INTELLIGENT SYSTEMS AND ROBOTICS

ABSTRACT

The present paper attempts to deal with intelligent systems and Robotics in the present

context of activities handled by various departments in the globe. Intelligence system is a

system which acts according to its set objective. The advantages of studying an IS

include self-preservation, accuracy and copying action of others. For an IS to work

properly it should have the capability of communicating with environment and a set

objective and it consumes energy for internal actions. Artificial Intelligence is a branch of

science and technology to develop machines that are intelligent. The applications of AI

include natural language processing, pattern recognition, robotics and expert systems.

Robotics is design and manufacture of intelligent machines that are programmed to

perform certain tasks. Robots are used in industries to increase productivity and handle

jobs that are too dangerous for humans. Their construction is not simple. In reality robots

are built in a complex way. They are made of a controller which acts as the brain of a

computer, an arm which resembles the human arm is designed according to the

application, the drive which drives the robot to do a certain task, an end-effector which

attaches the hand to the arm and a sensor which provides a limited feedback to the robot.

The robotic architecture is mainly based on the microcontrollers. The use of integrated

microcontrollers is gained a lot of importance because of its reliability at a low cost. The

microcontroller forms the heart of the embedded system that forms the brain of the

majority of robots. Robotics is used for industrial automation to the extent that the terms

‘robotics and industrial automation’ have become synonyms in the industrial world.

Use of highly integrated Microcontrollers allows development of distributed intelligence

systems. Motion control on a robot is accomplished by components, software enabled

components and integrated solutions.

Androids are the anthropomorphic robots (i.e robots that look more like humans) need a

special mention because of the wide range of their utilities, and their ability to replace

humans & thus help in automation. In real world, robots are redefining manufacturing,

medicine, exploration and consumer electronics. Robotics has the potential to change our

economy, health, standard of living, knowledge and above all the world we live in.

INTELLIGENT SYSTEMS AND ROBOTICS

INTELLIGENT SYSTEMS – SOME CONCEPTSThere are many definitions of intelligence. A person who learns fast or one who has a

vast amount of experience could be called "intelligent". However for our purposes the

most useful definition is:

Intelligence is the system’s comparative level of performance in reaching its

objectives. This implies having experiences where the system learned which actions

best let it reach its objectives.

Similarly a system is “a part of the universe (with a limited extension in space

and time) with stronger and more correlations exist between one part and the

other”.

What is an Intelligent System (IS): An intelligent system learns how

to act so that it can reach its objectives. The intelligent system continually records the

present situation and the action that follows as a response rule. It is a system that learns,

for each situation, which response permits it to reach its objective during its existence. It

continually acts, mentally, externally and by acting reaches its objectives more often than

pure chance would indicate. For acting, and for its internal processes, it consumes energy.

For this definition examples of an intelligent system would be: Humans, animals etc.

Advantages of IS: An IS will greatly benefit from a few of the most basic

instincts, which are normally:

Self-preservation (survival) by avoiding damage to the body or mind.

Curiosity, to promote the opportunity for learning and thus accelerate it.

Copying of actions done by other intelligent system

An overview of the Intelligent System:

The following figure depicts the various functions of an intelligent system:

IS is an existing system which interacts with the environment.

The IS has to have an objective, it has to be able to check if its last action was

favorable, if it resulted in getting nearer to its objective, or not.

To reach its objective it has to select its response. A simple way to select a

response is to select one that was favorable in a similar previous situation.

It must be able to receive communications from the environment, for its

elaboration of the present situation. By communications, in turn, we mean an

interchange of matter or energy. If this communication is for the purpose of

transmitting information, it is a variation of the flow of energy or a specific

structuring of matter that the system perceives.

It consumes energy in order to act and for its internal processes.

Since the same response sometimes is favorable and sometimes fails, it has to be able

to recall in which situation the response was favorable, and in which it was not.

Therefore it stores situations, responses, and results.

Finally, it must be able to act; to accomplish the selected response.

Critical elements that distinguish Intelligent Systems are:

Recognition, Feedback, Correction, Learning, Warning and Adaptation.

Artificial Intelligence (AI) It is a branch of science and technology to develop machines that are

intelligent. The current goal of AI is to develop machines that are able to think, hear,

talk, read, walk, and feel. According to Herbert A.Simon, professor of computer science

“AI is the capacity of a digital computer or computer-controlled robot device

to perform tasks commonly associated with the higher intellectual processes

characteristic of humans, such as the ability to reason, discover meaning,

generalize, or learn from past experience’.

