Wednesday, 31 July 2019

Walker is one of the newest robots from UBTECH Robotics. Below is just a few of the features and technologies used in its development. 1.Flexible walking on complex terrain: With gait planning and control, Walker can achieve stable walking on different surfaces including carpet, floor, marble, and more.
Walker is your agile smart companion—an intelligent, bipedal humanoid robot that aims to one day be an indispensable part of your family. Standing 4.75 feet (1.45 m) tall and weighing 170 lbs (77 kg), the new version of Walker is more advanced than ever, including arms and hands with the ability to grasp and manipulate objects, a refined torso with improved self-balancing, smooth and stable walking in difficult environments, and multi-modal interaction including voice, vision, and touch. Walker has 36 high-performance actuators and a full range of sensing systems that work together to insure smooth and fast walking.”There are a few things to keep in mind here. Walker seems to walk fairly well on a smooth surface free of obstacles, and doesn’t fall over, but that may or may not be a reasonable representation of how Walker would perform in an environment that is even slightly different. The piano playing is decent, but the fingers don’t appear to be actively actuated, at least in that version of the robot. I do like the box tracking and handoff, and it’s nice that Walker can sense and react to external forces, though I’m not sure we could say it is completely safe for human-robot interaction. It’s also worth pointing out that the push recovery, at this point, is very much best-case scenario: Walker is being pushed from the side while its near foot is planted; if pushed from the front or from behind while stationary, it may not fare so well.

I’m certainly excited to see what Walker becomes capable of as UBTECH continues its development, and it’s great that a consumer robotics company is investing in a humanoid like this. As we well know, building bipedal humanoids that can do useful things is very, very hard, and Walker is impressive even in its current state. Still, it’s important to be clear about what the capabilities and limitations of the robot actually are, especially when UBTECH suggests the robot “has the intelligence and capabilities to make a helpful impact in any home or business in the very near future,” and that it will “one day be an indispensable part of your family.”

Sunday, 23 June 2019

InMoov is the first Open Source 3D printed life-size robot. Replicable on any 3D printer with a 12x12x12cm area, it is conceived as a development platform .

Gael Langevin is the man behind this robot. He is a French sculptor and designer. His workshop is located in Paris, and he has been working for the biggest brands for more than 25 years. 7 years ago, January 2012 he started getting into robotics. The InMoov robot was born as a prosthetic hand project after he bought his first 3D printer for his work. After he released it to the public as open source, the feedback from the community helped and motivated him to continue with the robot.

This way InMoov was born as the first open source 3D printed life-size robot. The idea behind the design of each piece is to be able to print it in a small 3D printer with a 12x12x12 cm printable area, conceived as a development platform for universities, laboratories, hobbyist and makers. This system, based on sharing through a community gives him the honor to be reproduced in countless projects throughout the world. An estimation made by Gael himself numbers the amount of InMoov robots being built across the world at about 150 at different stages of the process. The feedback also helps in order to improve already existing parts of the robot, by either suggesting the improvements on the official InMoov website ( or by going a step further and designing the parts themselves with the appropriate modifications.
The project itself it’s still an unfinished work, since Gael wants to finish the whole robot adding legs to it, and the ability to walk. This will be the trickiest part of the robot design and functioning. Gael himself didn’t know anything about robotics before starting with this project, he has been learning about it as he was working on this project. Before starting the InMoov, he had already designed some robotic parts although they were never really functional, but just aesthetic. In the designing of this robot he has gone a step further having to think about all the parts involved in giving it the functionality and movement he was looking for. As this is being written there are already 228 different pieces designed for the robot, and more to come. All of its functions are controlled using a software called MyRobotLab, a package developed by Greg Perry and the community.
All the downloadable parts from the official InMoov website are designed by Gael himself using and open source software called Blender. After finishing each part, is released under a License CC BY-NC 3.0 (Creative Commons attribution-non-commercial) so “InMoov” is a trademark. This design is based on a human figure to make sure it stays in the lines and shapes, although it’s a secret on whom is based

Saturday, 1 June 2019

Mr.Aliriza Abdul Gafoor - Founder,Chairman and CEO of Flewup Technologies has participated in Ai Everything summit held in Dubai.Dubai is the host of the inaugural ‘AI Everything Summit,’ an event organised by the UAE National Program for Artificial Intelligence in strategic partnership with Smart Dubai. Held under the patronage of His Highness Sheikh Mohammed Bin Rashid Al Maktoum, Vice President and Prime Minister of the UAE, Ruler of Dubai, the summit took place from April 30 to May 1, 2019, at Dubai World Trade Centre.
Opened by Sheikh Ahmed bin Saeed Al Maktoum, President of the Dubai Civil Aviation Authority, CEO and Chairman of the Emirates Group and Chairman of Dubai World, the AI Everything Summit seeks to promote initiatives, collaborations, partnerships, and breakthroughs in the field of AI and harness its positive impact for governments, businesses, social enterprises, and people in general.
Smart Dubai’s role as strategic partner for the summit is part of its efforts to build interactive international platforms to explore leading global trends in advanced technologies, enhancing the emirate’s status as a hub for technology, innovation and for building the smart cities of tomorrow.
The event explored AI-based innovations across various sectors, including government, the creative economy, social enterprises, education, energy, finance, healthcare, transport & logistics, travel & tourism, retail, security and telecommunications.

