Рубрика: Robotics

How does Technology change over the years owing to Digital Transformation?

The pace of technology is changing over the years, as remarked in the 20th edition of Accenture’s Tech Vision 2020. Released earlier this year, this report is based on two decades of study, supported by tech trends and their evolution over time. To keep with the competition, it is imperative that enterprises need to embrace technologies concerning their existing investment portfolios.

The report says that artificial intelligence and robotics will be among the key technology trends redefining business parlance over the next three years. The need of the hour for enterprises is to answer the call to rebuild business and technology models from the ground up, keeping in tandem stakeholders’ expectations a priority.

The professional services MNC adds that as technology is adopted more than ever before, and organisations’ attempts to meet its needs and expectations may fall short. The Covid-19 pandemic has open doors to new adaptiveness among enterprises, which requires a new mindset and roadmap to succeed.

The Tech Vision encapsulates a study conducted over a cohort of 6,000 IT and Business executives worldwide. Tech Vision also bring forward the views of 100 Irish executives and directors to discuss the impact of technological change. The study found that 83% of Irish business leaders are recognising disruptive technologies like AI and Robotics which have become an indispensable component of elevating the human experience. Besides, Accenture also surveyed 2,000 consumers from across the world, 70% of whom foresee that their relationship with technology will be strengthening significantly into prominence over the next three years.

David Kirwan, Head of Technology at Accenture in Ireland, echo’s that enterprises must adapt to meet the evolving needs of customers. He says, “Covid-19 is the greatest challenge the world has faced in decades and has transformed people’s lives at an unprecedented scale, impacted every industry and co-opted enterprises’ ambitions for growth and innovation. Companies need to innovate, invent and redefine more quickly than ever before,”.

As enterprises face new challenges across the world, embracing technology the report adds that Apart from Automation, enterprises need to move ahead and brainstorm on use cases on emerging technologies, like Artificial Intelligence. The report concludes that Irish executives look at technology with discretion, with 50% saying that their employees who embrace robotics and automation will be challenged to figure how to adapt to robots as their working assistants and the other 50% saying their employees will find it easier to work with robotics and automation.

With an increase in the number of Coronavirus cases, worldwide more and more people are staying at home, and social distancing becomes the new normal/ Th report concluded that every enterprise must re-think its future through the lens of robotics to ensure its business continuity (BCP) framework in the times of the Pandemic.

The post Amplifying the Innovation Pace with Robotics Automation and Artificial Intelligence appeared first on Analytics Insight.

Robots also referred to as Cobots or co-workers are set to emerge across various industries. The most common of these being industrial robots, working alongside humans helping to pick strawberries in farms to serving at restaurants their applications are limitless. The growth estimates of robotics are encouraging, research estimates forecast that the global industrial robotics market will reach at an astounding US$D101.75 billion by 2026 growing at a CAGR of 11.1%. Analytics Insights brings you the top free online robotics courses in 2020, that help you learn robotics online-

Robotics Foundations I – Robot Modeling

• Offered by- FedericaX Web Learning on edX

• Length– 8 weeks at 8-10 hours per week

This two-part course explains the foundations of robotics. The first part covers robot modelling covering the scenarios of industrial robotics and advanced robotics. You will learn the fundamentals of kinematics, differential kinematics and statics, the inverse kinematics algorithms and the equations of motion of robot manipulators. The course is offered for free, you can add a verified certificate for INR 4,495.

Robotics Foundation II – Robot Control

• Offered by- FedericaX Web Learning on edX

• Length– 12 weeks at 8-16 hours per week

You will learn the trajectory planning algorithms, and joint space and operational space motion control strategies. Besides, the second part of this course will teach you the indirect and direct force control strategies and visual control technique. This course will introduce you to parameter identification algorithms and the features of modelling and control of wheeled mobile robots. The course is offered for free; you can add a verified certificate for INR 4,495.

Robotics

• Offered by- Columbia University on edX

• Length– 10 weeks at 8-16 hours per week

Learn to represent 2D and 3D spatial relationships, homogeneous coordinates to manipulate robot arms like kinematic chains, forward and inverse kinematics, differential kinematics and navigate mobile robots including map representations and motion planning. This course will assist you to plan complete robot systems and develop present and future applications for robots. The course is offered for free; you can add a verified certificate for INR 18,653.

Mechatronics Revolution: Fundamentals and Core Concepts

• Offered by- Georgia Tech on edX

• Length– 16 weeks at 6-8 hours per week

This course lets you recognize and describe the elements of a microcontroller as well as the operating principles of motors, sensors, and circuits commonly used in mechatronic devices. You will learn to create basic programs for microcontrollers using interrupt-driven programming, design and implement microcontroller programs that read from sensors and achieve appropriate actuator commands. The course is offered for free; you can add a verified certificate for INR 11,162.