Examples for artificial   intelligent systems are artificial insects and mobile autonomous

systems.

Applications of artificial intelligence: Natural language processing.

Pattern recognition.

Robotics.

Expert system.

RoboticsRobotics is one of the important applications of AI and is defined as the technology of

building and using robots with artificial intelligence and computer controlled human-like

capabilities. Robotics is design and manufacture of intelligent machines that

are programmed to perform certain specific tasks. Robots are generally designed

to be a helping hand. They help us in difficult, unsafe or boring tasks. Simply put, robots

are machines that can be programmed to perform a variety of jobs, and they can range

from simple machines to highly complex, computer-controlled intelligent systems.

Applications: Robots are used in factories to increase productivity and cut

cost by replacing human in doing regular, repetitious, and boring jobs. Robots are

very suitable to do jobs that are too dangerous for humans such as

decontamination of nuclear wastes.

Advantages: Robots are reliable, uncomplaining, never getting tired or bored.

Disadvantages: Scientists need to design a number of arms for doing

specific jobs.

When we talk of robotics, ‘Robocop’ and ‘Terminator’ come to our mind. In movies,

robots such as the terminator are portrayed as fantastic, intelligent machines. However,

the majority of the robots today are not exactly the walking, talking intelligent machines

as depicted in the movies. The majority of robots are used in factories, warehouses and

laboratories. In the future, they may show up in schools, homes or even our bodies-the

possibilities are endless.

Five musts in a robot:

Controller, arm, drive, end-effector and sensor are the basic parts that a useful

robotic system must have. However, robots without arms and end-effectors also do exist;

for example, certain mobile robots used for surveillance. But the controller, drive and

sensor are prerequisites for any robotic system, be it industrial, recreational or research-

oriented.

Controller: Every robot is connected to a computer, which keeps the pieces of

the arm working together. This computer is known as the controller. It functions

as the ‘brain’ of the robot. The controller also allows the robot to be networked

to other systems, so that it may work in collaboration with other machines,

processes or robots. The majority of robots today are entirely preprogrammed.

This means that they can do only what they are programmed to do at the time, and

nothing else. However, in the near future, controllers with artificial intelligence

could allow robots to ‘think’ on their own and even program themselves.

Arms: Robot arms come in all shapes and sizes. The arm is that part of the

robot which positions the end-effecter and sensors to do their preprogrammed

business. Many resemble human arms, and have shoulders, elbows, wrists and

even fingers. This gives the robot one degree of freedom. So a simple robot arm

with three degrees of freedom could move in three ways: up and down, left and

right, and forward and backward. Most working robots have six degrees of

freedom.

Drive: The drive is the ‘engine’ that drives the links into their desired position.

Without a drive, a robot is as good as dead. Most drives are powered by air, water,

pressure and electricity.

End - effector: The end-effecter is the hand connected to the robot’s arm. It is

often different from a human hand: It could be a tool such as gripper, vacuum

pump, tweezers, scalpel, blow torch or just about anything that helps it do its job.

Some robots can change end effectors and be reprogrammed for a different set of

tasks. If the robot has more than one arm, there can be more than one end-effecter

on the same robot, each suited to a specific task.

Sensor: Robots without sensors are deaf and blind. Sensors provide limited feed

back to the robot and aid it in performing the job. These send information in the

form of electronic signals back to the controller, letting it know about the state of

the world around it. However, compared to the senses and abilities of even the

simplest living things, robots still have a very long way to go.

Robot architectureRobotic systems are complex and tend to be difficult to develop .A robot ‘architecture’

primarily refers to the software and hardware framework for controlling the robotic

system. System developers have typically relied upon reference architectures to guide

the construction of robotic systems and provide computational services to sub-systems.

These architectures, however, have tended to be task and domain specific, and lack

suitability to a broad range of applications. For example, an architecture well suited to

direct teleportation will not be amenable for supervisory control or for autonomous use.

A mixture of asynchronous and synchronous control and data flow typifies the other

leading architectural trend. Asynchronous processes are characterized as loosely coupled

and event-driven without strict execution deadlines. Synchronous processes, in contrast,

are tightly coupled. These utilize a common clock and demand real-time situation.

