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#430734 Why XPRIZE Is Asking Writers to Take Us ...

In a world of accelerating change, educating the public about the implications of technological advancements is extremely important. We can continue to write informative articles and speculate about the kind of future that lies ahead. Or instead, we can take readers on an immersive journey by using science fiction to paint vivid images of the future for society.
The XPRIZE Foundation recently announced a science fiction storytelling competition. In recent years, the organization has backed and launched a range of competitions to propel innovation in science and technology. These have been aimed at a variety of challenges, such as transforming the lives of low-literacy adults, tackling climate change, and creating water from thin air.
Their sci-fi writing competition asks participants to envision a groundbreaking future for humanity. The initiative, in partnership with Japanese airline ANA, features 22 sci-fi stories from noteworthy authors that are now live on the website. Each of these stories is from the perspective of a different passenger on a plane that travels 20 years into the future through a wormhole. Contestants will compete to tell the story of the passenger in Seat 14C.
In addition to the competition, XPRIZE has brought together a science fiction advisory council to work with the organization and imagine what the future will look like. According to Peter Diamandis, founder and executive chairman, “As the future becomes harder and harder to predict, we look forward to engaging some of the world’s most visionary storytellers to help us imagine what’s just beyond the horizon and chart a path toward a future of abundance.”
The Importance of Science Fiction
Why is an organization like XPRIZE placing just as much importance on fiction as it does on reality? As Isaac Asimov has pointed out, “Modern science fiction is the only form of literature that consistently considers the nature of the changes that face us.” While the rest of the world reports on a new invention, sci-fi authors examine how these advancements affect the human condition.
True science fiction is distinguished from pure fantasy in that everything that happens is within the bounds of the physical laws of the universe. We’ve already seen how sci-fi can inspire generations and shape the future. 3D printers, wearable technology, and smartphones were first seen in Star Trek. Targeted advertising and air touch technology was first seen in Philip K. Dick’s 1958 story “The Minority Report.” Tanning beds, robot vacuums, and flatscreen TVs were seen in The Jetsons. The internet and a world of global instant communication was predicted by Arthur C. Clarke in his work long before it became reality.
Sci-fi shows like Black Mirror or Star Trek aren’t just entertainment. They allow us to imagine and explore the influence of technology on humanity. For instance, how will artificial intelligence impact human relationships? How will social media affect privacy? What if we encounter alien life? Good sci-fi stories take us on journeys that force us to think critically about the societal impacts of technological advancements.
As sci-fi author Yaasha Moriah points out, the genre is universal because “it tackles hard questions about human nature, morality, and the evolution of society, all through the narrative of speculation about the future. If we continue to do A, will it necessarily lead to problems B and C? What implicit lessons are being taught when we insist on a particular policy? When we elevate the importance of one thing over another—say, security over privacy—what could be the potential benefits and dangers of that mentality? That’s why science fiction has such an enduring appeal. We want to explore deep questions, without being preached at. We want to see the principles in action, and observe their results.”
An Extension of STEAM Education
At its core, this genre is a harmonious symbiosis between two distinct disciplines: science and literature. It is an extension of STEAM education, an educational approach that combines science, technology, engineering, the arts, and mathematics. Story-telling with science fiction allows us to use the arts in order to educate and engage the public about scientific advancements and its implications.
According to the National Science Foundation, research on art-based learning of STEM, including the use of narrative writing, works “beyond expectation.” It has been shown to have a powerful impact on creative thinking, collaborative behavior and application skills.
What does it feel like to travel through a wormhole? What are some ethical challenges of AI? How could we terraform Mars? For decades, science fiction writers and producers have answered these questions through the art of storytelling.
What better way to engage more people with science and technology than through sparking their imaginations? The method makes academic subject areas many traditionally perceived as boring or dry far more inspiring and engaging.
A Form of Time Travel
XPRIZE’s competition theme of traveling 20 years into the future through a wormhole is an appropriate beacon for the genre. In many ways, sci-fi is a precautionary form of time travel. Before we put a certain technology, scientific invention, or policy to use, we can envision and explore what our world would be like if we were to do so.
Sci-fi lets us explore different scenarios for the future of humanity before deciding which ones are more desirable. Some of these scenarios may be radically beyond our comfort zone. Yet when we’re faced with the seemingly impossible, we must remind ourselves that if something is within the domain of the physical laws of the universe, then it’s absolutely possible.
Stock Media provided by NASA_images / Pond5 Continue reading

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#430668 Why Every Leader Needs to Be Obsessed ...

