Tag Archives: car

#432165 Silicon Valley Is Winning the Race to ...

Henry Ford didn’t invent the motor car. The late 1800s saw a flurry of innovation by hundreds of companies battling to deliver on the promise of fast, efficient and reasonably-priced mechanical transportation. Ford later came to dominate the industry thanks to the development of the moving assembly line.

Today, the sector is poised for another breakthrough with the advent of cars that drive themselves. But unlike the original wave of automobile innovation, the race for supremacy in autonomous vehicles is concentrated among a few corporate giants. So who is set to dominate this time?

I’ve analyzed six companies we think are leading the race to build the first truly driverless car. Three of these—General Motors, Ford, and Volkswagen—come from the existing car industry and need to integrate self-driving technology into their existing fleet of mass-produced vehicles. The other three—Tesla, Uber, and Waymo (owned by the same company as Google)—are newcomers from the digital technology world of Silicon Valley and have to build a mass manufacturing capability.

While it’s impossible to know all the developments at any given time, we have tracked investments, strategic partnerships, and official press releases to learn more about what’s happening behind the scenes. The car industry typically rates self-driving technology on a scale from Level 0 (no automation) to Level 5 (full automation). We’ve assessed where each company is now and estimated how far they are from reaching the top level. Here’s how we think each player is performing.

Volkswagen
Volkswagen has invested in taxi-hailing app Gett and partnered with chip-maker Nvidia to develop an artificial intelligence co-pilot for its cars. In 2018, the VW Group is set to release the Audi A8, the first production vehicle that reaches Level 3 on the scale, “conditional driving automation.” This means the car’s computer will handle all driving functions, but a human has to be ready to take over if necessary.

Ford
Ford already sells cars with a Level 2 autopilot, “partial driving automation.” This means one or more aspects of driving are controlled by a computer based on information about the environment, for example combined cruise control and lane centering. Alongside other investments, the company has put $1 billion into Argo AI, an artificial intelligence company for self-driving vehicles. Following a trial to test pizza delivery using autonomous vehicles, Ford is now testing Level 4 cars on public roads. These feature “high automation,” where the car can drive entirely on its own but not in certain conditions such as when the road surface is poor or the weather is bad.

General Motors
GM also sells vehicles with Level 2 automation but, after buying Silicon Valley startup Cruise Automation in 2016, now plans to launch the first mass-production-ready Level 5 autonomy vehicle that drives completely on its own by 2019. The Cruise AV will have no steering wheel or pedals to allow a human to take over and be part of a large fleet of driverless taxis the company plans to operate in big cities. But crucially the company hasn’t yet secured permission to test the car on public roads.

Waymo (Google)

Waymo Level 5 testing. Image Credit: Waymo

Founded as a special project in 2009, Waymo separated from Google (though they’re both owned by the same parent firm, Alphabet) in 2016. Though it has never made, sold, or operated a car on a commercial basis, Waymo has created test vehicles that have clocked more than 4 million miles without human drivers as of November 2017. Waymo tested its Level 5 car, “Firefly,” between 2015 and 2017 but then decided to focus on hardware that could be installed in other manufacturers’ vehicles, starting with the Chrysler Pacifica.

Uber
The taxi-hailing app maker Uber has been testing autonomous cars on the streets of Pittsburgh since 2016, always with an employee behind the wheel ready to take over in case of a malfunction. After buying the self-driving truck company Otto in 2016 for a reported $680 million, Uber is now expanding its AI capabilities and plans to test NVIDIA’s latest chips in Otto’s vehicles. It has also partnered with Volvo to create a self-driving fleet of cars and with Toyota to co-create a ride-sharing autonomous vehicle.

Tesla
The first major car manufacturer to come from Silicon Valley, Tesla was also the first to introduce Level 2 autopilot back in 2015. The following year, it announced that all new Teslas would have the hardware for full autonomy, meaning once the software is finished it can be deployed on existing cars with an instant upgrade. Some experts have challenged this approach, arguing that the company has merely added surround cameras to its production cars that aren’t as capable as the laser-based sensing systems that most other carmakers are using.