Introduction to Robotics & Autonomous Car Design

• Offered by- Udemy

• Length– 45min of on-demand video

In this course, you will learn the basics of Robotics, Computer Programming, and Electronics by experimenting with a variety of sensors, motors, and other outputs as well as the Arduino microcontroller. Finally, you will apply the knowledge learnt in Arduino robotics to build and program a two-wheeled autonomous robot. This is an introductory class and no prior knowledge of Robotics, Engineering, or Programming is required.

Robotics Specialization

• Offered by– University of Pennsylvania on Coursera

• Length– 7 months at 4 hours per week

The Introduction to Robotics Specialization introduces you to the concepts of robot flight and movement, how robots perceive their environment, and how they adjust their movements to avoid obstacles, navigate difficult terrains and accomplish complex tasks such as construction and disaster recovery. You will be exposed to real-world examples of how robots find an application into disaster situations, how they have made advances in human health care and what their future capabilities would be. In the final capstone project, you will learn how to program a robot to perform a variety of movements such as flying and grasping objects.

Modern Robotics: Mechanics, Planning, and Control Specialization

• Offered by- Northwestern University on Coursera

• Length– 6 months at 5 hours per week

This Specialization provides a rigorous treatment of spatial motion and the dynamics of rigid bodies, employing representations from modern screw theory and the product of exponentials formula. This course is specially designed for high school first-year students with an engineering background to apply these tools to analysis, planning, and control of robot motion. You will test software on a free state-of-the-art cross-platform robot simulator, to have an authentic robot programming experience with industrial robot manipulators and mobile robots without purchasing expensive robot hardware. This course forms the first part of the six-part specialization in robotics offered in the online format. It is recommended that users take these courses in sequence to have a grasp on the subject.

Control of Mobile Robots

• Offered by- Georgia Tech on Coursera

• Length– 13 hours

Control of Mobile Robots focuses on the application of modern control theory to the problem of making robots move around in safe and effective ways. You will learn the fundamental concepts in mobile robotics. This course covers topics like closed-loop feedback, PID control & its implementation, a state-space form of systems clearly and concisely. Control of mobile robots is an apt course for those who are trying to seek a career in Robotics.

The post Learn Robotics Online- Top Free Online Robotics Courses in 2020 appeared first on Analytics Insight.

Robotics is an exciting technology, that provides automated services in the field of intelligent systems.

Robotic vehicles including unmanned ground, air, and sea vehicles, robotics and automation, intelligent control systems, intelligent manufacturing, intelligent transportation systems, weapon systems are some of the wonder deployments of robotics that have caught the attention of businesses.

Robotic products under development include collaborating with intelligent systems to control complex systems of systems that serve as decision tools for human decision-makers, and autonomous intelligent robots and vehicles for military and civil applications.

The Robotic Edge on Enterprises

• Handling Repetitive Work Processes

Robots are helpful to make repetitive activities much easier, for instance, assembly lines in a factory or collecting large amounts of mundane data, can be boring. Multiple pieces of research have connected mundane tasks associated with negative behaviours and lethargy, thus impacting production capabilities. This holds especially true for rule-based duties that require continuous attention, leaving the manual workforce tired and agitated. Thankfully, robots are a huge relief here, freeing manual labour from drudgeries of the monotonous tasks like weeding, assembly-line micro-tasks, and logistics handling.

• Working in Unpredictable Environments

Robotic sensors, which include highly sensitive microphones and cameras, integrate plug-and-play technologies. When they are combined with the computing power to understand sensor data result in the robots to work in more unpredictable environments. For example, sensor-equipped robots can see from narrow crevices to hear sounds which are too faint for the human ear, or detect harmful air quality.

• Speed and Scalability

Robots are also called as force multipliers capable of dramatically transforming heavy industries like equipment manufacturing. Robots can lift heavy objects more safely and quickly and work with no breaks. A huge advantage to the shrinking workforce in these industries.

Robotics – Business Use Cases

The diversity of robotics applications enables these machines to work in a variety of industries, from manufacturing and design to as diverse as defence and aerospace. Robotics workers are categorised into robotics engineers and robotics technicians. Robotics engineers develop new robotics systems and while also upgrade the old ones. While robotic technicians, on the other hand, maintain and repair already-existing robotics technology.

Inventory

Robots perform a variety of inventory tasks for businesses with deal with large warehouses or sorting facilities. Inventory robots can be driver-less vehicles that are programmed to navigate seamlessly from the warehouse to assembly lines, select specific pieces of merchandise, and bring them to employees for inventory record maintenance into automated systems. Inventory robots offer great potential to save time and also reduce the likelihood of error leading to inconsistencies in inventory tracking.