This article is part of a series exploring the skills leaders must learn to make the most of rapid change in an increasingly disruptive world. The first article in the series, “How the Most Successful Leaders Will Thrive in an Exponential World,” broadly outlines four critical leadership skills—futurist, technologist, innovator, and humanitarian—and how they work together.
Today’s post, part five in the series, takes a more detailed look at leaders as technologists. Be sure to check out part two of the series, “How Leaders Dream Boldly to Bring New Futures to Life,” part three of the series, “How All Leaders Can Make the World a Better Place,” and part four of the series, “How Leaders Can Make Innovation Everyone’s Day Job”.
In the 1990s, Tower Records was the place to get new music. Successful and popular, the California chain spread far and wide, and in 1998, they took on $110 million in debt to fund aggressive further expansion. This wasn’t, as it turns out, the best of timing.
The first portable digital music player went on sale the same year. The following year brought Napster, a file sharing service allowing users to freely share music online. By 2000, Napster hosted 20 million users swapping songs. Then in 2001, Apple’s iPod and iTunes arrived, and when the iTunes Music Store opened in 2003, Apple sold over a million songs the first week.
As music was digitized, hard copies began to go out of style, and sales and revenue declined.
Tower first filed for bankruptcy in 2004 and again (for the last time) in 2006. The internet wasn’t the only reason for Tower’s demise. Mismanagement and price competition from electronics retailers like Best Buy also played a part. Still, today, the vast majority of music is purchased or streamed entirely online, and record stores are for the most part a niche market.
The writing was on the wall, but those impacted most had trouble reading it.
Why is it difficult for leaders to see technological change coming and right the ship before it’s too late? Why did Tower go all out on expansion just as the next big thing took the stage?
This is one story of many. Digitization has moved beyond music and entertainment, and now many big retailers operating physical stores are struggling to stay relevant. Meanwhile, the pace of change is accelerating, and new potentially disruptive technologies are on the horizon.
More than ever, leaders need to develop a strong understanding of and perspective on technology. They need to survey new innovations, forecast their pace, gauge the implications, and adopt new tools and strategy to change course as an industry shifts, not after it’s shifted.
Simply, leaders need to adopt the mindset of a technologist. Here’s what that means.
Survey the Landscape
Nurturing curiosity is the first step to understanding technological change. To know how technology might disrupt your industry, you have to know what’s in the pipeline and identify which new inventions are directly or indirectly related to your industry.
Becoming more technologically minded takes discipline and focus as well as unstructured time to explore the non-obvious connections between what is right in front of us and what might be. It requires a commitment to ongoing learning and discovery.
Read outside your industry and comfort zone, not just Fast Company and Wired, but Science and Nature to expand your horizons. Identify experts with the ability to demystify specific technology areas—many have a solid following on Twitter or a frequently cited blog.
But it isn’t all about reading. Consider going where the change is happening too.
Visit one of the technology hubs around the world or a local university research lab in your own back yard. Or bring the innovation to you by building an internal exploration lab stocked with the latest technologies, creating a technology advisory board, hosting an internal innovation challenge, or a local pitch night where aspiring entrepreneurs can share their newest ideas.
You might even ask the crowd by inviting anyone to suggest what innovation is most likely to disrupt your product, service, or sector. And don’t hesitate to engage younger folks—the digital natives all around you—by asking questions about what technology they are using or excited about. Consider going on a field trip with them to see how they use technology in different aspects of their lives. Invite the seasoned executives on your team to explore long-term “reverse mentoring” with someone who can expose them to the latest technology and teach them to use it.
Whatever your strategy, the goal should be to develop a healthy obsession with technology.
By exploring fresh perspectives outside traditional work environments and then giving ourselves permission to see how these new ideas might influence existing products and strategies, we have a chance to be ready for what we’re not ready for—but is likely right around the corner.
Estimate the Pace of Progress
The next step is forecasting when a technology will mature.
One of the most challenging aspects of the changes underway is that in many technology arenas, we are quickly moving from a linear to an exponential pace. It is hard enough to envision what is needed in an industry buffeted by progress that is changing 10% per year, but what happens when technological progress doubles annually? That is another world altogether.
This kind of change can be deceiving. For example, machine learning and big data are finally reaching critical momentum after more than twenty years of being right around the corner. The advances in applications like speech and image recognition that we’ve seen in recent years dwarf what came before and many believe we’ve just begun to understand the implications.
Even as we begin to embrace disruptive change in one technology arena, far more exciting possibilities unfold when we explore how multiple arenas are converging.
Artificial intelligence and big data are great examples. As Hod Lipson, professor of Mechanical Engineering and Data Science at Columbia University and co-author of Driverless: Intelligent Cars and the Road Ahead, says, “AI is the engine, but big data is the fuel. They need each other.”
This convergence paired with an accelerating pace makes for surprising applications.
To keep his research lab agile and open to new uses of advancing technologies, Lipson routinely asks his PhD students, “How might AI disrupt this industry?” to prompt development of applications across a wide spectrum of sectors from healthcare to agriculture to food delivery.
Explore the Consequences
New technology inevitably gives rise to new ethical, social, and moral questions that we have never faced before. Rather than bury our heads in the sand, as leaders we must explore the full range of potential consequences of whatever is underway or still to come.
We can add AI to kids’ toys, like Mattel’s Hello Barbie or use cutting-edge gene editing technology like CRISPR-Cas9 to select for preferred gene sequences beyond basic health. But just because we can do something doesn’t mean we should.
Take time to listen to skeptics and understand the risks posed by technology.
Elon Musk, Stephen Hawking, Steve Wozniak, Bill Gates, and other well-known names in science and technology have expressed concern in the media and via open letters about the risks posed by AI. Microsoft’s CEO, Satya Nadella, has even argued tech companies shouldn’t build artificial intelligence systems that will replace people rather than making them more productive.
Exploring unintended consequences goes beyond having a Plan B for when something goes wrong. It requires broadening our view of what we’re responsible for. Beyond customers, shareholders, and the bottom line, we should understand how our decisions may impact employees, communities, the environment, our broader industry, and even our competitors.
The minor inconvenience of mitigating these risks now is far better than the alternative. Create forums to listen to and value voices outside of the board room and C-Suite. Seek out naysayers, ethicists, community leaders, wise elders, and even neophytes—those who may not share our preconceived notions of right and wrong or our narrow view of our role in the larger world.
The question isn’t: If we build it, will they come? It’s now: If we can build it, should we?
Adopt New Technologies and Shift Course
The last step is hardest. Once you’ve identified a technology (or technologies) as a potential disruptor and understand the implications, you need to figure out how to evolve your organization to make the most of the opportunity. Simply recognizing disruption isn’t enough.
Take today’s struggling brick-and-mortar retail business. Online shopping isn’t new. Amazon isn’t a plucky startup. Both have been changing how we buy stuff for years. And yet many who still own and operate physical stores—perhaps most prominently, Sears—are now on the brink of bankruptcy.
There’s hope though. Netflix began as a DVD delivery service in the 90s, but quickly realized its core business didn’t have staying power. It would have been laughable to stream movies when Netflix was founded. Still, computers and bandwidth were advancing fast. In 2007, the company added streaming to its subscription. Even then it wasn’t a totally compelling product.
But Netflix clearly saw a streaming future would likely end their DVD business.
In recent years, faster connection speeds, a growing content library, and the company’s entrance into original programming have given Netflix streaming the upper hand over DVDs. Since 2011, DVD subscriptions have steadily declined. Yet the company itself is doing fine. Why? It anticipated the shift to streaming and acted on it.
Never Stop Looking for the Next Big Thing
Technology is and will increasingly be a driver of disruption, destabilizing entrenched businesses and entire industries while also creating new markets and value not yet imagined.
When faced with the rapidly accelerating pace of change, many companies still default to old models and established practices. Leading like a technologist requires vigilant understanding of potential sources of disruption—what might make your company’s offering obsolete? The answers may not always be perfectly clear. What’s most important is relentlessly seeking them.
Stock Media provided by MJTierney / Pond5 Continue reading