But the company has collected data from hundreds of thousands of cars, driving millions of miles across all terrains. So, we shouldn’t dismiss the firm’s founder, Elon Musk, when he claims a Level 4 Tesla will drive from LA to New York without any human interference within the first half of 2018.

Winners

Who’s leading the race? Image Credit: IMD

At the moment, the disruptors like Tesla, Waymo, and Uber seem to have the upper hand. While the traditional automakers are focusing on bringing Level 3 and 4 partial automation to market, the new companies are leapfrogging them by moving more directly towards Level 5 full automation. Waymo may have the least experience of dealing with consumers in this sector, but it has already clocked up a huge amount of time testing some of the most advanced technology on public roads.

The incumbent carmakers are also focused on the difficult process of integrating new technology and business models into their existing manufacturing operations by buying up small companies. The challengers, on the other hand, are easily partnering with other big players including manufacturers to get the scale and expertise they need more quickly.

Tesla is building its own manufacturing capability but also collecting vast amounts of critical data that will enable it to more easily upgrade its cars when ready for full automation. In particular, Waymo’s experience, technology capability, and ability to secure solid partnerships puts it at the head of the pack.

This article was originally published on The Conversation. Read the original article.

Image Credit: Waymo Continue reading

Posted in Human Robots

#432031 Why the Rise of Self-Driving Vehicles ...

It’s been a long time coming. For years Waymo (formerly known as Google Chauffeur) has been diligently developing, driving, testing and refining its fleets of various models of self-driving cars. Now Waymo is going big. The company recently placed an order for several thousand new Chrysler Pacifica minivans and next year plans to launch driverless taxis in a number of US cities.

This deal raises one of the biggest unanswered questions about autonomous vehicles: if fleets of driverless taxis make it cheap and easy for regular people to get around, what’s going to happen to car ownership?

One popular line of thought goes as follows: as autonomous ride-hailing services become ubiquitous, people will no longer need to buy their own cars. This notion has a certain logical appeal. It makes sense to assume that as driverless taxis become widely available, most of us will eagerly sell the family car and use on-demand taxis to get to work, run errands, or pick up the kids. After all, vehicle ownership is pricey and most cars spend the vast majority of their lives parked.

Even experts believe commercial availability of autonomous vehicles will cause car sales to drop.

Market research firm KPMG estimates that by 2030, midsize car sales in the US will decline from today’s 5.4 million units sold each year to nearly half that number, a measly 2.1 million units. Another market research firm, ReThinkX, offers an even more pessimistic estimate (or optimistic, depending on your opinion of cars), predicting that autonomous vehicles will reduce consumer demand for new vehicles by a whopping 70 percent.

The reality is that the impending death of private vehicle sales is greatly exaggerated. Despite the fact that autonomous taxis will be a beneficial and widely-embraced form of urban transportation, we will witness the opposite. Most people will still prefer to own their own autonomous vehicle. In fact, the total number of units of autonomous vehicles sold each year is going to increase rather than decrease.

When people predict the demise of car ownership, they are overlooking the reality that the new autonomous automotive industry is not going to be just a re-hash of today’s car industry with driverless vehicles. Instead, the automotive industry of the future will be selling what could be considered an entirely new product: a wide variety of intelligent, self-guiding transportation robots. When cars become a widely used type of transportation robot, they will be cheap, ubiquitous, and versatile.

Several unique characteristics of autonomous vehicles will ensure that people will continue to buy their own cars.

1. Cost: Thanks to simpler electric engines and lighter auto bodies, autonomous vehicles will be cheaper to buy and maintain than today’s human-driven vehicles. Some estimates bring the price to $10K per vehicle, a stark contrast with today’s average of $30K per vehicle.

2. Personal belongings: Consumers will be able to do much more in their driverless vehicles, including work, play, and rest. This means they will want to keep more personal items in their cars.

3. Frequent upgrades: The average (human-driven) car today is owned for 10 years. As driverless cars become software-driven devices, their price/performance ratio will track to Moore’s law. Their rapid improvement will increase the appeal and frequency of new vehicle purchases.

4. Instant accessibility: In a dense urban setting, a driverless taxi is able to show up within minutes of being summoned. But not so in rural areas, where people live miles apart. For many, delay and “loss of control” over their own mobility will increase the appeal of owning their own vehicle.