Marketing

Businesses especially technology companies use robots for display and marketing mechanisms. Robots like Pleo, BigDog, ASIMO and Honda P-Series are showcased at conferences and industry meets to demonstrate the sense of innovation and invention which centre around them. Besides, robots are part of interactive displays at trade shows competing with more traditional marketing tools for the attendee’s attention.

Telecommunications

Telecommunications infrastructure is crucial to every business to communicate with stakeholders, suppliers and customers. Cobots (robots working alongside human beings) can simplify the functioning of call centres and handle bulky volumes of incoming phone or internet traffic to keep the communication channels run smooth. Automated calling robots the telecommunications domain handle pre-recorded calls like customer satisfaction surveys and medical appointment reminders.

Entertainment

Robots are used in business to entertain audiences. Robotic displays are common as theme park attractions and also appear in television and entertainment programs. Some of these robots are so intricately assembled that they resemble very close to real people while others represent mechanical robots from a fictional world (like that in the transformer movie) or fantastical creatures (like WALL-E movie).

Industrial Manufacturing

Industrial Manufacturing is one of the most common tasks which the mechanical robots perform, like assembling products or checking for quality improvements at the conveyer belt. Manufacturing robots handle tasks such as assembly and pick-and-place operations, welding and sorting, at a higher speed than their human counterparts, with chances of error at a bare minimum. ng and sorting, at a higher speed than their human counterparts, with chances of error at a bare minimal.

Robots are here to stay, combining sophisticated, intelligent systems to manoeuvre industries and varied applications without direct human intervention becoming commonplace automated machines that fill our factories and everyday lives with their finesse.

The post Robotic Technologies and Use Cases for Business Deployment appeared first on Analytics Insight.

Automated manufacturing solutions bring unprecedented efficiency, safety and competitive advantage into manufacturing.

Robots have been deployed in manufacturing to fill several rule-based operations. Fully autonomous robots in manufacturing are utilized for high-volume, repetitive processes work which demands speed and accuracy for the process of lifting, holding and moving heavy pieces. Manufacturing robots automate rule-based repetitive tasks, enable a human workforce to shift its focus on more productive and critical areas of operations to reduce error margins to negligible rates.

Here are the manufacturing robots and cobots (collaborative robots that work alongside human beings) to steadfast Industry 4.0-

Articulated Robots

Articulated robots range from the simple two-jointed structures to systems with 10 or more interacting joints and materials. They are powered by a variety of means, including electric motors and are utilised for pick and place, dispensing, packaging, assembling and welding activities. Their multiple points of rotation with some devices give them as high as seven degrees of freedom. Articulated robots can move around obstacles that may block other types of robots and are most commonly used in assembling factories.

Delta Robots

Delta robots also known as parallel or spider robots have force and collision detection sensors, and uses the force sensors for intricate assembly applications. The high-speed delta robots are deployed in the packaging industry, medical and pharmaceutical industry. For its stiffness delta robots also used for surgery, high precision assembly operations for electronic components and 3D printing.

Cartesian Robots

The use of Cartesian or six-axis robots, in particular, is gaining prominence credit to its standardized components, and operator-friendly controls that lower cost and boost performance. Cartesian robots, also called gantry robots, are mechatronic devices that use motors and linear actuators to position a tool.

Cartesian robots can be used for pick-and-place, assembly, and even dispensation of materials such as adhesive. Cartesian-robot movements stay within the framework’s confines, but the framework can be mounted horizontally or vertically, or even overhead in certain gantry configurations.

COBOTs (Collaborative Robots)

The International Federation of Robotics (IFR), collaborative industrial robots (COBOTS) defines cobots to be designed to perform collaborative tasks with humans in industrial sectors in four categories, including in cases where human and robot work from different physical workspaces without any human-robot contact or synchronization.

Sequential cobot collaboration occurs when there is an intersection between the humans and the robot’s workspace.Cobot cooperation occurs when humans and robots work on the same part at the same time, while in responsive cobot cooperation, the robot responds in real-time to the human’s movements.

SCARA Robots

SCARA is an acronym for Selective Compliance Articulated Robot Arm, designed to handle a variety of material handling operations. SCARA was invented in 1978 by Professor Hiroshi Makino at Yamanashi University in Japan. SCARA robots were designed for assembly applications and they have been used in industrial assembly lines since 1981.