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#430658 Why Every Leader Needs a Healthy ...

This article is part of a series exploring the skills leaders must learn to make the most of rapid change in an increasingly disruptive world. The first article in the series, “How the Most Successful Leaders Will Thrive in an Exponential World,” broadly outlines four critical leadership skills—futurist, technologist, innovator, and humanitarian—and how they work together.
Today’s post, part five in the series, takes a more detailed look at leaders as technologists. Be sure to check out part two of the series, “How Leaders Dream Boldly to Bring New Futures to Life,” part three of the series, “How All Leaders Can Make the World a Better Place,” and part four of the series, “How Leaders Can Make Innovation Everyone’s Day Job”.
In the 1990s, Tower Records was the place to get new music. Successful and popular, the California chain spread far and wide, and in 1998, they took on $110 million in debt to fund aggressive further expansion. This wasn’t, as it turns out, the best of timing.
The first portable digital music player went on sale the same year. The following year brought Napster, a file sharing service allowing users to freely share music online. By 2000, Napster hosted 20 million users swapping songs. Then in 2001, Apple’s iPod and iTunes arrived, and when the iTunes Music Store opened in 2003, Apple sold over a million songs the first week.
As music was digitized, hard copies began to go out of style, and sales and revenue declined.
Tower first filed for bankruptcy in 2004 and again (for the last time) in 2006. The internet wasn’t the only reason for Tower’s demise. Mismanagement and price competition from electronics retailers like Best Buy also played a part. Still, today, the vast majority of music is purchased or streamed entirely online, and record stores are for the most part a niche market.
The writing was on the wall, but those impacted most had trouble reading it.
Why is it difficult for leaders to see technological change coming and right the ship before it’s too late? Why did Tower go all out on expansion just as the next big thing took the stage?
This is one story of many. Digitization has moved beyond music and entertainment, and now many big retailers operating physical stores are struggling to stay relevant. Meanwhile, the pace of change is accelerating, and new potentially disruptive technologies are on the horizon.
More than ever, leaders need to develop a strong understanding of and perspective on technology. They need to survey new innovations, forecast their pace, gauge the implications, and adopt new tools and strategy to change course as an industry shifts, not after it’s shifted.
Simply, leaders need to adopt the mindset of a technologist. Here’s what that means.
Survey the Landscape
Nurturing curiosity is the first step to understanding technological change. To know how technology might disrupt your industry, you have to know what’s in the pipeline and identify which new inventions are directly or indirectly related to your industry.
Becoming more technologically minded takes discipline and focus as well as unstructured time to explore the non-obvious connections between what is right in front of us and what might be. It requires a commitment to ongoing learning and discovery.
Read outside your industry and comfort zone, not just Fast Company and Wired, but Science and Nature to expand your horizons. Identify experts with the ability to demystify specific technology areas—many have a solid following on Twitter or a frequently cited blog.
But it isn’t all about reading. Consider going where the change is happening too.
Visit one of the technology hubs around the world or a local university research lab in your own back yard. Or bring the innovation to you by building an internal exploration lab stocked with the latest technologies, creating a technology advisory board, hosting an internal innovation challenge, or a local pitch night where aspiring entrepreneurs can share their newest ideas.
You might even ask the crowd by inviting anyone to suggest what innovation is most likely to disrupt your product, service, or sector. And don’t hesitate to engage younger folks—the digital natives all around you—by asking questions about what technology they are using or excited about. Consider going on a field trip with them to see how they use technology in different aspects of their lives. Invite the seasoned executives on your team to explore long-term “reverse mentoring” with someone who can expose them to the latest technology and teach them to use it.
Whatever your strategy, the goal should be to develop a healthy obsession with technology.
By exploring fresh perspectives outside traditional work environments and then giving ourselves permission to see how these new ideas might influence existing products and strategies, we have a chance to be ready for what we’re not ready for—but is likely right around the corner.
Estimate the Pace of Progress
The next step is forecasting when a technology will mature.