Towards Autonomy The computing and software technologies have reached a point where anyone with the

right aptitude can give any electronic product or application more autonomous

behavioural functionality than could be imagined in the near past. The advances made in

the field of micro electronics have virtually made the design and development of robotic

systems much easier. You only need to identify the right product for your application

and there you are building your robotic system.

Robotics is used for industrial automation to the extent that the terms ‘robotics and

industrial automation’ have become synonyms in the industrial world.

The benefits of using electronics in robotic system are many:

1. Power requirements are typically less than for electromechanical systems.

2. Microcontroller-based devices are smaller and lighter than pure mechanical

systems.

3. Electronics provides a wide variety of changeable functions by simply

reprogramming the chip with the new product features.

4. The systems with fewer moving parts are more reliable while providing a longer

life.

In the hardware part the chip that forms the brain of the robot system steals the lime light.

A majority of robotic systems today employ a wide variety of micro controllers to power

the robotic brain. The low cost and significantly more advantages make micro controllers

and other electronic devices an ideal substitute for numerous mechanical applications.

The micro-controller is the No. 1 choice of robot developers to implement the brain that

powers the robot systems. The microcontroller forms the heart of the embedded system

that forms the brain of the majority of robots.

Distributed intelligence:

Use of highly integrated Microcontrollers allows development of distributed intelligence

systems. The prime reason why the trend is towards distributed intelligence is that it

provides higher reliability at a lower cost.

Microcontrollers are located in various parts throughout the system and control their local

functions while communicating with the master, which has less functionality. If a

problem occurs with one device, the rest of the system remains operational.

Motion Control:

In addition to highly repetitive tasks, positioning equipment has long been used to

provide specialized functions and processes. A good example is the semiconductor

manufacturing industry. In semiconductor manufacturing, the immediate presence of

operators has always been an unacceptable source of contamination. The newer facilities

are getting cleaner by completely removing people from the process; engineers are also

changing the equipment designs to eliminate that source of contamination.

When building a robot or a machine with a robotic function effectively embedded inside,

the biggest challenge is motion control. Robots are some of the most complex motion

control applications in the industry. The following performance requirements

consistently top the list of motion control challenges:

1. Mechanical Coupling: Robots are multiple but coupled motion control axes in a

single mechanism. Mechanical coupling is the major distinction between robots

and other mechanisms. In Cartesian machines, these coupled motions are linear-

move the X-axis and Y-axis exactly the same increment. But in robots coupling

creates complex non-linear motions which must be managed.

2. Kinematic Solutions: Unlike a collection of individual axes of motion control,

robots move in a coordinated fashion and this coordination is the basis for sensor

integration, path following, straight line movements and other features common to

commercial robots. Knematics is the mathematical representation of the robot

including it’s size, configuration and the relationship of each axes to the

mechanism as a whole. The kinematic solution is the algorithm for a robot’s

coordination system which is executed by the motion controller.

3. Large Work Envelopes: Robots are expected to perform uniformly throughout

their work envelope, but the use of a range of payloads makes servo tuning

extremely difficult. Mechanical coupling, the complex mechanisms, the need to

balance speed and precision all contribute to system resonance and vibration

issues which the motion controller is expected to manage and control.

4. Sensor Integration: Once reserved for the most advanced robots the integration of

complex sensors such as machine vision, force sensing and conveyor tracking is

now a routine requirement. The motion control system of a robot must atleast

adjusts points and paths in real time based on the sensed information.

Controlling Motion:

The three main approaches to implementing motion control on a robot are components;

software enabled components and integrated solutions.

The component approach is common for semiconductor robots, PCB assembling

machines and other Cartesian coordinate robots. Control components typically including

an industrial PC, motion control both, human machine interface and the programming

pendant are purchased from various vendors and integrated into a control system. Drives

and motors are matched for the mechanical device.

Robot Vision:

An increasing number of robotic applications require machine vision for guiding the

robot’s movement in automated assembly as well as for quality control. Machine vision

systems are replacing human vision for quality control inspection of manufactured or

natural objects because these inspections are often too fast or precise for human vision.

Machine vision replaces human vision with video cameras and specialized computers,

and can improve on human vision where precise and repeatable visual measurements and

inspections are required.

