Natural Language Understanding

Natural language understanding (NLU) is a branch of artificial intelligence (AI) that uses computer software to understand sentences in text or speech format. NLU understanding of natural human languages enables computers to understand commands without using formalized syntax of computer languages and for computers to communicate back to humans in their own languages. NLU is a challenging subfield of NLP.

The main drive behind NLU is to create chat and speech enabled bots that can interact effectively with the public without supervision. NLU is a pursuit of many start up and major IT companies. Companies working on NLU include Medium's Lola, Amazon's with Alexa and Lex, Apple's Siri, Google's Assistant and Microsoft's Cortana. There’s a fast-growing collection of useful applications derived from this field of study. Below are few of them:

• Spell Checking, Keyword Search, Finding Synonyms
• Extracting information from websites such as: product price, dates, location, people, or company names.
• Classifying: reading level of school texts, positive/negative sentiment of longer documents.
• Machine Translation.
• Spoken Dialog Systems.
• Complex Question Answering.

Problems in NLU

1. Ambiguity

Many of the things we say can be interpreted in more than one way. This ambiguity sometimes results in miscommunication between people and is one of the primary problems in programming computers to understand natural language.

2. Imprecision
Concepts often are not described with precision. Your ability to understand what is being said may rely on your familiarity with a situation. Consider the following sentences:
- I have been waiting in the doctor’s office for a long time.
- The crops died because it hadn’t rained in a long time.
- The dinosaurs ruled the earth a long-time age.
If you read a story that includes these sentences and then someone asked you about the length of the wait in the doctor’s office. You might respond that it was no longer than a few hours because you are familiar with the concepts discussed in these sentences. Without the conceptual familiarity, a computer would not be able to differentiate between the three different lengths of time represented by the same phrase “a long time”.

3. Incompleteness
We do not always say all of what we mean. Because we share common experience, we usually can omit many details without fear of being misunderstood; we assume that our listeners can “read between the lines.”
"John went out to a restaurant last night. He ordered steak. When he paid for it, he noticed that he was running out o money.”"
Did John eat the steak? Although it is not stated explicitly in the story, we probably assume that he did; after all, why else would he have paid for it? Your expectations of likely events in that particular situation allowed you to understand information that was not included in the text. To be able to comprehend incomplete information, a computer must possess the same kind of situational expectations.

4. Inaccuracy
People usually can understand what they are told, even if is not structured according to certain rules they know. Errors like

• Spelling errors.
• Ungrammatical constructions
• Incomplete sentences
• Improper punctuations

Types of Ambiguities in NLU

Following are the main types of ambiguites that usually occur in NLU

1. Lexical Ambiguity
Words have multiple meanings. For example,
"I saw a bat.
Now the word batmeans a flying-mammal or a wooden-club or saw in past tense of "see"(to cut with a saw).Without knowing something about the characteristics of both kinds of bat and saw, a computer could not determine which kind of bat or saw is meant in each sentence.
2. Syntatical Ambiguity
The ambiguity caused by the structure/syntax of the sentence is called syntactic ambiguity. Consider the following sentence.
I hit the man with the hammer.
How do you interpret this sentence? Did I pick the hammer and hit a man, or did I hit a man who was holding a hammer? Unless it is able to understand the context in which the sentence appears, a computer may be unable to determine the intended meaning.
3. Unclear Antecedents
We frequently use pronouns in place of previously used nouns.For example,
Aslam hit Akram because he sympathized with Nadeem.
Is Aslam or Akram the antecedent of “he”? In other words, who sympathized with Nadeem? As in the case of syntactic ambiguity, you cannot determine the antecedent of “he” without establishing a context for the sentence.

Solutions to NLU Problems

1. Context
One way that we resolve linguistic ambiguity is by understanding an idea in context. For example, consider the following narrative.
There were two men blocking my escape. One held a hammer; one had nothing in his hands. I knew that I could not hit both of them. I hit the man with the hammer.
This narrative ends with the ambiguous sentence “I hit the man with the hammer”. Because the sentence is presented here in context, you probably had no trouble determining its meaning.
2. Familiarity
We tend to identify with situations that are familiar to us, making it easier to understand language that deals with those situations. For example,
- I have been waiting in the doctor’s office for a long time.
- The crops died because it hadn’t rained in a long time.
- The dinosaurs ruled the earth a long-time age.
The phrase a long time ago in above sentences is giving different meaning in each sentence. Staying in a doctor's office for a long time is different from the phrase in the second or third sentence. We can only differentiate phrases when we will be familiar with all the situations.
3. Expectations
Through our experiences, we have come to expect certain things in certain situations. As an illustration, select the ending that is most likely to complete the following narrative.
John went to a restaurant and ordered a steak. When the waiter brought his order to the table, John:
a. Recited the Gettysburg Address.
b. Ate the steak.

