use in smaller areas. The effort is directed to make the software highly reliable for use in industrial setup as a pose sensor. 2. Mobile robot navigation in outdoor environment with 3D laser range finder and panoramic camera. They were busy building the robot. The task of navigation in outdoor environment is very complex because of the fact that the planes of the sensors keep changing continuously. But they are interested in this area as it is of utmost importance in many real applications of deployment of mobile robots. 3. Force sensing and control in robot manipulation: This is again a very important area for autonomous handling of objects by robots. They planned to buy a robot arm, integrate it with Force/Torque sensor and gripper and write controller programs for force sensing and control. Most recent 3-5 publications: 1. "Sonar-based mobile robot navigation through supervised learning on a neural net", Autonomous Robots 3, pp. 355-374, 1996. 2. "Gait Optimization through Search", The International Journal of Robotics Research, Vol.19, No.4, April 2000, pp. 394-408. 3. "Sensor based mobile robot navigation through curvature activation and context switching", National Conference on Advanced Manufacturing & Robotics, Durgapur, Jan 15-16, 2004. Some significant past projects executed:

1. Development of a motion planner for an in-house 4-axes robot (1991-93) 2. Robot learning of obstacle avoidance and goal following behavior using recurrent neural net (1994-96) 3. Development of a mobile robot and its navigation software for simultaneous localization and mapping (SLAM) (2002-2005)[4]

Mobile robots, following markers or wires

in the floor, or using vision or lasers, are used to transport goods around large facilities, such as warehouses, container ports, or hospitals. The Bhabha Atomic Research Centre has developed an Automated Guided Vehicle (AGV) for transportation of materials within the factory. Based on robotic science, BARC developed this at the request of Bajaj Auto for its manufacturing set-up. BARC has developed this at one-sixth the cost of the imported machine. The imported machine costs around Rs three crore while the BARC-developed AMTS would cost Rs 50 lakh. Automated loading and unloading operations are performed by programmed motion of powered roller conveyors onboard the AGV, and on corresponding stationary unit. The system is remotely controlled from a control room, and the possible routes for the AGV along with nominal speeds and stoppages can be specified in advance. Bajaj Auto gave the assignment to BARC in 2007. A demonstration was given to the Pune-based company last year and further finer requirements are being worked out. Earlier, in 2005, BARC had successfully developed a robotic system for Ordnance Factory in Jabalpur for remote defusing of explosives. BARC is also planning to put together customised AMTS for handling nuclear fuels in Nuclear Fuel Complexes (NFCs) remotely. At an upcoming NFC complex in Rajasthan, it would be incorporated. This would also be useful for handling radioactive sources at the Board of Radioactive and Isotope Technology (BRIT)at Vashi.[9] VI. ROBOTICS A distinction has already been drawn above between robots working in informational environments and robots with physical abilities. One advantage of the former is that there is little need for investment in additional expensive or unreliable robotic hard ware as existing computer systems and networks provide adequate sensor and effector environments. On the other hand, the kinds of robotics systems elaborated on here, physical robots, require mechanization of various physical sensory and motor abilities (Doyle and Dean, 1996). The challenges involved in

providing such a latter environment are considerable, especially when complete automation is sought, as in Honda’s humanoid ASIMO project. Thus, rather than focus on the ambitious and distant goal of relative autonomy, this report picks up on Trevelyan (1999) who points out that complete automation is often unfeasible, impossible, or simply unwanted. Indeed, much of today’s robotics research focuses instead on far humbler goals, such as simplicity, force control, calibration and accuracy. Thus, we can see that, to some extent, the field of robotics has followed similar lines as that of AI, attempting to rebound from the overly optimistic predictions of the 1950s and 1960s, and coming up against more contemporary problems not dissimilar to the AI effect .Indeed, while few of the innovations that emerge from the work of robotics researchers ever appear in the form of robots, or even parts of robots, their results are widely applied in industrial machines not defined as so (Trevelyan, 1999). In spite of these significant challenges, there are some good examples of AI-controlled robotic systems. For instance, Tri Path Imaging has built Focal Point, a diagnosis expert system that examines Pap smears for signs of cervical cancer. Focal Point screens five million slides each year, or about 10% of all slides taken in the US and, like human lab technicians in training, teaches itself by practicing on slides that pathologists have already diagnosed. Thus, one big advantage of such a system is that, if implemented properly, Focal Point allows you to replicate your very best people. A second example and, again, perhaps the most ambitious of all, concerns DARPA, who are in the process of developing an Unmanned Combat Air Vehicle (UCAV). According to Boeing (2002), the UCAV system I designed to ‘prove the technical feasibility of multiple UCAVs autonomously performing extremely dangerous and high priority combat missions.’ In a typical mission scenario, ‘multiple UCAVs will be equipped with preprogrammed objectives and preliminary targeting information from ground-based mission planners. Operations can then be carried out autonomously, but can also be revised en route by UCAV controllers should new objectives dictate.’ If the program is a success, the US DoD expects to begin fielding UCAV weapon systems in the 2008 time-frame. A. Types of Robots (used now a days) 1) Hard working Robots Traditionally robots have been used to replace human workers in areas of difficult labor, which is structured enough for automation, like assembly line work in the automobile industry (the classical example) or harvesting machines in the agricultural sector. Some existing examples apart from the assembly robot are:

Melon harvester robot

Ore transport robot for mines A robot that removes paint from large ships A robot that generates high precision sewer maps

If employed in a suitable environment robot can work faster, cheaper and more precise than humans. 2) Transporters Although most autonomous transport robots still need environmental modifications to find their way they are already widely in use. But building a robot which can navigate using natural landmarks is probably no more science fiction. Examples of currently available transporters are:

Container transporters used to load and unload cargo ships

Medication and food transport systems in hospitals

Autonomous helicopters, to deliver goods to remote areas. 3) Insensible Steel Giants As robots can be easily shielded against hazardous environments and are somewhat replaceable, they are used in dangerous, toxic or nuclear environments. Some places robots have helped cleaning up a mess:

In Chernobyl robots have helped to clean up nuclear waste

Robots have entered dangerous areas in the remains of the WTC

Robots are used to clean ammunition and mines all around the world For the same reasons robots are sent to Mars and into the depth of the oceans. They explore sunken ships or walk the craters of active volcanoes. 4) Servants and Toys Robots may not yet be a common sight in our world, but we already encounter them in many places. Many modern toys like the Sony Aibo are conquering today’s children’s life. Robots are developed that will help older people to have a better and more secure life. Nowadays, they start to come to us as toys or household helpers. Their time has just begun. VII. OBSTACLES IN AI The standard test against which the possibility of strongAI is often judged concerns Alan Turing’s 1950 article, Computing Machinery and Intelligence, in which the author discusses the conditions for considering a machine to be intelligent. He argues that if a machine could successfully pretend to be human to a knowledgeable observer then you certainly should consider it intelligent. This test would satisfy most people but not all philosophers, some of which have challenged the ‘inevitable’ achievement of strong AI based upon the assertion that the hypothesis of strong AI is itself false. One famous sceptic of AI is Hubert Dreyfus, who says that a computer will never be intelligent unless it can

display a good command of common-sense. Dreyfus then follows up by saying that computers will never be able to fully grasp common-sense, since much of our commonsense is on a ‘know-how’ basis. For example, the notion that one solid cannot easily penetrate another is commonsense, yet the knowledge required to ride a bicycle is not something you can gain from a book, or from someone telling you. You can only learn through experience. Thus, since current computers can only really ‘represent’ things, the possibility of taking a skill, emotion, or something else equally abstract, and changing it into a series of zeros and ones is according to Dreyfus, close to impossible. A second famous doubter is John Searle, who, with his Chinese Room analogy, has responded directly to Turing. VIII. FUTURE OF AI In spite of the many fundamental barriers highlighted above, the fields of AI and robotics are replete with many wonderfully inventive predictions, a domain where reality and science fiction often meet. Indeed, it is likely that in the next two decades we’ll see more and better capabilities that we tend to attribute as awareness. However, it is unlikely that machines will ever have human awareness in the philosophical sense of the term, although they may come close in the long term. Rather, we can expect to see classical AI going on to produce more and more sophisticated applications in restricted domains, such as expert systems, chess programs and Internet agents. At the same time, the next 30 years will produce new types of animal-inspired machines that are more ‘messy’ and unpredictable than any we have seen before – less rationally intelligent but more rounded and whole. IX. AI AND ROBOT COMBINATIONS Many of the major ethical issues surrounding AI - related development hinge upon the being voiced based upon the workability of such a system. This is because, while testing may be possible for an autonomous tank and other weapons of the electronic battlefield, it is not feasible for National Missile Defense. Such a system can only be realistically evaluated in actual combat (Augarten, 1986). More fundamentally, significant moral difficulties arise out of human distaste for autonomous weapons. Gary Chapman (2000) summarizes this concern well. X. ROBOT SUPERIOR THAN MACHINE Such issues of predatory machines are bound to raise concern over the scenario of AIs overtaking humankind and thus somehow competing with him. This idea has often been popularized by classic science fiction works and populist academics, such as