Due to their selective compliance, SCARAs are less rigid than Cartesian or gantry robots. However, they are more rigid than both 6-axis robots and Delta robots due to their rigid Z-axis. They are generally faster than 6-axis robots. The payload of SCARAs is generally quite low, but it is more than Delta robots which can lift between 0.3-8 kg. SCARAs are very well suited to high-speed assembly applications.

Robotics in the Future

With rapid advancements in artificial intelligence, machine learning and augmented reality the next generation of robots powered by AI and automation will usher a disruptive innovation of sorts. Research estimates forecast that by 2050, drones will be commonplace in homes, helping with daily chores such as cleaning and gaming.

Are we ready to embrace a scenario where robots will do most of the rule-based manual tasks not just in factories nut in our homes commanding equal rights just like we have?

The post Manufacturing Robots and Cobots to Steadfast Industry 4.0 appeared first on Analytics Insight.

It is not surprising that Automation will change the industry landscape while impacting the employment percentage of the common man. Robots have been replacing humans over the past decades in several countries. While some experts believe that it will lead to a future without work, others are unconvinced of this forecast.

A study co-authored by Daron Acemoglu, an MIT economist and Pascual Restrepo, an assistant professor of economics at Boston University, states the statistics on this trend and how the impact of robots differs by industry and region and may play a notable role in exacerbating income inequality in the USA. According to the study, from the period of 1990 to 2007, the addition of one robot per 1000 workers reduced the national employment-to-population ratio by an average of 0.2 percent. Each addition in manufacturing replaced 3.3 workers on a national level and lowered wages by roughly 0.4 percent. The paper further sheds light on the effect of automation on the business dynamics and labor implications in granular detail.

For the study, both the authors, pooled data on 19 industries listed by the International Federation of Robotics (IFR), a Frankfurt-based industry group that keeps comprehensive statistics on robot deployments worldwide. The professors then combined that with U.S.-based data on population, employment, business, and wages from the U.S. Census Bureau, the Bureau of Economic Analysis, and the Bureau of Labor Statistics, among other sources. They expanded their research by comparing robot deployment in the U.S. to that of other countries.

Surprisingly they found that automation figures in the USA lag behind that of Europe. In the period of 1993 to 2007, U.S. firms did introduce almost exactly one new robot per 1,000 workers; in Europe, firms added 1.6 new robots per 1,000 workers. Hence pointing out that despite being advanced in technological areas, it is far behind many countries with advanced economies, on account of industrial robots’ production and usage and innovation.

In the U.S., the primary adopters of automation were automobile, electronics, plastics and chemical, and metal manufacturing industries. Together these sectors employed 70 percent of robots out of total automation percentage. While automakers contributed to 38 percent of in-use Robots, electronics, plastics, and chemical factored 15% and 10% respectively and 7 percent by metal-based companies. Based on the geographical distinction, Michigan has the highest concentration of workplace robots and employment changes in Detroit, Lansing, and Saginaw than any other commuting zones. While these commuting zones were adversely affected, facing a loss of 6.6 jobs per robot, elsewhere, other industries and citizens were benefitted a lot, thanks to lower goods prices, among other national economic advantages.

Although the scholars did not find any other factor driving unemployment shifts, they did discover the side effects of robots having a direct consequence on income bias. This is because, in such scenarios, it is the low skilled workers and middle-skilled workers who are to bear the weight of it, thus leading to economic and pay differences. This, in turn, proves that automation also has social ramifications other than technological advancement. And this is something that needs immediate attention.

The post Recent Study Identifies how Automation and Employment are Linked appeared first on Analytics Insight.

Robots have extended their personality to make their way out of factories to bring a digital transformation!

Robots or mechanical support systems are programmed to undertake manual rule-based and routine tasks. Safety, speed, productivity contribute to its key USPs. Based on the end usage, robots are classified into service and industrial robots, both contributing to steadfast development.

Decoding Industrial Robots

Industrial robots find their application into manufacturing, they are automated, programmable and capable of movement on three or more axes There are six main types of industrial robot configurations. Each of these types offers a different joint configuration referred to as axes.

• Articulated – Articulated industrial robot design features rotary joints which can range from simple two joint structures to 10 or more joints. An articulated robot’s arm is connected to the base with a twisting joint. Each joint is called an axis which provides an additional degree of freedom, or range of motion. Industrial robots commonly have four or six axes.

• Cartesian – These robots are also called rectilinear or gantry robots. Cartesian robots have three linear joints that use the Cartesian coordinate system (X, Y, and Z), besides having an attached wrist to allow for rotational movement.

• Cylindrical – This robot has at least one rotary joint at the base and at least one prismatic joint to connect the links. Cylindrical robots operate within a cylindrical-shaped work envelope.