5. Diversity of form and function: Autonomous vehicles will be available in a wide variety of sizes and shapes. Consumers will drive demand for custom-made, purpose-built autonomous vehicles whose form is adapted for a particular function.

Let’s explore each of these characteristics in more detail.

Autonomous vehicles will cost less for several reasons. For one, they will be powered by electric engines, which are cheaper to construct and maintain than gasoline-powered engines. Removing human drivers will also save consumers money. Autonomous vehicles will be much less likely to have accidents, hence they can be built out of lightweight, lower-cost materials and will be cheaper to insure. With the human interface no longer needed, autonomous vehicles won’t be burdened by the manufacturing costs of a complex dashboard, steering wheel, and foot pedals.

While hop-on, hop-off autonomous taxi-based mobility services may be ideal for some of the urban population, several sizeable customer segments will still want to own their own cars.

These include people who live in sparsely-populated rural areas who can’t afford to wait extended periods of time for a taxi to appear. Families with children will prefer to own their own driverless cars to house their childrens’ car seats and favorite toys and sippy cups. Another loyal car-buying segment will be die-hard gadget-hounds who will eagerly buy a sexy upgraded model every year or so, unable to resist the siren song of AI that is three times as safe, or a ride that is twice as smooth.

Finally, consider the allure of robotic diversity.

Commuters will invest in a home office on wheels, a sleek, traveling workspace resembling the first-class suite on an airplane. On the high end of the market, city-dwellers and country-dwellers alike will special-order custom-made autonomous vehicles whose shape and on-board gadgetry is adapted for a particular function or hobby. Privately-owned small businesses will buy their own autonomous delivery robot that could range in size from a knee-high, last-mile delivery pod, to a giant, long-haul shipping device.

As autonomous vehicles near commercial viability, Waymo’s procurement deal with Fiat Chrysler is just the beginning.

The exact value of this future automotive industry has yet to be defined, but research from Intel’s internal autonomous vehicle division estimates this new so-called “passenger economy” could be worth nearly $7 trillion a year. To position themselves to capture a chunk of this potential revenue, companies whose businesses used to lie in previously disparate fields such as robotics, software, ships, and entertainment (to name but a few) have begun to form a bewildering web of what they hope will be symbiotic partnerships. Car hailing and chip companies are collaborating with car rental companies, who in turn are befriending giant software firms, who are launching joint projects with all sizes of hardware companies, and so on.

Last year, car companies sold an estimated 80 million new cars worldwide. Over the course of nearly a century, car companies and their partners, global chains of suppliers and service providers, have become masters at mass-producing and maintaining sturdy and cost-effective human-driven vehicles. As autonomous vehicle technology becomes ready for mainstream use, traditional automotive companies are being forced to grapple with the painful realization that they must compete in a new playing field.

The challenge for traditional car-makers won’t be that people no longer want to own cars. Instead, the challenge will be learning to compete in a new and larger transportation industry where consumers will choose their product according to the appeal of its customized body and the quality of its intelligent software.

Melba Kurman and Hod Lipson are the authors of Driverless: Intelligent Cars and the Road Ahead and Fabricated: the New World of 3D Printing.

Image Credit: hfzimages / Shutterstock.com

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Posted in Human Robots

#432021 Unleashing Some of the Most Ambitious ...

At Singularity University, we are unleashing a generation of women who are smashing through barriers and starting some of the most ambitious technology companies on the planet.

Singularity University was founded in 2008 to empower leaders to use exponential technologies to solve our world’s biggest challenges. Our flagship program, the Global Solutions Program, has historically brought 80 entrepreneurs from around the world to Silicon Valley for 10 weeks to learn about exponential technologies and create moonshot startups that improve the lives of a billion people within a decade.

After nearly 10 years of running this program, we can say that about 70 percent of our successful startups have been founded or co-founded by female entrepreneurs (see below for inspiring examples of their work). This is in sharp contrast to the typical 10–20 percent of venture-backed tech companies that have a female founder, as reported by TechCrunch.

How are we so dramatically changing the game? While 100 percent of the credit goes to these courageous women, as both an alumna of the Global Solutions Program and our current vice chair of Global Grand Challenges, I want to share my reflections on what has worked.