What is an Industrial Robot

An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axis. Typical applications of robots include welding, painting, assembly, disassembly, pick and place for printed circuit boards, packaging and labeling, palletizing, product inspection, and testing; all accomplished with high endurance, speed, and precision. They can assist in material handling. In the year 2015, an estimated 1.64 million industrial robots were in operation worldwide according to IFR On basis of their movement these robots are categorized into two categories:

• Fixed Arm Robot: These robots are mounted on a base in a single location near where it will perform its work. It is generally secured to a cement floor with heavy bolts or is mounted on a table or other work surface so that it cannot move. In some special applications, the robot arm can be movable. E.g.: it may be mounted on rails so that it can slide along a production line.
• Mobile Robot: A mobile robot is capable of moving around. Such robots are generally manipulator arms mounted on a small vehicle

Components of an Industrial Robot

Gripper

1. Controller
The controller is the "brain" of the industrial robotic arm and allows the parts of the robot to operate together. It works as a computer and allows the robot to also be connected to other system. It sends signals to the power source to move the robot arm to a specific position and to actuate the end effector. Many of today's industrial robot arms use an interface that resembles or is built on the Windows operating system.
2. Manipulator Arm
Industrial robot arms can vary in size and shape. The industrial robot arm is the part that positions the end effector. With the robot arm, the shoulder, elbow, and wrist move and twist to position the end effector in the exact right spot. Each of these joints gives the robot another degree of freedom. A simple robot with three degrees of freedom can move in three ways: up & down, left & right, and forward & backward.
3. End Effector
The end effector connects to the robot's arm and functions as a hand. This part comes in direct contact with the material the robot is manipulating. Some variations of an effector are a gripper, a vacuum pump, magnets, and welding torches.Gripper is the simplest end-effector with pincher-type assembly that simulates a thumb and one finger. This allows the robot to be able to pick up objects within a certain size limitation. More sophisticated assemblies use three or more “fingers” to provide added flexibility.
4. Drive or Actuator
The actuator or drive is also referred as the power source. This is the basic source of energy for moving the arm, controlling the joints, and operating the end effector. Industrial robot arms generally use one of the following types of drives: hydraulic, electric, or pneumatic.
• Hydraulic Drive:
A hydraulic drive is a method of providing movement to a robot manipulator. It uses a special hydraulic fluid, usually oil-based, to transfer forces to various joints and end effectors. Hydraulically driven manipulators are used when motions must be rapid, precise, and repeated numerous times. Hydraulic systems are also noted for the ability to impart considerable force, so they are good for applications involving heavy lifting or the application of large amounts of pressure or torque. In addition, hydraulically driven robot manipulators resist unwanted movement in the presence of external forces.
• Electric Drive:
These drives AC and DC motors that provide rotation or joint movement. These are used in combination with mechanical assemblies such as gears or pulleys to make the basic movements.
• Pneumatic Drive:
These actuators use the principle of Pneumatics (where pressurized air/gas) to create motion (or perform work). Pneumatic actuators can be used to produce both rotational motion and linear motion.
5. Sensors
Sensors allow the industrial robotic arm to receive feedback about its environment. They can give the robot a limited sense of sight and sound. The sensor collects information and sends it electronically to the robot controlled. One use of these sensors is to keep two robots that work closely together from bumping into each other. Sensors can also assist end effectors by adjusting for part variances. Following are main sensors used in Robots:



Sensors

• Vision Sensors:
Vision sensors allow a pick and place robot to differentiate between items to choose and items to ignore. Installing a camera that focuses on the workspace gives vision to robot.
• Hearing Sensors:
Robots having speech recognition and generation technology use hearing sensors. These robots collect sounds from environement then sound signals are converted into digit signals by an ADC. Then these binary digits are compared with with previously stored binary representations of words and phrases. When match occurs, recognition is achieved. Once recognition is achieved the robot executes the command.
• Strain Guage:
They provide pressure feedbacks installed generally on grippers. The controller program adjusts the actuation devices, either increasing or decreasing pressure according to the feedback from strain guage sensors.
• Touch Sensors:
Touch sense enables the robot to know when it has come into contact with the work piece. It gives robot the sense of knowing how much pressure is being applied to workspace by the arm or end effector.