• Polar – They are also called spherical robots; in this configuration the arm is connected to the base with a twisting joint and a combination, of two rotary joints and one linear joint.

• SCARA -SCARA are commonly used in assembly applications, this selectively compliant arm for robotic assembly is primarily cylindrical in design. It features two parallel joints that provide compliance in one selected plane.

• Delta – They are spider-like robots which are built from jointed parallelograms connected to a common base. Delta robots are used in the food, pharmaceutical, and electronic industries, curtest their capability of delicate and precise movements.

The Growth of Industrial Robots

Industrial robots are deployed in rule-based tasks which require high endurance, speed, and precision. They find their applications in pick and place, palletizing, product inspection, testing, welding, painting, ironing and assembly lines. The most famous brands for industrial automation robots are Brands- Fanuc, Motoman, ABB, Kuka, Denso, Adept, Comau and Kawasaki. Analytics Insights estimates that the growth of industrial robots will witness an upward increase, finding their application into Automotive, Food & Beverage, Electronics, and Metal and Machinery. The automotive domain is poised to capture the highest market revenue generation from US$17.1 billion to US$26.3 billion at a CAGR of 10.6%.

Industrial Robot Market Revenue Generation Estimates- by Analytics Insight

By End User	2020	2023
Industrial Robot
Automotive	17.1	26.3
Food and Beverage	2.8	3.7
Electronics	9.6	14.9
Metals and Machinery	6.8	8.9
Others	2.4	3.0
Total	38.8	56.8

The Rise of Service Robots

Service Robots are ideal for performing useful tasks for humans. As the name suggests, they are autonomous or semi-autonomous robots intended to interact with people and are typically deployed in retail, hospitality, healthcare, warehouse, space and defence, agricultural applications, and demolition to automate dangerous or laborious tasks.

Analytics Insights estimates that by 2021, the professional service robotic market revenues are predicted to reach US$14.5 billion. Enterprises are looking ahead to leverage the benefits of these wonder machines to automate safety, efficiency and productivity processes. Safety is an important consideration for service robots for handling dangerous jobs where human workers would be in danger. Enterprises rely heavily on service robots to improve efficiency working as inspection robots and cleaning robots credited for their low downtimes and improved cost of labour.

Nestlé relies on its humanoid robot, called Pepper, in numerous Japanese department stores to sell coffee makers. Pepper understands about 80% of the human conversations and uses the information it learns to help customers. Customers can go to a Robofusion kiosk and order ice cream. After customers choose what they want using a touchscreen, robotic dispensers serve the frozen treat with toppings without any human supervision.

Companies like Cobalt and Knightscope are leasing out security robots. They can travel around corporate offices and are equipped with heat sensors, facial detection and employee badge scanners. These service robots move autonomously, watching for signs of trouble, like an unauthorized person entering the building.

In the future, as the demand increases, both industrial and service robots will become more incorporated into every facet of enterprises and the service industry to bring about a new era in automation, are you and your enterprise ready for this change?

The post Leveraging Service Robots and Industrial Robots for Industry 4.0 appeared first on Analytics Insight.

What skills you will need to compete with the Robots in case they take away 50 million jobs in the next decade?

We had of late debated how will be the impact of Robotics in the employment scenario, and what will happen in case they take away our rule-based jobs, leaving the human labour in quandary. The fear of the unknown has taken unprecedented numbers- automation puts 51 million jobs at risk over the next decade.

Recent research from McKinsey suggests that over 90 million workers across Europe accounting to about 40% of the total workforce may have to significantly develop new skills within their current roles in the coming decade if they aim to stay competitive against robots. The report points that nearly all of the current European employees will face a challenge as robotics takes up most of the rule-based and repetitive jobs. However, though the statistics seem scary, the reports suggest that there is no need to worry, and fast conclusions must not be drawn. The trends and analysis point that the employment growth in other sectors will largely compensate for total job loss.

Addressing the Robotics Skill Gap

A lot may happen in the coming decade if we take into account the impact of Robotics over the next decade. The massive growth of technologies will pave the way for new employment trends, letting Europe discover itself in short of six million employees by 2030. This will be marked with the emerging of new alternatives in fields that need professional expertise. Add to the fact McKinsey anticipates that discovering adequate employees who can fill on the job roles created on the continent will prove to be difficult.

The surge will be seen in case of megacities like London and Paris which will fall short of answering to the call with too few residents certified to fill them. The report pointed out that in areas of dynamic development, less than 60% of the recent jobs will probably be taken up by an adequately skilled employee.