At the most basic level, it is essential to deeply believe in the inherent worth, intellectual genius, and profound entrepreneurial caliber of women. While this may seem obvious, this is not the way our world currently thinks—we live in a world that sees women’s ideas, contributions, work, and existence as inherently less valuable than men’s.

For example, a 2017 Harvard Business Review article noted that even when women engage in the same behaviors and work as men, their work is considered less valuable simply because a woman did the job. An additional 2017 Harvard Business Review article showed that venture capitalists are significantly less likely to invest in female entrepreneurs and are more likely to ask men questions about the potential success of their companies while grilling women about the potential downfalls of their companies.

This doubt and lack of recognition of the genius and caliber of women is also why women are still paid less than men for completing identical work. Further, it’s why women’s work often gets buried in “number two” support roles of men in leadership roles and why women are expected to take on second shifts at home managing tedious household chores in addition to their careers. I would also argue these views as well as the rampant sexual harassment, assault, and violence against women that exists today stems from stubborn, historical, patriarchal views of women as living for the benefit of men, rather than for their own sovereignty and inherent value.

As with any other business, Singularity University has not been immune to these biases but is resolutely focused on helping women achieve intellectual genius and global entrepreneurial caliber by harnessing powerful exponential technologies.

We create an environment where women can physically and intellectually thrive free of harassment to reach their full potential, and we are building a broader ecosystem of alumni and partners around the world who not only support our female entrepreneurs throughout their entrepreneurial journeys, but who are also sparking and leading systemic change in their own countries and communities.

Respecting the Intellectual Genius and Entrepreneurial Caliber of Women
The entrepreneurial legends of our time—Steve Jobs, Elon Musk, Mark Zuckerberg, Bill Gates, Jeff Bezos, Larry Page, Sergey Brin—are men who have all built their empires using exponential technologies. Exponential technologies helped these men succeed faster and with greater impact due to Moore’s Law and the Law of Accelerating Returns which states that any digital technology (such as computing, software, artificial intelligence, robotics, quantum computing, biotechnology, nanotechnology, etc.) will become more sophisticated while dramatically falling in price, enabling rapid scaling.

Knowing this, an entrepreneur can plot her way to an ambitious global solution over time, releasing new applications just as the technology and market are ready. Furthermore, these rapidly advancing technologies often converge to create new tools and opportunities for innovators to come up with novel solutions to challenges that were previously impossible to solve in the past.

For various reasons, women have not pursued exponential technologies as aggressively as men (or were prevented or discouraged from doing so).

While more women are founding firms at a higher rate than ever in wealthy countries like the United States, the majority are small businesses in linear industries that have been around for hundreds of years, such as social assistance, health, education, administrative, or consulting services. In lower-income countries, international aid agencies and nonprofits often encourage women to pursue careers in traditional handicrafts, micro-enterprise, and micro-finance. While these jobs have historically helped women escape poverty and gain financial independence, they have done little to help women realize the enormous power, influence, wealth, and ability to transform the world for the better that comes from building companies, nonprofits, and solutions grounded in exponential technologies.

We need women to be working with exponential technologies today in order to be powerful leaders in the future.

Participants who enroll in our Global Solutions Program spend the first few weeks of the program learning about exponential technologies from the world’s experts and the final weeks launching new companies or nonprofits in their area of interest. We require that women (as well as men) utilize exponential technologies as a condition of the program.

In this sense, at Singularity University women start their endeavors with all of us believing and behaving in a way that assumes they can achieve global impact at the level of our world’s most legendary entrepreneurs.

Creating an Environment Where Woman Can Thrive
While challenging women to embrace exponential technologies is essential, it is also important to create an environment where women can thrive. In particular, this means ensuring women feel at home on our campus by ensuring gender diversity, aggressively addressing sexual harassment, and flipping the traditional culture from one that penalizes women, to one that values and supports them.

While women were initially only a small minority of our Global Solutions Program, in 2014, we achieved around 50% female attendance—a statistic that has since held over the years.

