November 2018 - Archieve

Under the hood articles from the past.

Artificial Intelligence

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.

AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as Apple's Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention.

Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services.

While AI tools present a range of new functionality for businesses,the use of artificial intelligence raises ethical questions. This is because deep learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given in training. Because a human selects what data should be used for training an AI program, the potential for human bias is inherent and must be monitored closely.

Some industry experts believe that the term artificial intelligence is too closely linked to popular culture, causing the general public to have unrealistic fears about artificial intelligence and improbable expectations about how it will change the workplace and life in general. Researchers and marketers hope the label augmented intelligence, which has a more neutral connotation, will help people understand that AI will simply improve products and services, not replace the humans that use them.

Types of artificial intelligence
Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, categorizes AI into four types, from the kind of AI systems that exist today to sentient systems, which do not yet exist. His categories are as follows:

Type 1: Reactive machines. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chess board and make predictions, but it has no memory and cannot use past experiences to inform future ones. It analyzes possible moves -- its own and its opponent -- and chooses the most strategic move. Deep Blue and Google's AlphaGO were designed for narrow purposes and cannot easily be applied to another situation.
Type 2: Limited memory. These AI systems can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way. Observations inform actions happening in the not-so-distant future, such as a car changing lanes. These observations are not stored permanently.
Type 3: Theory of mind. This psychology term refers to the understanding that others have their own beliefs, desires and intentions that impact the decisions they make. This kind of AI does not yet exist.
Type 4: Self-awareness. In this category, AI systems have a sense of self, have consciousness. Machines with self-awareness understand their current state and can use the information to infer what others are feeling. This type of AI does not yet exist.
[Image: An explanation of the differences between AI and cognitive computing]   What's the difference between AI and cognitive computing?
Examples of AI technology
AI is incorporated into a variety of different types of technology. Here are seven examples.

Automation: What makes a system or process function automatically. For example, robotic process automation (RPA) can be programmed to perform high-volume, repeatable tasks that humans normally performed. RPA is different from IT automation in that it can adapt to changing circumstances.
Machine learning: The science of getting a computer to act without programming.Deep learning is a subset of machine learning that, in very simple terms, can be thought of as the automation of predictive analytics. There are three types of machine learning algorithms:
Supervised learning: Data sets are labeled so that patterns can be detected and used to label new data sets
Unsupervised learning: Data sets aren't labeled and are sorted according to similarities or differences
Reinforcement learning: Data sets aren't labeled but, after performing an action or several actions, the AI system is given feedback
Machine vision: The science of allowing computers to see. This technology captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing. It is often compared to human eyesight, but machine vision isn't bound by biology and can be programmed to see through walls, for example. It is used in a range of applications from signature identification to medical image analysis. Computer vision, which is focused on machine-based image processing, is often conflated with machine vision.
Natural language processing (NLP): The processing of human -- and not computer -- language by a computer program. One of the older and best known examples of NLP is spam detection, which looks at the subject line and the text of an email and decides if it's junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis and speech recognition.
Robotics: A field of engineering focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used in assembly lines for car production or by NASA to move large objects in space. Researchers are also using machine learning to build robots that can interact in social settings.
Self-driving cars: These use a combination of computer vision, image recognition and deep learning to build automated skill at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians.
AI applications
Artificial intelligence has made its way into a number of areas. Here are six examples.

AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best known healthcare technologies is IBM Watson. It understands natural language and is capable of responding to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications include chatbots, a computer program used online to answer questions and assist customers, to help schedule follow-up appointments or aid patients through the billing process, and virtual health assistants that provide basic medical feedback.
AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers. Automation of job positions has also become a talking point among academics and IT analysts.
AI in education. AI can automate grading, giving educators more time. AI can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. AI could change where and how students learn, perhaps even replacing some teachers.
AI in finance. AI in personal finance applications, such as Mint or Turbo Tax, is disrupting financial institutions. Applications such as these collect personal data and provide financial advice. Other programs, such as IBM Watson, have been applied to the process of buying a home. Today, software performs much of the trading on Wall Street.
AI in law. The discovery process, sifting through of documents, in law is often overwhelming for humans. Automating this process is a more efficient use of time. Startups are also building question-and-answer computer assistants that can sift programmed-to-answer questions by examining the taxonomy and ontology associated with a database.
AI in manufacturing. This is an area that has been at the forefront of incorporating robots into the workflow. Industrial robots used to perform single tasks and were separated from human workers, but as the technology advanced that changed.
[Image: The impact of AI on marketing]   How AI affects marketing operations
Security and ethical concerns
The application of AI in the realm of self-driving cars raises security as well as ethical concerns. Cars can be hacked, and when an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing the programming to make an ethical decision about how to minimize damage.

