Newsbyte: Total to deploy autonomous robot on North Sea platform

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total oil and gas to use autonomous robot in north sea

French oil giant Total has partnered with Austrian robotics company Taurob, and German university TU Darmstad, to develop an autonomous robot for deployment to an oil and gas platform in the North Sea.

Taurob and research partner TU Darmstadt won Total’s ARGOS Challenge, in which five teams from around the world competed to develop a robot for routine inspections and on-platform emergency operations.

The winning robot is expected to be deployed to Total’s gas plant on Shetland. It will then move on to operations on the firm’s Alwyn platform in the North Sea, some 440km north-east of Aberdeen.

The 90kg robot moves on two tracks and uses laser scanners to read instruments and valve positions. It can also measure air temperature and gas concentrations, detect abnormal noises, sense obstacles, and move with ease on slick, slippery staircases.

Read more: Shell joins digital twin initiative for offshore oil and gas assets

When working on oil and gas platforms, the priority for any machinery or operations is to avoid anything that can cause a fire.

“Our robot is also the first fully automated inspection robot in the world that can be used safely in a potentially explosive atmosphere,” says Dr. Lukas Silberbauer, who founded Taurob with partner Matthias Biegl in 2010. The robot is fully ATEX certified to ensure it doesn’t trigger an explosion while operating near explosive gases.

Falling revenues in the North Sea oil industry present one side of the argument for increased automation. But Total expects that it will also make inspections more reliable and safer.

Dave Mackinnon, head of technology and innovation for Total, believes that autonomous robots are very much here to stay in the oil and gas industry.

“Total believes that robots have the potential to play an important role on offshore platforms,” he said. “We are on the cusp of delivering technology that will improve safety, reduce costs, and even prolong the life of North Sea operations.”

Internet of Business says

The use of robots and also drones for remote or offshore maintenance – particularly in hazardous environments – is both a growing application of the technology, and ‘low hanging fruit’ in regulatory terms.

For example, a number of startups are focusing on drone maintenance of offshore wind farms in order to prove that the technology works and is safe. Authorities are happy to approve these deployments as test cases, because there are few other people around and airspace is less crowded.

In this way, the offshore energy industry is both an ideal application of robotics in itself, and a proving ground for the technology.

Read more: Aerones creates drone to de-ice and service wind turbines

Read more: DJI and FLIR launch drone tech that saves lives

Read more: The world’s fastest drone fleet is ready to service the US

Read more: Robot teachers take classes at Finland primary school

Read more: Predictability key to robot-human collaboration, finds Disney research

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Tesla slammed by safety board after latest autonomous fatality

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US carmaker Tesla has been slammed by the US road safety board after confirming details of a fatal crash involving one of its vehicles last week.

Walter (Wei) Huang, the driver of a Tesla Model X SUV, was killed on March 23 when his car hit a concrete barrier on Highway 101, which connects San Francisco with Silicon Valley. He was reportedly on his way to work at Apple.

The company has announced that the car was in autonomous mode, using Tesla’s Autopilot technology, when it hit the barrier, and that Huang’s hands were not on the wheel – as they should have been – when the accident happened.

In a blog post on Tesla’s website, the company said:

“In the moments before the collision, which occurred at 9.27 a.m. on Friday, March 23rd, Autopilot was engaged with the adaptive cruise control follow-distance set to minimum.

“The driver had received several visual and one audible hands-on warning earlier in the drive and the driver’s hands were not detected on the wheel for six seconds prior to the collision. The driver had about five seconds and 150 metres of unobstructed view of the concrete divider with the crushed crash attenuator, but the vehicle logs show that no action was taken.

“The reason this crash was so severe is because the crash attenuator, a highway safety barrier which is designed to reduce the impact into a concrete lane divider, had been crushed in a prior accident without being replaced. We have never seen this level of damage to a Model X in any other crash.”

Tesla has been slammed by the US National Transportation Safety Board (NTSB) for releasing this information without alerting the agency beforehand, as it is required to do in a signed agreement.

The NTSB, which is still investigating the accident, said, “We take each unauthorised release seriously. However, this release will not hinder our investigation.”

Increased safety

Tesla has been swift to defend the safety record of its autonomous technologies after the incident, which saw the value of its shares plunge in a sell-off.

“Over a year ago, our first iteration of Autopilot was found by the US government to reduce crash rates by as much as 40 percent. Internal data confirms that recent updates to Autopilot have improved system reliability.

“In the US, there is one automotive fatality every 86 million miles across all vehicles from all manufacturers. For Tesla, there is one fatality, including known pedestrian fatalities, every 320 million miles in vehicles equipped with Autopilot hardware. If you are driving a Tesla equipped with Autopilot hardware, you are 3.7 times less likely to be involved in a fatal accident.

“Tesla Autopilot does not prevent all accidents – such a standard would be impossible – but it makes them much less likely to occur. It unequivocally makes the world safer for the vehicle occupants, pedestrians, and cyclists.”

The fatality occurred just one week after a pedestrian was killed by an autonomous Uber vehicle in Tempe, Arizona. However, it is not the first death involving a Tesla vehicle running on Autopilot. Two years ago, a driver was killed when an autonomous Tesla Model S drove into the side of a truck. It was reported that the driver may have been watching a Harry Potter movie in the vehicle at the time of the accident.