This is not due to a quota—every year we turn away extremely qualified women from our program (and are working on reformulating the program to allow more people to participate in the future.) While part of our recruiting success is due to the efforts of our marketing team, we also benefited from the efforts of some of our early female founders, staff, faculty, and alumnae including Susan Fonseca, Emeline Paat-Dahlstrom, Kathryn Myronuk, Lajuanda Asemota, Chiara Giovenzana, and Barbara Silva Tronseca.

As early champions of Singularity University these women not only launched diversity initiatives and personally reached out to women, but were crucial role models holding leadership roles in our community. In addition, Fonseca and Silva also both created multiple organizations and initiatives outside of (or in conjunction with) the university that produced additional pipelines of female candidates. In particular, Fonseca founded Women@TheFrontier as well as other organizations focusing on women, technology and innovation, and Silva founded BestInnovation (a woman’s accelerator in Latin America), as well as led Singularity University’s Chilean Chapter and founded the first SingularityU Summit in Latin America.

These women’s efforts in globally scaling Singularity University have been critical in ensuring woman around the world now see Singularity University as a place where they can lead and shape the future.

Also, thanks to Google (Alphabet) and many of our alumni and partners, we were able to provide full scholarships to any woman (or man) to attend our program regardless of their economic status. Google committed significant funding for full scholarships while our partners around the world also hosted numerous Global Impact Competitions, where entrepreneurs pitched their solutions to their local communities with the winners earning a full scholarship funded by our partners to attend the Global Solution Program as their prize.

Google and our partners’ support helped individuals attend our program and created a wider buzz around exponential technology and social change around the world in local communities. It led to the founding of 110 SU chapters in 55 countries.

Another vital aspect of our work in supporting women has been trying to create a harassment-free environment. Throughout the Silicon Valley, more than 60% of women convey that while they are trying to build their companies or get their work done, they are also dealing with physical and sexual harassment while being demeaned and excluded in other ways in the workplace. We have taken actions to educate and train our staff on how to deal with situations should they occur. All staff receives training on harassment when they join Singularity University, and all Global Solutions Program participants attend mandatory trainings on sexual harassment when they first arrive on campus. We also have male and female wellness counselors available that can offer support to both individuals and teams of entrepreneurs throughout the entire program.

While at a minimum our campus must be physically safe for women, we also strive to create a culture that values women and supports them in the additional challenges and expectations they face. For example, one of our 2016 female participants, Van Duesterberg, was pregnant during the program and said that instead of having people doubt her commitment to her startup or make her prove she could handle having a child and running a start-up at the same time, people went out of their way to help her.

“I was the epitome of a person not supposed to be doing a startup,” she said. “I was pregnant and would need to take care of my child. But Singularity University was supportive and encouraging. They made me feel super-included and that it was possible to do both. I continue to come back to campus even though the program is over because the network welcomes me and supports me rather than shuts me out because of my physical limitations. Rather than making me feel I had to prove myself, everyone just understood me and supported me, whether it was bringing me healthy food or recommending funders.”

Another strength that we have in supporting women is that after the Global Solutions Program, entrepreneurs have access to a much larger ecosystem.

Many entrepreneurs partake in SU Ventures, which can provide further support to startups as they develop, and we now have a larger community of over 200,000 people in almost every country. These members have often attended other Singularity University programs, events and are committed to our vision of the future. These women and men consist of business executives, Fortune 500 companies, investors, nonprofit and government leaders, technologists, members of the media, and other movers and shakers in the world. They have made introductions for our founders, collaborated with them on business ventures, invested in them and showcased their work at high profile events around the world.

Building for the Future
While our Global Solutions Program is making great strides in supporting female entrepreneurs, there is always more work to do. We are now focused on achieving the same degree of female participation across all of our programs and actively working to recruit and feature more female faculty and speakers on stage. As our community grows and scales around the world, we are also intent at how to best uphold our values and policies around sexual harassment across diverse locations and cultures. And like all businesses everywhere, we are focused on recruiting more women to serve at senior leadership levels within SU. As we make our way forward, we hope that you will join us in boldly leading this change and recognizing the genius and power of female entrepreneurs.

Meet Some of Our Female Moonshots
While we have many remarkable female entrepreneurs in the Singularity University community, the list below features a few of the women who have founded or co-founded companies at the Global Solutions Program that have launched new industries and are on their way to changing the way our world works for millions if not billions of people.