Compensating for the Job Loss

The report points out that almost all of the European workers will face some degree of change, due to technology transformation. Although the statistics seemingly feed into a common fear that robots will be taking over our jobs, although we cannot draw quick conclusions at the present. The research also shows that employment growth in other sectors will largely compensate for the overall job loss.

Though the up-skilling and re-training of the workforce will soar to the highest of to-do listing for enterprise leaders over some years a pattern which has been increasingly accelerated by the COVID-19 disaster. McKinsey’s report further suggests that the present roles which are mostly in danger from automation increasingly add to the burden making the workforce highly susceptible to the transformation.

The Workforce Displacement

The three sectors which are more prone to the ongoing tide remains meals companies, customer support and gross sales and construction segments. These work sectors can most certainly displace due to the automation upsurge and now, at the onset of the disaster.

The question remains, where we can look to finding these “rising occupations”?

Manufacturing and agriculture are the two sectors which are losing the race in favour of automation. Particularly, McKinsey analysts point out that the demand for socio-emotional abilities will develop. Human beings will concentrate on roles which cannot be fulfilled by the humans increasingly requiring the technological interplays, in particular caregiving, instructing and coaching, in addition to managing others.

Equally, some new alternatives that include reskilling and knowledge capability addition may emerge to allow a smoother transition for employees as we look ahead in the future. The rise of “cobots” (or collaborative robots) which are specifically designed to simplify the usage of automation for human workers will usher the new revolution. The future is not so far where it could appear that robots are coming to the office as our next-generation co-workers.

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How the humankind must answer to the dark side of Robotics powered by AI?

About 78 years ago, back in the year, 1942 sci-fi legend Isaac Asimov laid out the popularly known Asimov’s Laws, a set of principles which the robots should follow for the future applications, these include-

• A robot may not injure a human being or, through inaction, allow a human being to come to harm.

• A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.

• A robot must protect its existence as long as such protection does not conflict with the First or Second Laws.

Unfortunately, the first rule has been broken a lot of times, causing concerns about the dangers of Automation.

The gravest threat arises from the co-working Robots also called as the Cobots, who work in tandem with the human hands. This is no exaggeration, the US Department of Labor which keeps a track of robotic injuries to the workforce, lists out serious injuries in 38 pages which are caused by robotic malfunction, and that not include the manual dangers of hacking.

The insecure software systems are no help, regularly attacked by a growing number of hackers who take advantage of insecure software systems to manipulate robot programming to turn on the dark side of Robotics. In his book When Robots Kill, law professor Gabriel Hallevy discusses the criminal liability that arises from the perils of AI infiltrating the commercial, industrial, military, medical, and personal spheres.

The Threat from Robotics

Robots, when taken as those, AI-powered devices who have arms, legs or wheels, are also ramifications of kinetic IoT devices that, if hacked, can pose new serious threats that the humankind has never encountered before.

The vulnerabilities associated with Robotics will surely multiply as more investment flocks into the start-up market. Analytics Insight estimates that investments in robotics will reach new heights growing from US$34.6 billion to US$57.9 for the forecasted period spanning from 2020 to 2023 growing at a CAGR of 13.2%.

Dark Side of Robotics

Experts categorise the dark side of Robotics falling within the following parameters:

• Privacy concerns

• Weak default configuration

• Vulnerable open robot frameworks and libraries

• Insecure communications

• Authentication issues

• Missing authorization

• Weak cryptography

Here are cases when Robotics has chosen to be on the darker side of humanity-

July 4, 1981

• Who: Kenji Urada, a 37-year-old maintenance worker

• Where: Kawasaki Heavy Industries plant (Akashi, Japan)

• What happened: When a robot in Kawasaki’s state-of-the-art facility malfunctioned, Urada opened the safety barrier (an action that should’ve automatically powered down the machine), and attempted to fix the issue. The robot turned back on, stabbed Urada in the back with its arm, then crushed him.
An investigation found that many Japanese factories had a “tendency to put aside regulations” when it came to exciting new robots. The offending machine was removed from the factory and more secure fences were erected.

July 21, 2009

• Who: Ana Maria Vital, a 40-year-old factory worker

• Where: Golden State Foods (Industry, California-based meat supplier)

• What happened: Vital was overseeing a palletizer robot, a giant machine that stacked boxes. A box become stuck, and Vital entered the robot’s “cage” to pull it out — but when she did, the robot mistook her for a box and grabbed her, crushing her torso. The robot had supposedly been equipped with sensors to differentiate humans from boxes, but they had failed.

July 7, 2015

• Who: Wanda Holbrook, a 57-year-old factory technician

• Where: Ventra Ionia (Ionia, Michigan-based auto assembly factory)

• What happened: Holbrook was fixing a piece of machinery when a factory robot went “rogue.” According to a lawsuit, the robot’s arm “took [Holbrook] by surprise,” entered the section she was working in (against programming commands), and “crushed her head between a hitch assembly it was attempting to place.” She died 40 minutes later.