Expert System

Expert systems (ES) are one of the prominent research domains of AI. It is introduced by the researchers at Stanford University, Computer Science Department. These systems are the computer applications developed to solve complex problems in a particular domain, just like human experts.Expert systems are ideal when it is necessary for an individual to select the best alternative from a long list of choices. Based on the criteria supplied to it, the expert system can choose the best option. For example, there are expert systems that will help you to select one of the many places to invest your money based on your own financial conditions, goals, and personality traits.

Let's Look at the diffrence between conventional Database System and Expert System

Diffrence between DB and ES System

Conventional Database Systems	Expert Systems
DB system is composed of Database, DB repository and Database Management System (DBMS)	This system is comprised of knowledge base, inference engine and user interface.
Data is entered into DB via DBMS.	Data is fed into knowledge base through UI.
No component in DB to make decisions.	Inference Engine makes decisions on base of knowledge fed into the knowledge base
It accepts only textual Data.	It accepts all kind of data i.e. textual, pictorial or complex data patterns from nature.
It has no AI involvment.	The system involves some sort of AI functionality.

Features of Expert System

Each expert system has its own particular characteristics; there are several features common to many expert systems. These are:

• “The program should be useful.” An expert system should be developed to meet a specific need, one for which it is recognized that assistance is needed.
• “The program should be usable.” ” An expert system should be designed so that even a novice computer user finds it easy to use.
• “The program should be educational when appropriate.” An expert system may be used by non-experts, who should be able to increase their own expertise by using the system.
• “The program should be able to explain its advice.” ” An expert system should be able to explain the “reasoning” process that led it to its conclusions, to allow you to decide whether to accept the system’s recommendation.
• “The program should be able to respond to simple questions.” Because people with different levels of knowledge may use the system. An expert system should be able to answer questions about points that may not be clear to all users.
• The Program should be able to learn new knowledge. Not only should an expert system be able to respond to your questions, it also should be able to ask questions to gain additional information.
• The program’s knowledge should be easily modified. It is important that you be able to revise the knowledge base of an expert system easily to correct errors or add new information.

Applications of ExpertSystem

• Engineering and Manufacturing
ES in engineering and manufacturing process can provide greatest assistance for operational workers while performing and dealing the critical and important tasks. Furthermore, ES produces more accurate results than human expert and in short time.

• Medical
In many countries people have wait for longer periods before diesease has been diagnosed by specialist and when the treatment is stated, it may already late and patient could be suffered for the whole life. Computer technologies such as expert system can solve the above problem with the aim to conduct the earlier diagnosis diseases for patients, identify disease symptom and provide immediate accurate response to save patient life.

• Management
In large organization or companies, there are managers, accountant, financial analysis, consultant, strategic planners etc. These management people might have difficulties on budget, time constraint, planning and other management support and contributions. ES can provide assistance to the management of a company to investigate different aspects of organization’s problems.
• Military
ES can support in the command and control process ability by a military commander due to expensive and complexity real situation in the military program training. The potential of expert system can solve many problems for the military such as a device tool to find bombs and mines, and search different radar.
• Education and Training
Most of teaching courses provide today are inn conventional method where there is less or no interaction in the learning process between teachers and pupils. Teachers would teach by chalk-talk method and pupils were just listening and takes note. Therefore, an ES may very useful to facilitate teaching and learning process. Moreover, expert system can act as intelligent tutor and perhaps tutor and students are unnecessary anymore to meet in the same tutorial classroom.

Functionality of an Expert System

An ES includes following main components:

1. Knowledge Base:
It contains the knowledge related to specific domain.
What is Knowledge? The data is collection of facts. The information is organized as data and facts about the task domain. Data, information, and past experience combined together are termed as knowledge.
2. Inference Engine:
It acquires and manipulates the knowledge to reach to a solution from multiple solutions.
3. User Interface:
It provides interaction between user and ES.