One of the most challenging aspects of the changes underway is that in many technology arenas, we are quickly moving from a linear to an exponential pace. It is hard enough to envision what is needed in an industry buffeted by progress that is changing 10% per year, but what happens when technological progress doubles annually? That is another world altogether.
This kind of change can be deceiving. For example, machine learning and big data are finally reaching critical momentum after more than twenty years of being right around the corner. The advances in applications like speech and image recognition that we’ve seen in recent years dwarf what came before and many believe we’ve just begun to understand the implications.
Even as we begin to embrace disruptive change in one technology arena, far more exciting possibilities unfold when we explore how multiple arenas are converging.
Artificial intelligence and big data are great examples. As Hod Lipson, professor of Mechanical Engineering and Data Science at Columbia University and co-author of Driverless: Intelligent Cars and the Road Ahead, says, “AI is the engine, but big data is the fuel. They need each other.”
This convergence paired with an accelerating pace makes for surprising applications.
To keep his research lab agile and open to new uses of advancing technologies, Lipson routinely asks his PhD students, “How might AI disrupt this industry?” to prompt development of applications across a wide spectrum of sectors from healthcare to agriculture to food delivery.
Explore the Consequences
New technology inevitably gives rise to new ethical, social, and moral questions that we have never faced before. Rather than bury our heads in the sand, as leaders we must explore the full range of potential consequences of whatever is underway or still to come.
We can add AI to kids’ toys, like Mattel’s Hello Barbie or use cutting-edge gene editing technology like CRISPR-Cas9 to select for preferred gene sequences beyond basic health. But just because we can do something doesn’t mean we should.
Take time to listen to skeptics and understand the risks posed by technology.
Elon Musk, Stephen Hawking, Steve Wozniak, Bill Gates, and other well-known names in science and technology have expressed concern in the media and via open letters about the risks posed by AI. Microsoft’s CEO, Satya Nadella, has even argued tech companies shouldn’t build artificial intelligence systems that will replace people rather than making them more productive.
Exploring unintended consequences goes beyond having a Plan B for when something goes wrong. It requires broadening our view of what we’re responsible for. Beyond customers, shareholders, and the bottom line, we should understand how our decisions may impact employees, communities, the environment, our broader industry, and even our competitors.
The minor inconvenience of mitigating these risks now is far better than the alternative. Create forums to listen to and value voices outside of the board room and C-Suite. Seek out naysayers, ethicists, community leaders, wise elders, and even neophytes—those who may not share our preconceived notions of right and wrong or our narrow view of our role in the larger world.
The question isn’t: If we build it, will they come? It’s now: If we can build it, should we?
Adopt New Technologies and Shift Course
The last step is hardest. Once you’ve identified a technology (or technologies) as a potential disruptor and understand the implications, you need to figure out how to evolve your organization to make the most of the opportunity. Simply recognizing disruption isn’t enough.
Take today’s struggling brick-and-mortar retail business. Online shopping isn’t new. Amazon isn’t a plucky startup. Both have been changing how we buy stuff for years. And yet many who still own and operate physical stores—perhaps most prominently, Sears—are now on the brink of bankruptcy.
There’s hope though. Netflix began as a DVD delivery service in the 90s, but quickly realized its core business didn’t have staying power. It would have been laughable to stream movies when Netflix was founded. Still, computers and bandwidth were advancing fast. In 2007, the company added streaming to its subscription. Even then it wasn’t a totally compelling product.
But Netflix clearly saw a streaming future would likely end their DVD business.
In recent years, faster connection speeds, a growing content library, and the company’s entrance into original programming have given Netflix streaming the upper hand over DVDs. Since 2011, DVD subscriptions have steadily declined. Yet the company itself is doing fine. Why? It anticipated the shift to streaming and acted on it.
Never Stop Looking for the Next Big Thing
Technology is and will increasingly be a driver of disruption, destabilizing entrenched businesses and entire industries while also creating new markets and value not yet imagined.
When faced with the rapidly accelerating pace of change, many companies still default to old models and established practices. Leading like a technologist requires vigilant understanding of potential sources of disruption—what might make your company’s offering obsolete? The answers may not always be perfectly clear. What’s most important is relentlessly seeking them.
Stock Media provided by MJTierney / Pond5 Continue reading