While laying down the principles or guidelines for Robotics, Asimov, of course, couldn’t have imagined the powers which an Automated Robot could have unleashed credit to the AI capabilities that make these machines even stronger. Killer Robots seems to suggest, especially in the context of situations like police robotics, where automatons are used to kill or apprehend suspected criminals, as well as retrieve bombs and protect citizens.

But as Killer Robots suggests, it’s next to impossible to try and prevent the misuse of robots. As long as they’re made by humans, and therefore not as smart as humans, it’s reasonable to expect there will be some hurdles to cross some much bigger than others.

The post The Perils of AI- Can Robotics be Programmed to Kill Humans? appeared first on Analytics Insight.

Could robotic birds be the drone and aircraft technology mainstream?

For a large number of years, flying creatures have been an interest to mankind, creating a motivation to touch the skies. It is a miracle how a little animal can impact people to plan such flying machines. Once again, humankind has turned to these winged animals for advancement.

The great thing about robots is that they are available today in all shapes and sizes. You never anticipate what can be a robot in today’s time. Robotic birds are the new age robots which are set to be a major upgrade to the drone and aircraft technology.

If ground robots are currently enriched with cutting edge self-sufficient capacities, permitting them to keep away from hindrances, to construct inner guides of their environment, to pick the best activity to try whenever, their flying counterparts are a long way from displaying such capacities, and an immediate application of methods created for ground robots is troublesome. In this way, the plan and control of winged animal-like robots have been drawing much consideration of numerous scientists and researchers.

The bird models and applications are very distinct, yet there’s one thing the researchers concur on—the fact that it is so hard to demonstrate a bird’s flight. For instance, the birds’ wing developments are perplexing to the point that so far present-day science hasn’t had the option to instantly portray them utilizing various methods and scientific conditions.

Everything about a bird is made for flight and this explanation; the kinematic and dynamic designing of birdlike robots is more elaborated than that of sequential robots. Along these lines, to develop a mechanical robotic bird, we first need to execute a computer stimulation thinking about each single physical and dynamical perspective.

To think of this flying gadget, scientists around the world widely consider and study the bird’s flight designs, wing shapes, feather dynamics, etc. They became more acquainted with that with a straightforward flick of the wrist and finger, birds can move their feathers.

Their new structure highlights programmable wings that can be controlled freely, similar to real bird wings, taking into consideration high-speed jumps, rolls, and other aerial trapeze artistry. The robotic birds today come in different shapes and sizes taking into consideration the aerodynamics of each model, yet its motion is exceedingly realistic. So realistic indeed, that some robotic birds have even tricked nature – a few early models were destroyed by falcons.

The development of flying models should follow the standards of uniformity, brevity, and vigour. In this way, the wooden framework, given to its low thickness and the tremendous ease which it very well may be worked out, is one of the essential materials in the development of flying models. A fundamental part of the bird is the wing. It is answerable for producing the powers that will raise the flying creature of the ground. It’s in the development of the wing, therefore, that becomes fundamental to analyze and needs special care and attention.

One such famous example of a robotic bird is the ‘PigeonBot’. Presently, utilizing new insights into precisely how pigeons’ joints control the spread of their wing feathers, experts have constructed an automated pigeon, named PigeonBot, whose feathered wings change shape like the real animal. This research paves the way for creating more agile aircraft in the future.

Airplanes have unbending arrangements of wings and drones have rotational advancements that are very tricky. With this innovation, they would now be able to have a lightweight body. This, in turn, can lead to lesser fuel utilization.

With birdlike wings, these airborne machines could make more tight turns in jumbled spaces, for example, around structures or in woods, and could more readily explore harsh air. Several other robotic birds are designed contrastively based on different movements of the birds. Since it is a little hard to unravel the complex movements of the flying animals there is always scope for improvement.

Because of its sturdy structure, there is likelihood that it very well may be utilized for spying purposes by the military. This plan may likewise discover use in delivery services as well.

It’s energizing to feel that the avian world despite everything has a lot to educate us. We despite everything endeavour to catch the world as experienced by flying creatures – the way they so carefully move meticulously the skies, see the ground, and distinguish the undetectable powers that encompass us.

New studies, joined with new manufacturing advances, is presenting to us somewhat closer to the day when the recognizable planes and scaring drones filling our skies will be reinstated by self-sufficient, normally flying, all-seeing, mechanical robotic birds. Despite hundreds of years of examination, we’ve just barely begun to open the mysteries that nature idealized overages.