CPEC

CPEC

China Pakistan Economic Corridor

A Short Introduction

China-Pakistan Economic Corridor is a framework of regional connectivity. CPEC will not only benefit China and Pakistan but will have positive impact on Iran, Afghanistan, India, Central Asian Republic, and the region. The enhancement of geographical linkages having improved road, rail and air transportation system with frequent and free exchanges of growth and people to people contact, enhancing understanding through academic, cultural and regional knowledge and culture, activity of higher volume of flow of trade and businesses, producing and moving energy to have more optimal businesses and enhancement of co-operation by win-win model will result in well connected, integrated region of shared destiny, harmony and development. 

China Pakistan Economic Corridor is journey towards economic regionalization in the globalized world. It founded peace, development, and win-win model for all of them. China Pakistan Economic Corridor is hope of better region of the future with peace, development and growth of economy.

China–Pakistan Economic Corridor (Urdu: پاكستان-چین اقتصادی راہداری‎;is a collection of infrastructure projects that are currently under construction throughout Pakistan. Originally valued at $46 billion, the value of CPEC projects is now worth $62 billion. CPEC is intended to rapidly modernize Pakistani infrastructure and strengthen its economy by the construction of modern transportation networks, numerous energy projects, and special economic zones. On 13 November 2016, CPEC became partly operational when Chinese cargo was transported overland to Gwadar Port for onward maritime shipment to Africa and West Asia, while some major power projects were commissioned by late 2017.

A vast network of highways and railways are to be built under the aegis of CPEC that will span the length and breadth of Pakistan. Inefficiencies stemming from Pakistan's mostly dilapidated transportation network are estimated by the government to cause a loss of 3.55% of the country's annual GDP. Modern transportation networks built under CPEC will link seaports in Gwadar and Karachi with northern Pakistan, as well as points further north in western China and Central Asia. A 1,100 kilometer long motorway will be built between the cities of Karachi and Lahore as part of CPEC, while the Karakoram Highway between Rawalpindi and the Chinese border will be completely reconstructed and overhauled. The Karachi–Peshawar main railway line will also be upgraded to allow for train travel at up to 160 km per hour by December 2019. Pakistan's railway network will also be extended to eventually connect to China's Southern Xinjiang Railway in Kashgar. The estimated $11 billion required to modernize transportation networks will be financed by subsidized concessionary loans.

Over $33 billion worth of energy infrastructure are to be constructed by private consortia to help alleviate Pakistan's chronic energy shortages, which regularly amount to over 4,500MW, and have shed an estimated 2–2.5% off Pakistan's annual gross domestic product. Over 10,400MW of energy generating capacity is to be brought online by the end of 2018, with the majority developed as part of CPEC's fast-tracked "Early Harvest" projects. A network of pipelines to transport liquefied natural gas and oil will also be laid as part of the project, including a $2.5 billion pipeline between Gwadar and Nawabshah to eventually transport gas from Iran. Electricity from these projects will primarily be generated from fossil fuels, though hydroelectric and wind-power projects are also included, as is the construction of one of the world's largest solar farms.

CPEC's potential impact on Pakistan has been likened to that of the Marshall Plan undertaken by the United States in post-war Europe. Pakistani officials predict that CPEC will result in the creation of upwards of 2.3 million jobs between 2015–2030, and add 2 to 2.5 percentage points to the country's annual economic growth.

Were the initial $46 billion worth of projects to be implemented, the value of those projects would be roughly equivalent to all foreign direct investment in Pakistan since 1970, and would be equal to 17% of Pakistan's 2015 gross domestic product. CPEC is seen as the main plank of Chinese President Xi Jinping's Belt and Road Initiative.

What is Robotics

Robotics

The word Robot comes from a Czech word, robota, meaning "forced labor". It was first used to denote a fictional humanoid in a 1920 play. The first commercial, digital and programmable robot was built by George Devol in 1954 and was named the Unimate,.