Jessica Scorpio co-founded Getaround in 2009. Getaround was one of the first car-sharing service platforms allowing anyone to rent out their car using a smartphone app. GetAround was a revolutionary idea in 2009, not only because smartphones and apps were still in their infancy, but because it was unthinkable that a technology startup could disrupt the major entrenched car, transport, and logistics companies. Scorpio’s early insights and pioneering entrepreneurial work brought to life new ways that humans relate to car sharing and the future self-driving car industry. Scorpio and Getaround have won numerous awards, and Getaround now serves over 200,000 members.

Paola Santana co-founded Matternet in 2011, which pioneered the commercial drone transport industry. In 2011, only military, hobbyists or the film industry used drones. Matternet demonstrated that drones could be used for commercial transport in short point-to-point deliveries for high-value goods laying the groundwork for drone transport around the world as well as some of the early thinking behind the future flying car industry. Santana was also instrumental in shaping regulations for the use of commercial drones around the world, making the industry possible.

Sara Naseri co-founded Qurasense in 2014, a life sciences start-up that analyzes women’s health through menstrual blood allowing women to track their health every month. Naseri is shifting our understanding of women’s menstrual blood as a waste product and something “not to be talked about,” to a rich, non-invasive, abundant source of information about women’s health.

Abi Ramanan co-founded ImpactVision in 2015, a software company that rapidly analyzes the quality and characteristics of food through hyperspectral images. Her long-term vision is to digitize food supply chains to reduce waste and fraud, given that one-third of all food is currently wasted before it reaches our plates. Ramanan is also helping the world understand that hyperspectral technology can be used in many industries to help us “see the unseen” and augment our ability to sense and understand what is happening around us in a much more sophisticated way.

Anita Schjøll Brede and Maria Ritola co-founded Iris AI in 2015, an artificial intelligence company that is building an AI research assistant that drastically improves the efficiency of R&D research and breaks down silos between different industries. Their long-term vision is for Iris AI to become smart enough that she will become a scientist herself. Fast Company named Iris AI one of the 10 most innovative artificial intelligence companies for 2017.

Hla Hla Win co-founded 360ed in 2016, a startup that conducts teacher training and student education through virtual reality and augmented reality in Myanmar. They have already connected teachers from 128 private schools in Myanmar with schools teaching 21st-century skills in Silicon Valley and around the world. Their moonshot is to build a platform where any teacher in the world can share best practices in teachers’ training. As they succeed, millions of children in some of the poorest parts of the world will have access to a 21st-century education.

Min FitzGerald and Van Duesterberg cofounded Nutrigene in 2017, a startup that ships freshly formulated, tailor-made supplement elixirs directly to consumers. Their long-term vision is to help people optimize their health using actionable data insights, so people can take a guided, tailored approaching to thriving into longevity.

Anna Skaya co-founded Basepaws in 2016, which created the first genetic test for cats and is building a community of citizen scientist pet owners. They are creating personalized pet products such as supplements, therapeutics, treats, and toys while also developing a database of genetic data for future research that will help both humans and pets over the long term.

Olivia Ramos co-founded Deep Blocks in 2016, a startup using artificial intelligence to integrate and streamline the processes of architecture, pre-construction, and real estate. As digital technologies, artificial intelligence, and robotics advance, it no longer makes sense for these industries to exist separately. Ramos recognized the tremendous value and efficiency that it is now possible to unlock with exponential technologies and creating an integrated industry in the future.

Please also visit our website to learn more about other female entrepreneurs, staff and faculty who are pioneering the future through exponential technologies. Continue reading

Posted in Human Robots

#431987 OptoForce Industrial Robot Sensors

OptoForce Sensors Providing Industrial Robots with

a “Sense of Touch” to Advance Manufacturing Automation

Global efforts to expand the capabilities of industrial robots are on the rise, as the demand from manufacturing companies to strengthen their operations and improve performance grows.

Hungary-based OptoForce, with a North American office in Charlotte, North Carolina, is one company that continues to support organizations with new robotic capabilities, as evidenced by its several new applications released in 2017.