“It is clear that Artificial Intelligence has grown into a bona-fide sector of its own – and a rapidly expanding one at that. AI is gaining tremendous momentum around the world. Recent studies have predicted that AI will account for 45% of the world economy’s total gains by 2030 – that’s $15.7T – and as much as $122B to our GDP here in the UAE by 2030,” said Her Excellency Dr Aisha Bint Butti Bin Bishr.
“We are here today at the AI Everything 2019 Summit to find the ideal formula for all of us to work together and launch initiatives, R&Ds, and partnerships with AI at their core. Our shared objective is to affect positive change and support governments and businesses to embrace technology for the good of mankind,” Her Excellency concluded.
H.E. Al Nasser, Assistant Director General of Smart Dubai and CEO of the Dubai Data Establishment, co-chaired a workshop at the summit titled ‘Data Governance & Ethics,’ in addition to attending the launch of 2 new reports, the first of which, ‘Convergence in the Smart City’, explores how the convergence of emerging technologies (Blockchain, IoT, AI, etc.) necessitates the creation of a new decentralised web.
The second report, compiled by Smart Dubai, The Economist Intelligence Unit and Google, examines the potential economic impact of AI. His Excellency also gave a presentation exploring data and the ‘X Factor’ to powering Artificial Intelligence.
H.E. Wesam Lootah, CEO of the Smart Dubai Government Establishment, took part in a panel discussion titled ‘Welcome to The Future City of AI,’ which evaluated the concepts of applied Artificial Intelligence, AI for social good, and ‘augmented humanity,’ while Hessa Al Balooshi, Smart Dubai’s Director of Smart Services, took part in a panel discussion titled ‘The Secret Sauce in Successfully Implementing your AI Program.’
Smart Dubai used the forum to shed light on its forays into the Artificial Intelligence sector, showcasing the Ethical AI Toolkit, launched in January 2019 to set clear guidelines on the ethical use of the technology. It aims to prevent a fragmented, incoherent approach to ethics where every entity sets its own rules and to serve as a blueprint for governments to draft AI laws and regulations.
Smart Dubai also highlighted its AI Lab initiative, established in March 2017 in collaboration with multinational giant IBM, to harness the power of machine learning and produce practical solutions that enhance the lives of residents and visitors in Dubai.
Fundamental to its operations is the AI Roadmap, designed to integrate AI across all smart city services. Since its inception, the AI Lab has partnered with 13 government departments to identify more than 43 use cases that are currently being developed into pilots and live productions.
Smart Dubai also showcased its ‘Rashid’ initiative at the summit. Launched in October 2016, the AI platform puts the technology at the disposal of the community, offering official and reliable answers to their questions, procedures, documents and transactions – all according to the extensive database of Dubai’s Department of Economic Development.
The service was latterly upgraded with the ‘Living in Dubai’ feature to provide residents and visitors with access to the information they need to lead happy lives in the city and to complete transactions in a seamless and straightforward fashion

Thursday, 29 November 2018

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 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.

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.

Service Robots of All Types Promise to Disrupt Manual Processes Outside the Facility

Professional service robots are a diverse group of industrial and commercial robots. Whether they’re mobile or stationary, intended to build or demolish, service robots all have one thing in common: their highly unique capabilities put them in a position to disrupt a wide range of industries.

This section will be updated regularly with educational content on professional service robots. Continue to visit this site to continue learning more.