Robotics is defined as

Robotics is a domain in artificial intelligence that deals with the study of creating intelligent and efficient robots.It is an interdisciplinary branch of engineering and science that includes mechanical engineering, electronic engineering, information engineering, computer science, and others.This field of science is concerned with the development of machines that can substitute humans and replication human actions.

Main Application Areas of Robotics:

1. Factory Robots:

1. Car production
   A typical factory contains hundreds of industrial robots working on different parts of a car like welding, glue, painting and finally assembling different parts.
2. Packaging
   Industrial robots are also used extensively for palletizing and packaging of manufactured goods, for example for rapidly taking drink cartons from the end of a conveyor belt and placing them into boxess.
3. Electronics:
   Mass-produced printed circuit boards (PCBs) are almost exclusively manufactured by pick-and-place robots.



2. Dirty, dangerous, dull or inaccessible tasks

   There are many jobs which humans would rather leave to robots. The job may be boring, such as domestic cleaning or sports field line marking, or dangerous, such as exploring inside a volcano.
1. Space probes:
   Almost every unmanned space probe ever launched was a robot. E.g. Curiosity Rover sent to Mars lunched on 26 November 2011. Teleoperated robots, or telerobots, are devices remotely operated from a distance by a human operator. They are used when a human cannot be present on site to perform a job because it is dangerous, far away, or inaccessible. Like, when disabling a bomb, the operator sends a small robot to disable it. E.g. Predator Unmanned Aerial Vehicle used by Military.
2. Domestic robots:
   These robots are simple robots dedicated to a single task work in home use like disliked or boring jobs, such as vacuum cleaning, floor washing, and lawn mowing. E.g Rumba

3. Research Robots:

1. Bionics, Bioinformatics

Types of Robotics

Generally we have two types of robotics

1. General Purpose Robotics

• Android
An android is a humanoid robot designed to be similar in form to humans. Some androids are built with the same basic physical structure and motion capabilities as humans but are not identical to humans. They may have jointed arms and legs and capable of walking and running like humans but have a plastic or metal exterior that in no way mimics human appearance. Examples of this type of include android Google-owned Boston Dynamics’ Atlas robot, Houstan Robotics’Sophia.
• Cyborg
A cybrog short for “cybernetic Organism”, is a being with both organic and biomechatronic body parts. The term was coined in 1960 by Manfred Clynes and Nathan S. Kline. The term cybrog is used for organism with enhanced abilities due to the integration of some artificial component or technology.E.g. Colorblind Neil Harbisson attached high-tech antenna to his head. This device translates color frequencies into sound frequencies, which allow Harbisson to hear “color”. The implant has also internet connection, people can send image, files and music to his head.

1. Industrial Robotics

An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axis. Typical applications of robots include welding, painting, assembly, disassembly, pick and place for printed circuit boards, packaging and labeling, palletizing, product inspection, and testing; all accomplished with high endurance, speed, and precision. They can assist in material handling. In the year 2015, an estimated 1.64 million industrial robots were in operation worldwide according to IFR . On basis of their movement these robots are categorized into two categories:
• Fixed Arm Robots
These robots are mounted on a base in a single location near where it will perform its work. It is generally secured to a cement floor with heavy bolts or is mounted on a table or other work surface so that it cannot move. In some special applications, the robot arm can be moveable. E.g.: it may be mounted on rails so that it can slide along a production line.
• Mobile Robots
A mobile robot is capable of moving around. Such robots are generally manipulator arms mounted on a small vehicle.

What is AI and Its Main Applications

What is AI?

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

Main Applications of AI

Expert System

Expert systems (ES) are one of the prominent research domains of AI. It is introduced by the researchers at Stanford University, Computer Science Department. These systems are the computer applications developed to solve complex problems in a particular domain, just like human experts. Expert systems are ideal when it is necessary for an individual to select the best alternative from a long list of choices. Based on the criteria supplied to it, the expert system can choose the best option. For example, there are expert systems that will help you to select one of the many places to invest your money based on your own financial conditions, goals, and personality traits. An ES includes following main components:
1: Knowledge Base
It contains the knowledge related to specific domain. What is Knowledge? The data is collection of facts. The information is organized as data and facts about the task domain. Data, information, and past experience combined together are termed as knowledge.
2: Inference Engine It acquires and manipulates the knowledge to reach to a solution from multiple solutions.
3: User Interface: It provides interaction between user and ES.