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#430550 This Week’s Awesome Stories From ...

DRONES
MIT Is Building Autonomous Drones That Can Both Drive and FlyApril Glaser | Recode“The drones, which were built at MIT’s Computer Science and Artificial Intelligence Laboratory, also include route-planning software that can help calculate when the flying robot switches from air to ground in order to optimize its battery life.”
SPACE
SpaceX Is Making Commercial Space Launches Look Like Child’s PlayJamie Condliffe | MIT Technology Review“Late Friday, SpaceX launched a satellite into orbit from Florida using one of its refurbished Falcon 9 rockets. Then on Sunday, for good measure, it lofted 10 smaller satellites using a new version of the same rocket, which it launched from California. The feat is a sign that the private space company seems more likely than ever to turn its vision of competitively priced, rapid-turnaround rocket launches into reality.”
CYBERSECURITY
A New Ransomware Attack Is Infecting Airlines, Banks, and Utilities Across EuropeRussell Brandom | The Verge“The origins of the attack are still unclear, but the involvement of Ukraine’s electric utilities is likely to cast suspicion on Russia. Ukraine’s power grid was hit by a persistent and sophisticated attack in December 2015, which many attributed to Russia. The attack ultimately left 230,000 residents without power for as long as six hours.”
SILICON VALLEY NEWS
Mark Zuckerberg’s Probably Nonexistent 2020 Presidential Campaign, ExplainedTimothy B. Lee | VOX“After all, the kind of outreach Zuckerberg would do in a presidential campaign isn’t that different from the kind of outreach he’d do if he were simply trying to understand Facebook users better and build public goodwill for his massive social media site.”
AUTONOMOUS CARS
Riding in a Robocar That Sees Around CornersPhilip E. Ross | IEEE Spectrum“It takes 20 to 30 minutes to fit a car with the necessary hardware: a GPS sensor and a wireless transceiver. Here in the MCity compound, at least, the GPS system uses a repeater to enhance its accuracy down to centimeter level—good enough to locate a car precisely and to allow other cars to figure out its trajectory and measure its speed.”
Image Credit: SpaceX / Flickr Continue reading