True vision guidance in robotics is both a hardware and software issue. A real vision

guided robot system is one which, with a single or multiple cameras integrated to the

robot controller, locates randomly oriented objects in the field of view of camera and

generates a robot transformation to identify the location and orientation of the object.

In order to achieve this capability a robust robot to camera calibration utility is required

and the robot controller must have an accurate model of the robot it is controlling. In

addition the robot programming language must have transformation variables for

developing the real location of the object by combining robot and vision location

information. Besides cameras small camcorders can be an inexpensive option for some

imaging applications in robotics.

The AndroidsAny thing on robotics will be incomplete without a reference to androids. Technically,

androids are anthropomorphic robots, i.e robots that look more like humans. An android

is robot with shape and abilities of a human. Androids can be said to be the ultimate in

instrumentation and control engineering. Androids will help us enjoy life by relieving us

of many of the mundane tasks. We have been designing tools and devices for our use of

millennia. But, if we build a robot it will automatically be able to use all of those

countless tools in the same manner as we would. Thus the androids will take over many

of our mundane tasks provided they have our shape and capabilities.

Androids will be capable of building themselves. This, in turn, will lead to lower product

cost. Androids will also be able to tell us what is wrong when some thing inside them

fails. In some cases they will be able to repair themselves or other androids-such as

doctors repair humans. In short, androids will be a new species of humans.

What lies ahead? Robots are no longer just the characters of sci-fi movies. In real world, they are

redefining manufacturing, medicine, exploration and consumer electronics. Combining

computer science and real world practicality, robotic applications range from today’s

automated vacuum cleaners and interactive toys to connected intelligent devices and

personal service companions of tomorrow.

Robotics has the potential to change our economy, health, standard of living, knowledge

and above all the world we live in. As technology progresses, we are finding newer ways

to leverage robotics. However, we must not forget that good things often come with

potential dangers also.

Suggestions:

To proceed effectively and systematically, robot designers and their critics might

concentrate on the following:

1. Be clear what design alternatives you are using and why. Speak in terms of memory,

perception, learning. What representations of the world are built in? What is stored? How

are sensation and action coordinated? How are routines learned? Attempt to develop a

language for classifying systems:

  a) categorical perception vs. only direct sensation. b) maps, map primitives, or

grammars for creating maps are hardwired. c) composite behaviors (e.g., sentence

templates), primitive behaviors (e.g., reflexes), or constraints between behaviors are

hardwired. d) opposing behaviors built in (e.g., left and right turn); sensors are fixed or

mobile.

2. Specify a robot's behavior using classical representations (e.g., scripts, grammars,

situation-action rules) so we can compare the capacities or "knowledge" of different

designs (including after learning). Similarly, specify environmental assumptions using

classical representations (e.g., quantitative and qualitative models). Principled robot

design requires systematically describing behaviors and environments.

3. Define the enterprise in terms of specific constraints: a) Functional; Biological and

Computational.

4. Don't view the design of a society of robots as a different research problem. Ignoring

the effect of other agents is just a variation of ignoring how the environment can structure

behavior (presumably the view we are arguing against).

5. Look for ways that emergent multi-agent patterns of interaction can be perceived by

individuals and structure individual behavior (Steels, 1990).

6. Move towards construction of processes, not just activation of rewired constraints

between behaviors. Move from the idea of predetermined, layered control (subsumption

architecture) to creating new compositions (literally new networks) that can be

reactivated (and potentially generalized rather than simply re-enacted). Programs like

Toto, compared to people, are both too reactive (no learning of procedures, composite

behaviors that effectively become new primitives) and too predetermined (no learning of

categories, new ways of coordinating behaviors outside the consumption layering).

Correlating multi-modal sensation might be a practical and not too complex starting

point.

References

1.Agre, P. 1988. The dynamic structure of everyday life. Dissertation in Electrical

Engineering and Computer Science, MIT.

2. Brooks, R. 1991. Intelligence without reason. IJCAI Proceedings. Sydney, Australia.

3.Clancey, W.J. in press a. Review of Rosenfield's The Invention of Memory. To appear

in the Journal of Artificial Intelligence.

4.Maes, P. 1990. Designing Autonomous Agents, Guest Editor. Robotics and

Autonomous Systems 6(1,2) 1-196.

5.Newell, A. 1984. The knowledge level, Artificial Intelligence 18(1) 87-127 .

6.www.bus.orst.edu/faculty/brownc/es_tutor/tree-lg.gif