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Welcome to an Age where AI meets the machine world.

Artificial intelligence is en route to changing all industries and the robotics industry is not an exception. Presently, the innovative combination of AI and robotics has created a number of futuristic possibilities, in all the industry domains. While most of us will agree that most robots will be humanoids in 10 years from now; in many environments, robots are designed to emulate a range of behaviors and physical abilities will reflect a best fit for those characteristics. An exception will likely be robots that provide medical or other care or companionship for humans, and perhaps service robots that are meant to establish a more personal and ‘humanized’ relationship. Here are how the different technologies, combining AI will bring a difference to Robotics-

Computer Vision

Though related, some would argue that the correct term is machine vision or robot vision rather than computer vision, because “robots seeing” involves more than just computer algorithms; engineers and roboticists also have to account for camera hardware that allow robots to process physical data. Robot vision is very closely linked to machine vision, which can be given credit for the emergence of robot guidance and automatic inspection systems.

Imitation Learning

Imitation learning is closely related to observational learning, a behaviour exhibited by infants and toddlers. Imitation learning is also an umbrella category for reinforcement learning, or the challenge of getting an agent to act in the world so as to maximize its rewards. Bayesian or probabilistic models are a common feature of this machine learning approach. The question of whether imitation learning could be used for humanoid-like robots was postulated as far back as 1999.

Self-Supervised Learning

Self-supervised learning approaches enable robots to generate their own training examples in order to improve performance; this includes using a priori training and data captured close range to interpret “long-range ambiguous sensor data.” It’s been incorporated into robots and optical devices that can detect and reject objects (dust and snow, for example); identify vegetables and obstacles in rough terrain; and in 3D-scene analysis and modeling vehicle dynamics

Watch-Bot is a concrete example, created by researchers from Cornell and Stanford, that uses a 3D sensor (a Kinect), a camera, laptop and laser pointer to detect ‘normal human activity’, which are patterns that it learns through probabilistic methods. Watch-Bot uses a laser pointer to target the object as a reminder (for example, the milk that was left out of the fridge). In initial tests, the bot was able to successfully remind humans 60 percent of time, and the researchers expanded trials by allowing its robot to learn from online videos (called project RoboWatch).

Other examples of self-supervised learning methods applied in robotics include a road detection algorithm in a front-view monocular camera with a road probabilistic distribution model (RPDM) and fuzzy support vector machines (FSVMs), designed at MIT for autonomous vehicles and other mobile on-road robots.

Assistive and Medical Technologies

An assistive robot (according to Stanford’s David L. Jaffe) is a device that can sense, process sensory information, and perform actions that benefit people with disabilities and seniors (though smart assistive technologies also exist for the general population, such as driver assistance tools). Movement therapy robots provide a diagnostic or therapeutic benefit. Both of these are technologies that are largely (and unfortunately) still confined to the lab, as they’re still cost-prohibitive for most hospitals in the U.S. and abroad.

Early examples of assistive technologies included the DeVAR, or desktop vocational assistant robot, developed in the early 1990s by Stanford and the Palo Alto Veterans Affairs Rehabilitation Research and Development. More recent examples of machine learning-based robotic assistive technologies are being developed that include combining assistive machines with more autonomy, such as the MICO robotic arm (developed at Northwester University) that observes the world through a Kinect Sensor. The implications are more complex yet smarter assistive robots that adapt more readily to user needs but also require partial autonomy (i.e. a sharing of control between the robot and human).

Multi-Agent Learning

Coordination and negotiation are key components of multi-agent learning, which involves machine learning-based robots (or agents – this technique has been widely applied to games) that are able to adapt to a shifting landscape of other robots/agents and find “equilibrium strategies.” Examples of multi-agent learning approaches include no-regret learning tools, which involve weighted algorithms that “boost” learning outcomes in multi-agent planning, and learning in market-based, distributed control systems.

A more concrete example is an algorithm for distributed agents or robots created by researchers from MIT’s Lab for Information and Decision Systems in late 2014. Robots collaborated to build a better and more inclusive learning model than could be done with one robot, based on the concept of exploring a building and its room layouts and autonomously building a knowledge base.

The Futuristic Outlook

The above, brief outline of machine-learning based approaches in robotics, combined with contracts and challenges put out by powerful military sponsors (e.g. DARPA, ARL); innovations by major robotics manufacturers (e.g. Silicon Valley Robotics) and start-up manufacturers (Mayfield Robotics); and increased investments by a barrage of auto-manufacturers (from Toyota to BMW) on a next generation of autonomous vehicles (to name a few influential domains), point to the trend of machine learning as a long-term priority.

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