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#426831 Industrial robot runtime programming

Article provided by: www.robotct.ru
In this article, runtime programming is understood as the process of creating an executable program for a robot controller (hereinafter referred to as “robot”) on an external controller. In this case the robot performs the program iteratively, by sending the minimum executable command or batch of commands to it. In other words, in runtime programming, the executable program is sent to the robot in portions, thus the robot does not have, store, or know the entire executable program beforehand. Such an approach allows creating an abstract parameterized executable program, which is generated by the external device “on the fly”, i.e., during runtime.
Under the cut, there is the description and a real example of how runtime programming works.
Typically, a program for a robot is a sequence of positions of the robot manipulator. Each of these positions is characterized by the TCP (Tool Center Point) position, the point of the tip of the tool mounted on the manipulator (by default, TCP is in the center of robot’s flange, see the picture below, but its position may be adjusted, and it is often that TCP with the tip of the tool mounted on the manipulator of the robot). Therefore, when programming, TCP position in space is often specified, and the robot determines the positions of manipulator’s joints itself. Further in this article, we will use the term “TCP position”, or, in other words, the point that the robot shall arrive to.

The program for the robot may also contain control logic (branching, loops), simple mathematical operations, and commands for controlling peripheral devices – analog and digital inputs/outputs. In the proposed approach to runtime programming, a standard PC is used as an external controller, which can use powerful software that ensures the necessary level of abstraction (OOP and other paradigms), and tools that ensure speed and ease of developing complex logic (high-level programming languages). The robot itself has only to deal with the logic that is critical to response rate, for execution of which the reliability of an industrial controller is required, for example, prompt and adequate response to an emergency situation. The control of the peripherals connected to the robot is simply “proxied” by the robot on the PC, allowing the PC to activate or deactivate corresponding signals on the robot; it is something similar to controlling “legs” of Arduino.

As it has been noted earlier, runtime programming enables sending the program to the robot in portions. Usually, a set of states of output signals and several points, or even only a single point is sent. Thus, the trajectory of the TCP movement performed by the robot may be built dynamically, and some of its parts may belong both to different technological processes, and even to different robots (connected to the same external controller), where a group of robots works.
For example, the robot has moved to one of the working areas, performed the required operations, then – to the next one, then to yet another one, and then back to the first one, etc. In different working areas, the robot performs operations required for different technological processes, where programs are executed in parallel threads on the external controller, which allocates the robot to different processes that do not require constant presence of the robot. This mechanism is similar to the way an OS allocates processor time (execution resource) to various threads, and at the same time, different executors are not linked to threads throughout the whole period of program execution.
A little more theory, and we will proceed to practice.
Description of the existing methods of programming industrial robots.
Without regard to the approach of runtime programming introduced in this article, two ways of programming industrial robots are usually identified. Offline and online programming.
The process of online programming occurs with direct interaction of the programmer and the robot at the location of usage. Using a remote control, or by physical movement, the tool (TCP) mounted on the flange of the robot is moved to the desired point.
The advantage of this method of programming is the ease of approach to robot programming. One does not have to know anything about programming; it is enough to state the sequence of robot positions.
An important disadvantage of this approach is the significantly increased time consumption, when the program is increased at least to several dozen (not to mention thousands) points, or when it (the program) is subsequently modified. In addition, during such learning, the robot cannot be used for work.
The process of offline programming, as the name implies, occurs away from the robot and its controller. The executable program is developed in any programming environment on a PC, after which it is entirely loaded into the robot. However, programming tools for such development are not included into the basic delivery set of the robot, and are additional options to be purchased separately, and expensive on the whole.
The advantage of offline programming is that the robot may be used in production and may work, while the program is being developed. The robot is only needed to debug ready programs. There is no need to go to the automation object and program the robot in person.
A great disadvantage of the existing offline programming environments is their high cost. Besides, it is impossible to dynamically distribute the executable program to different robots.
As an example, let us consider creating a robot program in runtime mode, which enables the process of writing an ad with a marker.