Natural Language Processing NLP

Natural Language Processing, usually shortened as NLP, is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language (voice or text). The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable. Generally, the output of NLP can be Speech or Written Text. It has three basic parts: 

1: Parser:The parser takes the natural language input sentence and breaks it down into the various parts of grammar (nouns, verbs, adjectives, prepositions, etc.). This is the first step in determining the function of each word in the sentence and the way the words related to one another. This analysis usually results in construction of parse tree. A dictionary associatedwith the parser helps determine word meaning

2: Knowledge Base:It analyses the data came from parser with associated dictionay meanings. It then tries to take some action on basis of input received from parser.

2: Output Translator:It takes input from Knowledge Base system and performs some action or produces some ouput. Ouput may be speech in some other Natural Language or same language that is entered or it may produce some results in written form.


Speech Recognition and Generation

It allows users to interact with system via voice. One of the most common application of speech recognition and Generation is Microsoft’s Cortana used in win 8 and win 10. Other applications of voice recognition are Google’s speech recognition system and Apple’s Sirri. In early 2014, Amazon released the Amazon Dash, a portable device that one can use to compile a grocery list by voice recognition. The output of the voice reconition can be used to drive a natural language processing system and the NLP will take actions according to voice commands.



Neural Networks

Artificial neural networks (ANN) are computing systems that are inspired by, but not identical to, biological neural networks that constitute animal brains. Such systems "learn" to perform tasks by considering examples, generally without being programmed with task-specific rules. For example, in image recognition, they might learn to identify images that contain cats by analyzing example images that have been manually labeled as "cat" or "no cat" and using the results to identify cats in other images. They do this without any prior knowledge of cats, for example, that they have fur, tails, whiskers and cat-like faces. Instead, they automatically generate identifying characteristics from the examples that they process.

An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses (a structure in brain which allows neurons to send signal to other neurons) in a biological brain, can transmit a signal to other neurons. An artificial neuron that receives a signal then processes it and can signal neurons connected to it. ANNs have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games, medical diagnosis and even in activities that have traditionally been considered as reserved to humans, like painting.

Computer Vision

Computer vision is a scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos or Visuals. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to perform a decision. Domains of computer vision are scene reconstruction, video tracking, object recognition, motion sensing and image restoration.

Computer vision extracts information from images through a camera or set of cameras. This information is then converted into digital format with the help of ADC (Analog to Digital Convertor). Once the data is converted into digital format then AI in computer analysis this data and performs the required action.

Virtual Reality

Virtual Reality (VR) is the use of computer technology to create a simulated environment. Unlike traditional user interfaces, VR places the user inside an experience. Instead of viewing a screen in front of them, users are immersed and able to interact with 3D worlds. By simulating as many senses as possible, such as vision, hearing, touch, even smell, the computer is transformed into a gatekeeper to this artificial world. The only limits to near-real VR experiences are the availability of content and cheap computing power. As of the end of 2018, the three-best selling Virtual Reality headsets were Sony’s PlayStation VR (PSVR), Facebook’s Oculus Rift and the HTC Vive. This was not a surprise, seeing as the same three HMDs (Head Mounted Displays) had also been best sellers in 2017. 2019 sees the VR landscape broadening with Google, HP, Lenovo, and others looking to grab a piece of the still-burgeoning market. For Further Details visit these sites:
Oculus From facebook: https://www.youtube.com/embed/-bQUBzPZHHQ
PlayStation VR https://www.youtube.com/embed/-GXvYexMoZY
HTC Vive https://www.youtube.com/embed/i1r76omNeI8

Robotics

Robotics is a domain in artificial intelligence that deals with the study of creating intelligent and efficient robots.It is an interdisciplinary branch of engineering and science that includes mechanical engineering, electronic engineering, information engineering, computer science, and others.This field of science is concerned with the development of machines that can


substitute humans and replication human actions. Robots can be used in many situations and for lots of purposes like today they are used dangerous environments like deactivation of bombs, in manufactring processes or in those situations where humans cannot survive like space, water, in high temprature and cleaning up hazardous materials and radiations.

Current Potential Uses of Robots

• Construction Robots
• Agricultural Robots
• Combat Robots
• Medical Robots
• Humaniod Robots
• Military Robotics