Another major concern is the potential for abuse of AI tools. Hackers are starting to use sophisticated machine learning tools to gain access to sensitive systems, complicating the issue of security beyond its current state.

Deep learning-based video and audio generation tools also present bad actors with the tools necessary to create so-called deepfakes, convincingly fabricated videos of public figures saying or doing things that never took place.

[Image: How biased data leads to inaccurate AI predictions]   How data bias impacts AI outputs
Regulation of AI technology
Despite these potential risks, there are few regulations governing the use AI tools, and where laws do exist, the typically pertain to AI only indirectly. For example, federal Fair Lending regulations require financial institutions to explain credit decisions to potential customers, which limit the extent to which lenders can use deep learning algorithms, which by their nature are typically opaque. Europe's GDPR puts strict limits on how enterprises can use consumer data, which impedes the training and functionality of many consumer-facing AI applications.

In 2016, the National Science and Technology Council issued a report examining the potential role governmental regulation might play in AI development, but it did not recommend specific legislation be considered. Since that time the issue has received little attention from lawmakers.

Customer Service Robots

Customer service robots are professional service robots intended to interact with customers. These robots come in humanoid and non-humanoid forms and automate much of the most basic of tasks in customer service. Like all robots, their value lies in labor savings, efficiency and uptime.
The market for public relations robots is set for robust growth. In 2018, sales of public relations robots grew 53% over 2017, with an estimated 7,000 units sold, according to the International Federation of Robotics World Robotics 2018 Service Robots report. Between 2019 and 2021, approximately 40,500 units will be sold, representing a 37% compound annual growth rate (CAGR).
Most customer service robots are used to assist customers in finding an item or completing a task. They’re being deployed in the retail industry to guide customers around a store, as well as in the hospitality industry. Customer service robots can be found in banks, shopping malls, family entertainment centers and more.
The true value of customer service robots lies not only in their ability to interact with customers more cost-effectively than human staff, but their ability to collect customer data during face-to-face interactions. In this way, customer service robots have major potential for developing interactive marketing and re-branding strategies and for the tracking and analytics of customer behavior.
Customer service robots can be deployed in a variety of ways. The market is expected to steadily rise as industry consolidation accelerates technological progress. As their ability to interact with customers and collect data improves, they’re expected to become an increasingly regular part of the customer service process.

Welcome To The Robotics World

As soon as we come across the word robot, we tend to imagine a metallic structure with arms and legs carrying a human-like appearance and running errands for our help. However, in actual terms, it’s just a machine operated externally or through a controller embedded within and doesn’t necessarily look like a human. Technically, robotics is a branch of Science and Engineering which deals with designing, constructing, and operating robots as well as computer systems for their control, sensory feedback, and information processing.

Introduction to Robotics

Interestingly, the concept is almost as old as the hills with the first robot dating back to 350 BC, built in the form of a mechanical bird, by a Greek mathematician named Archytas. Although the term was coined ages ago, the actual potential of the fully autonomous robotics was realised in the second half of the 20th century.


The primary objective of robotics was to just perform a set of complex tasks mainly in factories with parts of robots but now it has spread to a lot of fields. Today, we can find the following industrial applications of robotics -:

Military: It goes without saying that military operations involve a high level of risk and hence it makes sense to use machines so as to save human lives. There a lot of varieties of military robots namely UAVs (Unmanned Aerial Vehicles aka drones), UGVs (Unmanned Ground Vehicles) and UUVs (Unmanned Underwater Vehicles). These are used to locate the terrorists and launching attacks. There are even four-legged robots for carrying heavy arms and ammunition.

Education: Many schools and institutes are using robots to educate and engage the students for STEM programs (Science, Technology, Engineering, and Mathematics). There are a lot of kits available for students through which they can learn a lot about robotics. Not only this, but kids with autism and other behavioral disorders also find it more convenient to interact with robots and gain knowledge about various subjects.