Result:

ATTENTION! The video is not an advertisement, the vacancy is closed. The article was written after the video had become obsolete, to show the proposed approach to programming.

The written text:
HELLO, PEOPLE! WE NEED A DEVELOPER TO CREATE A WEB INTERFACE OF OUR KNOWLEDGE SYSTEM.
THIS WAY WE WILL BE ABLE TO GET KNOWLEDGE FROM YOU HUMANOIDS.
AND, FINALLY, WE’LL BE ABLE TO CONQUER AND IMPROVE THIS WORLD

READ MORE: HTTP://ROBOTCT.COM/HI
SINCERELY YOURS, SKYNET =^-^=
To make the robot write this text, it was necessary to send over 1,700 points to the robot.
As an example, the spoiler contained a screenshot of the program drawing a square from the robot’s remote control. It only has 5 points (lines 4-8); each point is in fact a complete expression, and takes one line. The manipulator traverses each of the four points, and returns to the starting point upon completion.
The screenshot of the remote control with the executable program:

If the program is written this way, it would take at least 1,700 lines of code, a line per point. What if you have to change the text, or the height of the characters, or the distance between them? Edit all the 1,700 point lines? This contradicts the spirit of automation!
So, let’s proceed to the solution…
We have a FANUC LR Mate 200iD robot with an R-30i B series cabinet controller. The robot has a preconfigured TCP at the marker end, and the coordinate system of the desktop, so we can send the coordinates directly, without worrying about transforming the coordinates from the coordinate system of the table into the coordinate system of the robot.
To implement the program of sending the coordinates to the robot, which will calculate the absolute values of each point, we will use the RCML programming language that supports this robot and, which is important, which is free for anyone to use.
Let’s describe each letter with dots, but in the relative coordinates inside the frame, in which the letter will be inscribed, rather than in the real space coordinates. Each letter will be drawn by a separate function receiving the sequence number of the character in the line, line number and the size of the letter as input parameters, and sending a set of points to the robot with calculated absolute coordinates for each point.
To write a text, we will have to call a series of functions that would draw the letters in the sequence in which they (letters) are present in the text. RCML has a meager set of tools for working with strings, so we will write an external Python script which will generate a program in RCML – essentially, generate only the sequence of function calls that corresponds to the sequence of letters.
The whole code is available in repository: rct_paint_words
Let us consider the output file in more detail, execution starts from function main():

Spoiler: “Let us consider the code for drawing a letter, for example, letter A:”
function robot_fanuc::draw_A(x_cell,y_cell){
// Setting the marker to the point, the coordinates of the point are 5% along X and 95% along Y within the letter frame
robot->setPoint(x_cell, y_cell, 5, 95);
// Drawing a line
robot->movePoint(x_cell, y_cell, 50, 5);
// Drawing the second line
robot->movePoint(x_cell, y_cell, 95, 95);
// We get the “roof” /

// Moving the marker lifted from the table to draw the cross line
robot->setPoint(x_cell, y_cell, 35, 50);
// Drawing the cross-line
robot->movePoint(x_cell, y_cell, 65, 50);
// Lifting the marker from the table to move to the next letter
robot->marker_up();
}
End of spoiler

Spoiler: “The functions of moving the marker to the point, with or without lifting, are also very simple:”
// Moving the lifted marker to the point, or setting the point to start drawing
function robot_fanuc::setPoint(x_cell, y_cell, x_percent, y_precent){
// Calculating the absolute coordinates
x = calculate_absolute_coords_x(x_cell, x_percent); y = calculate_absolute_coords_y(y_cell, y_precent);

robot->marker_up(); // Lifting the marker from the table
robot->marker_move(x,y); // Moving
robot->marker_down(); // Lowering the marker to the table

// Moving the marker to the point without lifting, or actually drawing
function robot_fanuc::movePoint(x_cell, y_cell, x_percent, y_precent){ x = calculate_absolute_coords_x(x_cell, x_percent); y = calculate_absolute_coords_y(y_cell, y_precent);
// Here everything is clear robot->marker_move(x,y);
}
End of spoiler