The company, a leading robotics technology provider of multi-axis force and torque sensors, delivers 6 degrees of freedom force and torque measurement for industrial automation, and provides sensors for most of the currently-used industrial robots.

It recently developed and brought to market three new applications for KUKA industrial robots.

The new applications are hand guiding, presence detection, and center pointing and will be utilized by both end users and systems integrators. Each application is summarized below and what they provide for KUKA robots, along with video demonstrations to show how they operate.

Photo By: www.optoforce.com

Hand Guiding: With OptoForce’s Hand Guiding application, KUKA robots can easily and smoothly move in an assigned direction and selected route. This video shows specifically how to program the robot for hand guiding.

Presence Detection: This application allows KUKA robots to detect the presence of a specific object and to find the object even if it has moved. Visit here to learn more about presence detection.
Center Pointing: With this application, the OptoForce sensor helps the KUKA robot find the center point of an object by providing the robot with a sense of touch. This solution also works with glossy metal objects where a vision system would not be able to define its position. This video shows in detail how the center pointing application works.

The company’s CEO explained how these applications help KUKA robots and industrial automation.

Photo By: www.optoforce.com
“OptoForce’s new applications for KUKA robots pave the way for substantial improvements in industrial automation for both end users and systems integrators,” said Ákos Dömötör, CEO of OptoForce. “Our 6-axis force/torque sensors are combined with highly functional hardware and a comprehensive software package, which include the pre-programmed industrial applications. Essentially, we’re adding a ‘sense of touch’ to KUKA robot arms, enabling these robots to have abilities similar to a human hand, and opening up numerous new capabilities in industrial automation.”

Along with these new applications recently released for KUKA robots, OptoForce sensors are also being used by various companies on numerous industrial robots and manufacturing automation projects around the world. Examples of other uses include: path recording, polishing plastic and metal, box insertion, placing pins in holes, stacking/destacking, palletizing, and metal part sanding.

Specifically, some of the projects current underway by companies include: a plastic parting line removal; an obstacle detection for a major car manufacturing company; and a center point insertion application for a car part supplier, where the task of the robot is to insert a mirror, completely centered, onto a side mirror housing.

For more information, visit www.optoforce.com.

This post was provided by: OptoForce

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Posted in Human Robots

#431828 This Self-Driving AI Is Learning to ...