Wednesday, 28 November 2018

The Future of Professional Service Robots
Non-Factory Robotic Automation Opens Up New Markets
Robots were born in the factory. The rise of automation outside of the factory environment is nothing short of a robotic revolution. Professional service robots are the result of rapid technological advances over the past few decades. As quickly as they’ve been developed and deployed, they’ll just as quickly hit mainstream applications and are expected become an increasingly common presence on job sites and in commercial venues around the world. There are already dozens of industries leveraging them.
While there are technological barriers for today’s professional service robots, they’ve progressed a long way in a relatively short of time, and the short-term market growth projections are optimistic.
Projected Market Growth of Professional Service Robots
By all measures, the market outlook for professional service robots is strong, with particular areas of explosive growth over the next few years. Overall, the market is expected to reach a value of $37 billion between 2019 and 2021, according to the International Federation of Robotics (IFR). Between 2019 and 2021, it's predicted that the market will grow an average of 21% each a year – a remarkable number due to the wide-ranging forms and functions of robots considered 'professional service robots.'
Logistics robots are expected to lead the way in terms of sales volumes, with approximately 485,000 units to be sold between 2019 and 2021, representing an average 18% increase each year. Defense robots will see a moderate increase to 43,700 units sold during the same time period, at 8% yearly growth, and field robots will sell approximately 32,700 units, an average annual growth of 22%.
Projections for public relations robots remain strong – a 53% increase in sales to 15,870 units is expected for 2018, with about 93,350 units then sold between 2019 and 2021. Exoskeletons will begin to establish themselves in the market, with 40,500 units sold between 2019 and 2021, representing an average increase of 37%.
The market for professional service robots of all kinds looks bright. Across the board, high growth in sales volumes is projected.
Technological Challenges for Professional Service Robots
To facilitate continued market growth, there are a few key technological challenges to widespread implementation currently being addressed. Chief among them are vision for navigation, dexterity for control, and cognition for human interaction.
Improving vision software to help professional service robots navigate may be one of the most important challenges to the continued success of these robots. To profitably automate non-factory tasks, almost every single type of professional service robot needs to be able to autonomously navigate the environment around it without being preprogrammed. Vision systems are still advancing to a point where this autonomy is a standard feature, enabling robots to detect objects in their path and successfully navigate highly variable environments.
Similarly, dexterity is a key issue when it comes to professional service robots. Unlike industrial robots, they aren’t locked behind cages, which means some form of force limitation may be needed to protect human workers. Just as importantly, many professional service robots, such as cleaning robots or agricultural robots, need to be precise and careful not to damage the objects they’re working with and around. Vision systems will play a key role here, too.
Finally, advancing cognition for better face-to-face interaction with humans is a crucial barrier to overcome. Some types of professional service robots, such as customer service robots and humanoid robots, speak with and help customers as their primary responsibility. This requires complex programming that’s constantly being improved by some of the world’s biggest tech companies, but still has room for improvement for more fluid and accurate interactions.
Today’s professional service robots face a few key technological barriers, but there are solutions in development that may make future professional service robots more capable than ever.
Technological Innovations in Professional Service Robots
For navigation, dexterity and cognition, there are a host of technological developments that show promising signs of solving some of the biggest barriers facing professional service robots. These technologies will help bring professional service robots into the mainstream.
Visual Simultaneous Localization and Mapping (VSLAM)
When it comes to autonomous navigation, one of the most promising technologies is visual simultaneous localization and mapping (VSLAM). Basically, a VSLAM algorithm allows a vision system to map the environment around it while locating itself within that environment. These systems have clear advantages over GPS systems and allow for autonomous navigation and path planning, even in highly dynamic environments, as long as there are multiple vision sensors and some form of data fusion to make sense of the incoming visual data.
Embedded Vision
For dexterity, embedded vision systems play a key role. While this technology is also crucial for autonomous navigation, it can help robots stop operation if an unsafe interaction with a human occurs. Even more importantly, embedded vision systems can give professional service robots a lighter and more accurate grip in applications such as robotic fruit picking. In this scenario, embedded vision can help a robot recognize an object, determine the best way to grasp the object, and successfully move and grasp the object.
Artificial Intelligence
Cognition is the most difficult barrier to overcome for professional service robots, but fortunately, each incremental step yields drastically improved results. Artificial intelligence (AI) and machine learning techniques are used to train robots to more effectively interact with humans. The primary focus of these technologies is in improving natural language processing, which has progressed quickly over the past decade. Leveraging AI, customer service or humanoid robots can intelligently converse with humans, helping guide them around a store or solve a problem with the service they’ve received.
The Future of Professional Service Robots Looks Bright
Some of the most cutting-edge technologies available today are coming together in a way that gives professional service robots more capabilities than ever before. With these and new technologies, robots will be able to autonomously navigate and react to their environment while skillfully carrying out their automation responsibilities and intelligently conversing with humans.
With expanding capabilities, professional service robots will become an increasingly common presence in work spaces around the world. Whether it’s interacting with customers or automating dangerous tasks, professional service robots will be well-equipped to take over a wide range of responsibilities outside of the factory setting, opening up new market growth opportunities

Robots help the workers work more efficiently than before. Today, they are already working in our everyday life and are affecting our life forever. We should be aware that the development and innovation in robots will change how we live forever. Like what we know that manufacturing companies are working with the robots over two decades and it has been more successful. According to the study, in 2014 the robot sales increase 29% with total 229,261 units. So, we should be ready for the change and aware that the robots could have the similar function to humans, may be smarter than the creators as humans.

These 10 robots make life a lot easier.

#1 This suitcase follows you around. Travelmate uses GPS to stay close to your connected smartphone.

#2 Grillbot is like a Roomba for your grill. Just set the timer and let Grillbot go to work.

#3 This machine fixes the worst part about doing laundry. FoldiMate will fold your clothes for you.

#4 Moley Robotics created a robot chef. It does the cooking for you. The robot imitates a chef's exact motions.

#5 Pillo will give you the pills you need. It uses facial recognition to dispense the right pills at the right times.

#6 Temi is a mobile personal assistant robot. It can follow you around and be there when you need it. You can ask Temi questions and use it to make video calls.

#7 The BratWurst Bot can do the grilling for you. It grilled over 200 sausages at a party in Berlin.

#8 Kobi is like a Roomba for your driveway and lawn. It takes care of leaves, snow, and grass maintenance.

#9 The Ohea Smart Bed makes itself. The Ohea Smart Bed makes itself.

#10 Winbot is an automatic window cleaner. You can also steer the Winbot with a remote control.