Healthcare: Various kinds of robots are being developed to be used in hospitals to aid the doctors and nurses in taking care of the patients. There are robots that can disinfect a place, take care of the needs of the patients and even remove unwanted elements from the body without surgery. There is also a robot named da Vinci which helps in performing surgeries with precision which are difficult to perform manually.

Agriculture: Many small-sized robots are used in agricultural fields which are equipped with camera and sensors. These navigate through fields and detect the weeds and other kinds of infection. The sensors help in applying the spray only on the affected areas, thereby protecting the environment from the release of harmful chemicals in the air.

Factory: Industrial robots are evidently being equipped on a large scale in factories building heavy equipment. Factors like negative population growth in certain countries, the disinterest of the younger workforce to indulge in factory work and time-saving efficiency of robotic parts are determining the surge in the usage of industrial robots. The most common illustration that can be cited here is the automobile factories that build cars through robotic parts along with human workers.

Space: Several countries have built their own space robots carrying various shapes and sizes in order to explore the space. Some of them can’t even control their own weight on earth but work efficiently in space with excellent dexterity. Since there isn’t any gravity and certain situations are challenging for survival, these robots can be easily substituted in the space for capturing videos and for performing other routine tasks.

From the heavy, metallic, and wired machines known as super robots to tiny devices known as nanobots, the field of robotics has been explored to a great extent. Enlisted below are the varieties of robots that have been designed lately. Let’s check out the list of some interesting forms of robots -:

Exoskeletons: It’s a technology where an electronic body suit offers limb movement and increased strength to the user. Primarily, these are used for the military purpose to lift heavy load and for patients suffering from spinal injuries.

Example: Ekso Bionics has developed full body ekso suits that can be worn by people who are victims of stroke or a spinal cord injury to get back on their feet. Originally developed for DARPA to be used by soldiers, these suits are also used in various rehabilitation clinics for patients with lower extremity weakness.

Humanoid robots: These are the robots that have a body resembling with a human containing a head, two arms, a torso and two legs. A subcategory of humanoids is known as Androids who appear much like a human with respect to the aesthetic aspects and can imitate the expressions of a human.

Example: Atlas is one of the most advanced humanoid robot developed by Google-owned Boston Dynamics. Although it’s not an android with human-like skin and expressions, yet it can do a lot of interesting stuff. It can walk in snow and re-balance itself just like us, open doors, lift boxes and even sense objects lying in front of it.

Animal Robots: Bio-inspired robotics is a fairly new category of robotics where the natural biological characteristics of living beings are replicated in the form of animal-inspired robotic models. The traits of animals like the way they hop, climb, walk or crawl is observed and then efforts are made to iterate them in a machine setup.

Example:  There is a robot named Cheetah developed by Boston Dynamics that can gallop at more than 29 miles per hour. A similar robot with the same name is developed by MIT which can sense obstacles and jump over them while running at 13 miles per hour.

Rescue Robots: One of the most logical and sensible uses of robots is to deploy them in situations of disaster management for rescue operations. It takes a lot of courage as well as efforts to search and save the victims during a human or man-made disaster. Even though there have been instances when robots were designated for rescue operations but they failed to perform as per the expectations. It’s still considered as an emerging technology since there are a lot of challenges to be faced.

Nanobots: These tiny devices are designed to perform repetitive tasks with precision at nanoscale dimensions of a few nanometers or less. These are applied in the assembly and maintenance of sophisticated systems or for building devices, machines, and circuits at the atomic or molecular level. Besides, nanobots are equipped in healthcare for the purpose of drug delivery, destroying cancer cells, etc.

Example: A group of physicists at the University of Mainz in Germany have designed the world’s smallest engine from a single atom. It converts heat energy into the movement at the smallest scale that one has ever seen.
Swarm: Swarm robotics is much like imitating a group of insects or ants in the form of tiny devices crawling together and forming certain designs. These can be used in the fields like agriculture, rescue tasks or military operations.

Example: A swarm of 1,024 tiny robots was devised by Harvard University that could make certain formations like alphabets, five-pointed stars and other complex designs without any central intelligence.

[Image: Amazing world of robotics-Swarm robots]

Figure 5: Swarm Robots creating various formations DARPA Robotics Challenge
DARPA Robotics Challenge i.e. DRC was conducted by US Defense Agency DARPA (Defense Advanced Research Projects Agency) which went on from 2012-15. The idea was to develop semi-autonomous robots that could help in rescue operations in a human-engineered environment. A lot of teams participated in the contest but only three of them were able to complete all the 8 tasks. The first price was bagged by Team KAIST with their robot DRC Hubo, followed by the runners-up IHMC and Tartan Rescue at second and third positions respectively.