Professor Kevin Warwick, Professor of Cybernetics at the University of Reading, UK, who has repeated this beliefs concerning robot ‘take-over’ on many occasions in the press, in his books, and on television and radio. Consider the following letter from Nicholas Albery (1999) of the Institute of Social Inventions. Published in New Scientist and entitled Robot Terror, Albery seeks support for the following petition: The strong public reaction to machine takeover appears, then, not to be well founded. However, if it is possible to agree, for argument's sake, that humankind will be able to create a truly intelligent machine, a much deeper issue arises: how will a sentient artificial being be received by humankind and by society? ‘Would it be forced to exist like its automaton predecessors who have effectively been our slaves, or would it enjoy the same rights as the humans who created it, simply because of its intellect?’ This is an enormous question that touches religion, politics and law, but to date little serious discussion has been given to the possibility of a new intelligent species and to the rights an autonomous sentient might claim. XI. CONCLUSION This paper began by stressing the need to provide background information on AI. In doing so, it was hoped that the prospects of these emerging technologies to affect quality of life in the coming decades could be realistically assessed. One consequence of providing such an overview is that there can be no decisive conclusions as such; the industries characterized here are too dynamic and uncertain to generate any real sense of resolution. However, it is possible to highlight a number of important differences and similarities between robotics and AI which go some way to shedding more light on their character. Perhaps the greatest contrast between the two industries concerns public interest. Indeed, as this paper has demonstrated, robotics is widely regarded as a ‘new’ and exciting branch of science and technology. AI, on the other hand, is viewed by many as a highly specialized and unproven discipline. One reason for this concerns the gross over-optimism that characterized the industry in the 1960s and 1980s. Another reason reflects the AI community’s seemingly insurmountable difficulty in publicizing its own achievements without whipping up general anxiety over machine superiority. The upshot of all this has been the field’s struggle to attract funding in the past and it is likely that this trend will continue for some time into the foreseeable future. Revealing similarities also exist between robotics and AI. There has been much talk recently regarding the convergence of traditionally

separate scientific fields, in particular the blurring of the boundaries between the physical sciences and life sciences – perhaps even the first step towards the long sought after unification of physics, chemistry and biology. For example, the concourse of nanoscience, biotechnology, IT, and cognitive science (‘NBIC’) was discussed during a December 2001 NSF workshop. NBIC, it was agreed ‘could achieve a tremendous improvement in human abilities, societal outcomes, the nation’s productivity and the quality of life’. In some ways, the above conclusion is hardly surprising given the ambitious and broad scope of the technologies discussed in this paper. As pointed out above, ‘convergence’ largely arises from the wide availability of techniques and tools on offer today – the real innovation stems from the process of bringing individuals from traditionally separate disciplines together. [1] Robotic technology will definitely grow and encompass a huge range of surgical procedures, particularly in urology. India should not ignore the robotic revolution and should wholeheartedly imbibe the future generation of technological expertise. Robotic surgery has come to stay and will make slow but steady inroads into Indian healthcare delivery system. Health is a human right, which has also been accepted in the Constitution. Its accessibility and affordability has to be insured. According to the recent reports, the health sector in India has become a Rs 25,000 crore industry. Indian can afford this technology restricted access for many patients. To improve healthcare delivery system to promote medical tourism and medical education, India should invest on robots. [3]

There is tremendous scope for industry to participate in the development and production of systems and technologies for the Indian Army. Barring a few major PSUs and some private industries, most Indian industries engaged in

production of defence equipment have limited R & D infrastructure and spend little on R & D. There is, therefore, an urgent need for Indian Industry to develop a vibrant defence R & D and production capability to meet requirements of the Indian Army. The participation of the Indian Industry in themodernisation, collaborative research and development and equipping of the Indian Army will provide improved capability and also boost the Indian economy. [2] ACKNOWLEDGEMENT Mrs. Madhavi Vaidya Professor, Department of Computer Science, Vivekananda Education Society’s College of Arts, Science and Commerce, Chembur, Mumbai. REFERENCES [1]http://www.ipedr.net/vol6/22-A10017.pdf [2]http://www.ciidefence.com/pdf/Future_Technology_Requirements_of_the%20Indian_Army.pdf [3]http://www.ias.ac.in/currsci/25jun2010/1553.pdf [4]http://sigai.cdacmumbai.in/files/AI_India_compilation.pdf [5]http://drdo.gov.in/drdo/labs/CAIR/English/index.jsp?pg=achieve.jsp [6]http://www.thinkdigit.com/Mobiles-PDAs/IBM-to-build-AI-mobile-interfaces-at_5191.html Posted on: Aug 09, 2010 18:45:43 IST [7]http://www.managementparadise.com/forums/articles/6846-ai-artificial-intelligence-india.html [8]http://www.indianexpress.com/news/now-artificial-intelligence-made-in-india/412129/ Posted: Sun Jan 18 2009, 02:02 hrs [9]http://post.jagran.com/barc-develops-roboticsbased-automated-vehicle-for-industry-1316008078 [10]http://science.howstuffworks.com/robot6.htm