I don’t have to open the doors of AImotive’s white 2015 Prius to see that it’s not your average car. This particular Prius has been christened El Capitan, the name written below the rear doors, and two small cameras are mounted on top of the car. Bundles of wire snake out from them, as well as from the two additional cameras on the car’s hood and trunk.
Inside is where things really get interesting, though. The trunk holds a computer the size of a microwave, and a large monitor covers the passenger glove compartment and dashboard. The center console has three switches labeled “Allowed,” “Error,” and “Active.”
Budapest-based AImotive is working to provide scalable self-driving technology alongside big players like Waymo and Uber in the autonomous vehicle world. On a highway test ride with CEO Laszlo Kishonti near the company’s office in Mountain View, California, I got a glimpse of just how complex that world is.
Camera-Based Feedback System
AImotive’s approach to autonomous driving is a little different from that of some of the best-known systems. For starters, they’re using cameras, not lidar, as primary sensors. “The traffic system is visual and the cost of cameras is low,” Kishonti said. “A lidar can recognize when there are people near the car, but a camera can differentiate between, say, an elderly person and a child. Lidar’s resolution isn’t high enough to recognize the subtle differences of urban driving.”
Image Credit: AImotive
The company’s aiDrive software uses data from the camera sensors to feed information to its algorithms for hierarchical decision-making, grouped under four concurrent activities: recognition, location, motion, and control.
Kishonti pointed out that lidar has already gotten more cost-efficient, and will only continue to do so.
“Ten years ago, lidar was best because there wasn’t enough processing power to do all the calculations by AI. But the cost of running AI is decreasing,” he said. “In our approach, computer vision and AI processing are key, and for safety, we’ll have fallback sensors like radar or lidar.”
aiDrive currently runs on Nvidia chips, which Kishonti noted were originally designed for graphics, and are not terribly efficient given how power-hungry they are. “We’re planning to substitute lower-cost, lower-energy chips in the next six months,” he said.
Testing in Virtual Reality
Waymo recently announced its fleet has now driven four million miles autonomously. That’s a lot of miles, and hard to compete with. But AImotive isn’t trying to compete, at least not by logging more real-life test miles. Instead, the company is doing 90 percent of its testing in virtual reality. “This is what truly differentiates us from competitors,” Kishonti said.
He outlined the three main benefits of VR testing: it can simulate scenarios too dangerous for the real world (such as hitting something), too costly (not every company has Waymo’s funds to run hundreds of cars on real roads), or too time-consuming (like waiting for rain, snow, or other weather conditions to occur naturally and repeatedly).
“Real-world traffic testing is very skewed towards the boring miles,” he said. “What we want to do is test all the cases that are hard to solve.”
On a screen that looked not unlike multiple games of Mario Kart, he showed me the simulator. Cartoon cars cruised down winding streets, outfitted with all the real-world surroundings: people, trees, signs, other cars. As I watched, a furry kangaroo suddenly hopped across one screen. “Volvo had an issue in Australia,” Kishonti explained. “A kangaroo’s movement is different than other animals since it hops instead of running.” Talk about cases that are hard to solve.
AImotive is currently testing around 1,000 simulated scenarios every night, with a steadily-rising curve of successful tests. These scenarios are broken down into features, and the car’s behavior around those features fed into a neural network. As the algorithms learn more features, the level of complexity the vehicles can handle goes up.
On the Road
After Kishonti and his colleagues filled me in on the details of their product, it was time to test it out. A safety driver sat in the driver’s seat, a computer operator in the passenger seat, and Kishonti and I in back. The driver maintained full control of the car until we merged onto the highway. Then he flicked the “Allowed” switch, his copilot pressed the “Active” switch, and he took his hands off the wheel.
What happened next, you ask?
A few things. El Capitan was going exactly the speed limit—65 miles per hour—which meant all the other cars were passing us. When a car merged in front of us or cut us off, El Cap braked accordingly (if a little abruptly). The monitor displayed the feed from each of the car’s cameras, plus multiple data fields and a simulation where a blue line marked the center of the lane, measured by the cameras tracking the lane markings on either side.
I noticed El Cap wobbling out of our lane a bit, but it wasn’t until two things happened in a row that I felt a little nervous: first we went under a bridge, then a truck pulled up next to us, both bridge and truck casting a complete shadow over our car. At that point El Cap lost it, and we swerved haphazardly to the right, narrowly missing the truck’s rear wheels. The safety driver grabbed the steering wheel and took back control of the car.
What happened, Kishonti explained, was that the shadows made it hard for the car’s cameras to see the lane markings. This was a new scenario the algorithm hadn’t previously encountered. If we’d only gone under a bridge or only been next to the truck for a second, El Cap may not have had so much trouble, but the two events happening in a row really threw the car for a loop—almost literally.
“This is a new scenario we’ll add to our testing,” Kishonti said. He added that another way for the algorithm to handle this type of scenario, rather than basing its speed and positioning on the lane markings, is to mimic nearby cars. “The human eye would see that other cars are still moving at the same speed, even if it can’t see details of the road,” he said.
After another brief—and thankfully uneventful—hands-off cruise down the highway, the safety driver took over, exited the highway, and drove us back to the office.
Driving into the Future
I climbed out of the car feeling amazed not only that self-driving cars are possible, but that driving is possible at all. I squint when driving into a tunnel, swerve to avoid hitting a stray squirrel, and brake gradually at stop signs—all without consciously thinking to do so. On top of learning to steer, brake, and accelerate, self-driving software has to incorporate our brains’ and bodies’ unconscious (but crucial) reactions, like our pupils dilating to let in more light so we can see in a tunnel.
Despite all the progress of machine learning, artificial intelligence, and computing power, I have a wholly renewed appreciation for the thing that’s been in charge of driving up till now: the human brain.
Kishonti seemed to feel similarly. “I don’t think autonomous vehicles in the near future will be better than the best drivers,” he said. “But they’ll be better than the average driver. What we want to achieve is safe, good-quality driving for everyone, with scalability.”
AImotive is currently working with American tech firms and with car and truck manufacturers in Europe, China, and Japan.
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