The tasks assigned to the robots include driving a vehicle, walk through uneven rubble, clear debris, turn valves, connect hoses, open doors, drill a hole and climb up the stairs. Though these are easy for humans, the same is extremely complicated for robots. It takes hundreds and thousands of lines of coding to make the robot take just one step. Besides, humans started walking after multiple years of evolution and even now when a child is born, it takes more than a year to be able to walk with perfection. So, there are still a lot of challenges and obstacles that have to be handled.

Today there are plenty of robots carrying a variety of shapes, sizes, and structures but all of them are subject to certain challenges. For instance, the robots participating in DARPA contest were efficient in human-like tasks but they didn’t have a proper system to perceive their environment and were simply following instructions from the operator. Then there are mini robots like Darwin developed by ROBOTIS who are quite skilled in walking, playing football, and even get up after falling but then they can’t be put to use in applications needing physical strength. There is also a robot named Cozmo by Anki which can even express feelings and play but it’s merely for entertainment.

Moving on, there are certain implications of robotics that need to be discussed. It’s been a long-time notion that the development and deployment of robots are going to take away numerous jobs from the human workforce. However, Sherry Turkle who is a professor at MIT says that robots are not substitutes but companions of humans and their development would rather generate jobs.

Another concern is that we need to set a limit on the nature of tasks that are designated to the robots. It’s logical to use them at places which are too dangerous for humans to access but it also raises a big question that if anything goes wrong, who will bear the blame. Undoubtedly, technology has always offered numerous benefits and plays an important role in our life but it’s equally important to decide the limit of its usage.

Different Types Of Service Robots

service robot is a robot which operates semi- or fully autonomously to performservices useful to the well-being of humans and equipment, they exclude manufacturing operations, and they are capable of making decisions and acting autonomously in real and unpredictable environments to accomplish determined tasks.

Industrial Robots Are The Largest Application Of Robotic Technology

Owing to rapid technological advancements in robotics and automation, the manufacturing sector has witnessed an increased adoption of robotics engineering and technology into its production processes. Industrial robots are being used to perform tasks with high precision and repeatability resulting in products of higher quality. The ability of industrial robots to work continuously without taking a break is helping manufacturers in increasing output. Moreover, robots can work in dangerous and harmful environments, thus improving the working conditions and safety of the production plant. Therefore, the several advantages of industrial robots are encouraging manufacturers to integrate different types of industrial robots in its production line to increase plant efficiency and profitability.

The food packaging robotics market is expected to grow at a CAGR of over 10% by 2022. To be a part of this highly profitable market, industrial robot manufacturers such as ABB, FANUC Robotics, KUKA, Yaskawa Electric and Kawasaki Heavy Industries are investing in research and development to provide end users with more sophisticated and customized automation solutions.

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What are the Major Types of Industrial Robots in 2018

Based on mechanical configuration, industrial robots can be classified into six major types namely: articulated robots, cartesian robots, SCARA robots, delta robots, polar robots and cylindrical robots. Apart from mechanical configuration, industrial robots can also be categorized based on motion control, power supply control and physical characteristics.

This blog will focus on the major types of industrial robots based on configuration, their advantages and disadvantages and the areas of application.

Articulated Robots

Articulated robot is one of the most comment types of industrial robots. It resembles a human arm in its mechanical configuration. The arm is connected to the base with a twisting joint. The number of rotary joints connecting the links in the arm can range from two joints to ten joints and each joint provides an additional degree of freedom. The joints can be parallel or orthogonal to each other. Articulated robots having six degrees of freedom are the most commonly used industrial robots as the design offers maximum flexibility.


High speed
Large work envelope for least floor space
Easier to align to multiple planes

Requires dedicated robot controller
Complicated programming
Complicated kinematics

Food packaging
Arc welding
Spot welding
Material handling
Machine tending
Automotive assembly
Steel bridge manufacturing
Steel cutting
Glass handling
Foundry and forging application

Cartesian Robots

Cartesian robots are also called rectilinear or gantry robots and have a rectangular configuration. These types of industrial robots have three prismatic joints to deliver linear motion by sliding on its three perpendicular axes (X, Y and Z). They might also have an attached wrist to allow rotational movement. Cartesian robots are used in majority of industrial applications as they offer flexibility in their configuration which make them suitable for specific application needs.