Spoiler: Functions marker_up, marker_down, marker_move contain only the code of sending the changed part of the TCP point coordinates (Z or XY) to the robot.
function robot_fanuc::marker_up(){
robot->set_real_di(“z”, SAFE_Z);
er = robot->sendMoveSignal();
if (er != 0){
system.echo(“error marker upn”);
throw er;
}
}

function robot_fanuc::marker_down(){
robot->set_real_di(“z”, START_Z);
er = robot->sendMoveSignal();
if (er != 0){
system.echo(“error marker downn”);
throw er;
}
}

function robot_fanuc::marker_move(x,y){
robot->set_real_di(“x”, x);
robot->set_real_di(“y”, y);
er = robot->sendMoveSignal();
if (er != 0){
system.echo(“error marker moven”);
throw er;
}
}
End of spoiler

All configuration constants, including size of letters, their number in the line, etc., were put to a separate file.
Spoiler: “Configuration file”
define CHAR_HEIGHT_MM 50 // Character height in mm
define CHAR_WIDTH_PERCENT 60 // Character width in percentage of height

define SAFE_Z -20 // Safe position of the tip of the marker along the z-axis
define START_Z 0 // Working position of the tip of the marker along the z-axis

// Working area border
define BORDER_Y 120
define BORDER_X 75

// ON/OFF signals
define ON 1
define OFF 0

// Pauses between sending certain signals, milliseconds
define _SIGNAL_PAUSE_MILLISEC 50
define _OFF_PAUSE_MILLISEC 200

// Euler angles of the initial marker position
define START_W -179.707 // Roll
define START_P -2.500 // Pitch
define START_R 103.269 // Yaw

// Euler angles of marker turn
define SECOND_W -179.704
define SECOND_P -2.514
define SECOND_R -14.699

define CHAR_OFFSET_MM 4 // Spacing between letters

define UFRAME 4 // Table number
define UTOOL 2 // Tool number
define PAYLOAD 4 // Load number
define SPEED 100 // Speed
define CNT 0 // Movement smoothness parameter
define ROTATE_SPEED // Speed in turn

define HOME_PNS 4 // The number of the PNS program for home position return
End of spoiler

In total, we’ve got about 300 lines of high level code that took not more than 1 hour to develop and write.
If the problem had been solved in the “straightforward” manner by online programming with the use of points, it would have taken more than 9 hours (approximately 20-25 seconds per point, given the fact that there are over 1,700 points). In this case, the developer’s sufferings are unimaginable :), especially when he would have found out that he had forgotten about the indents between the frames that the letters were inscribed in, or the height of the letters was wrong, and the text did not fit in.
Conclusion:
The use of runtime programming is one of the ways to create executable software. The advantages of this approach include the following:
The possibility of writing and debugging programs without the need to stop the robot, thus minimizing the downtime for changeover.
A parameterized executable program that’s easy to edit.
Dynamic activation and deactivation robots in the active technological task, and cooperation of robots from various manufacturers.
Thus, with the use of runtime programming, an executable command may be described in a way to make its execution available for any robot within the working group, or may be written for a particular robot, that will be the only one to execute it.
However, this approach has one significant limitation – incorrect understanding of the displacement smoothing instruction (CNT) by the robot, or ignoring it, since when only the current point is sent, the robot knows nothing about the next one, and cannot calculate the smoothed trajectory for bypassing the current point with smoothing.
Spoiler: “What is trajectory smoothing?”
When moving the robot’s tool, two parameters may be adjusted:
Travel speed
Level of smoothing
Travel speed sets the speed of the tool travel in mm/sec.
Level of smoothing (CNT) allows passing a group of points along the trajectory with the least distance between the extreme points of the group.

End of spoiler

The danger of using this instruction in the runtime mode is that the robot reports its arrival to the smoothed target point, although in reality the robot is still moving towards it. The robot does it to request the next point, and to calculate smoothing. Evidently, it is impossible to know exactly in what position the robot is when passing such a point, besides, tool activation at the manipulator may be required at a certain point. The robot will send a signal about reaching the point, but it is not actually so. In this case, the tool will be enabled before it is needed. At the best case, the robot will simply ignore the CNT instruction (depending on the model).
This may be fixed by sending 2 or more points at a time, where the CNT point is not the last one; however, this increases program complexity and the burden on the programmer.
Article provided by: robotct.ru
Photo Credits: Robotct.ru

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