Provides high positional accuracy
Simple operation
Easy to program offline
Highly customizable
Can handle heavy loads
Less cost

Requires large operational and installation area
Complex assembly
Movement limited to only one direction at a time

Pick and place operations
Loading and unloading
Material handling
Assembly and sub-assembly
Nuclear material handling
Adhesive applications
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SCARA Robots

SCARA (Selective Compliance Assembly Robot Arm) robots have a donut shaped work envelope and consists of two parallel joints that provide compliance in one selected plane. The rotary shafts are positioned vertically, and the end effector attached to the arm moves horizontally. SCARA robots specialize in lateral movements and are mostly used for assembly applications. The SCARA robots can move faster and have easier integration than cylindrical and cartesian robots.


High speed
Excellent repeatability
Large workspace

Requires dedicated robot controller
Limited to planar surfaces
Hard to program offline

Assembly applications
Semiconductor wafers handling
Biomed applications
Machine loading
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Delta Robots

Delta robots are also called parallel link robots as it consists of parallel joint linkages connected with a common base. Owing to direct control of each joint over the end effector, the positioning of the end effector can be controlled easily with its arms resulting in high speed operation. Delta robots have a dome shaped work envelope. These robots are generally used for fast pick-and-place or product transfer applications.


Very high speed
High operational accuracy

Complicated operation
Requires dedicated robot controller

Food industry
Pharmaceutical industry
Electronic industry
Flight simulators
Automobile simulators
Optical fiber alignment
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Polar Robots

Polar robots have a twisting joint connecting the arm with the base and a combination of two rotary joints and one linear joint connecting the links. These are also called as spherical robots, since it has a spherical work envelope and the axes form a polar co-ordinate system. These robots have a centrally pivoting shaft and an extendable rotating arm. The gun turret configuration of polar robots sweeps a large volume of space, but the access of the arm is restricted within its workspace.


Can reach all around
Can reach above or below obstacles
Large work volume
Requires less floor space

Cannot reach above itself
Short vertical reach
Low accuracy and repeatability in direction of rotary motion
Requires sophisticated control system
Fallen out of favor and not common in new designs

Die casting
Glass handling
Stacking and unstacking
Injection molding
Material handling
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Cylindrical Robots

Cylindrical robots have at least one rotary joint at the base and at least one prismatic joint connecting the links. These robots have a cylindrical workspace with a pivoting shaft and an extendable arm which moves vertically and by sliding. Thus, robots with cylindrical configuration offers vertical and horizontal linear movement along with rotary movement about the vertical axis. The compact design of the end of the arm allows the robot to reach tight work envelopes without any loss of speed and repeatability. It is mostly used in simple applications where materials are picked up, rotated and placed.


Simple operation and installation
Minimal assembly
Can reach all around itself
Requires less floor space
Can carry large payloads

Cannot reach around obstacles
Low accuracy in direction of rotary motion
Fallen out of favor and not common in new designs

Transport of LCD panels
Assembly applications
Coating applications
Die casting
Foundry and forging application
Machine loading and unloading

Future Trends: Major Types of Industrial Robots

While implementing industrial robotics and automation into their businesses, one needs to understand and select the appropriate type of robot for their operations. Manufacturers are considering factors such as load, orientation, speed, precision, duty cycle, travel and environment before selecting the robot that will give the most effective and profitable results in their plant. Leading robotics companies are providing automation and robotics solutions to cater to the specific needs of their clients.

There Is A Huge Demand For Artificial Intelligence Technologies

AI was once only the research subject of a select group of doctoral candidates, but now it has wide application for commercial, government agency and consumer use. For example, AI is used to create expert systems that are able to gather data, process it into information and make intelligent responses to stimuli. This technology has wide application in agriculture, military defense systems and health care surgical procedures. The area of robotics design and development uses AI technology to build machines for industrial entities that are able to work in places that are not suitable for humans like underwater at great depths or in outer space. Consumers also benefit from AI technology when they want to learn a foreign language without employing a human tutor. Voice recognition software enables foreign language students to practice their second language via computer and receive correction if words are mispronounced. AI is widely used in translation software that allows users to convert text from one language to another. Those who like computer games often benefit from contributions to the field of AI when they play online chess against a formidable digital opponent.