In the past Tesla has been criticised for talking about the safety of its technologies after serious accidents or fatalities. It addressed this point in its blog post, saying: “In the past, when we have brought up statistical safety points, we have been criticised for doing so, implying that we lack empathy for the tragedy that just occurred. Nothing could be further from the truth.

“We care deeply for and feel indebted to those who chose to put their trust in us. However, we must also care about people now and in the future whose lives may be saved if they know that Autopilot improves safety. None of this changes how devastating an event like this is or how much we feel for our customer’s family and friends. We are incredibly sorry for their loss.”

Read more: Uber: Self-driving cars ordered off road by US, sells to Grab

Read more: Toyota halts autonomous car tests after Uber accident

Internet of Business says

This latest fatality puts US regulators in a difficult position. While Arizona authorities took Uber’s self-driving cars off the road after a pedestrian was killed by one during an autonomous test, this latest fatality involves a technology, Autopilot, that is already built into production models.

The accident reveals the core problem with driverless technologies at present: in the two most recent fatalities, the general thrust of arguments has been to imply that the human drivers were at fault for either not looking at the road or not having their hands on the wheel – a logical absurdity with autonomous technologies.

Waymo CEO John Krafcik explained the distinction. “Tesla has driver-assist technology and that’s very different from our approach. If there’s an accident in a Tesla, the human in the driver’s seat is ultimately responsible for paying attention.”

Nevertheless, in both recent fatalities the technologies were driving the cars, regardless of whether the human drivers should have been paying more attention. This cannot be ignored.

Huang’s brother Will told ABC7 news that Walter had complained “Seven to 10 times that the car would swivel toward that same exact barrier during autopilot. Walter took it into dealership addressing the issue, but they couldn’t duplicate it there.”

The core question, then, is simple: should the developers of a technology that is still in its infancy seek to blame human drivers for every death? Questions like this will become increasingly commonplace as AI and autonomous systems become more dominant in our lives, calling into question longstanding legal concepts, such as liability, and ethical concepts, such as responsibility.

The subtext, therefore, is all about trust: human drivers need to trust autonomous technologies, but doing so makes them focus on things other than the road. To suggest that human drivers should concentrate on the road and the wheel while their vehicles are in autonomous mode is tantamount to suggesting that they shouldn’t trust the technology.

As we move towards completely autonomous systems, including driverless trucks and road vehicles that are designed purely for passengers, the law urgently needs to catch up.

Read more: New Baidu, Jaguar Land Rover driverless cars take to the road

Read more: Waymo turns the ignition on self-driving trucks

Read more: Fetch launches world’s first autonomous AI smart ledger

Read more: Pure Storage, NVIDIA launch enterprise AI supercomputer in a box

Read more: AI regulation & ethics: How to build more human-focused AI

Read more: Cambridge Analytica vs Facebook: Why AI laws are inadequate

 

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Apple Patent Application Aims to Put VR Systems in Autonomous Cars

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Apple’s patents might not be a clear indicator of what’s actually going to be a product anytime soon, but it does at least present a clear look at some of Apple’s lofty ideas. Continue reading
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Waymo may work with Honda on an autonomous delivery vehicle

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Last week, Waymo announced a partnership to build autonomous Jaguar vehicles for its upcoming self-driving taxi service, which will augment its existing fleet of Chryslers. But today Bloomberg reported that the Alphabet company is nearing a deal with…
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University of Michigan launches outdoor lab for autonomous drones

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The University of Michigan's autonomous vehicle testing grounds are no longer limited to earthbound machines. It just opened M-Air, a 9,600 square foot, four-story facility designed for testing autonomous aircraft outdoors. The complex lets researc…
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Fetch launches world’s first autonomous AI smart ledger

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Fetch.AI has announced the launch of what it claims is the world’s first adaptive, self-organising smart ledger technology for decentralised transactions.

Fetch is described as a next-generation protocol that enables autonomous economic agents (AEAs) to perform proactive economic activities. The technology allows AIs on both sides of an economic transaction to interface with each other, said the company in an announcement today.

In other words, the system enables AIs to buy and sell digital assets autonomously, from or to another AI, with contracts, payments, and execution all handled automatically.

The company says that corporations can interface their closed, internal networks with the Fetch network without exposing their proprietary IP.

According to the company, Fetch’s distributed ledger system also generates tokens that can be exchanged for utility value on the network, which provides an incentive for operating a node. In this sense, the system includes concepts ported over from cryptocurrency mining.

So how does it all work?

Removing the blocks from the chain

Fetch combines artificial intelligence, machine learning, and distributed ledger technologies to deliver what the company describes as a self-organising framework.

The underlying smart ledger combines elements of blockchain and directed acyclic graph technologies with built-in AI, a consensus mechanism, and a data architecture that “can support millions of agents transacting together”.

Together, the technologies can scale to millions of transactions per second at near zero cost, claimed the company today.

The new consensus mechanism is called Useful Proof of Work. Unlike traditional blockchains, the Proof of Work computations needed to secure the network aren’t abstract, according to Fetch. Instead, they are “redeployed to perform the machine learning tasks that give the ledger its intelligence”.

Using this new system, developers can build autonomous agents that might act on consumers’ or companies’ behalf, and which can be designed to address “almost any task”.

Who’s onboard?

Founded in 2016 and operating in stealth mode until today, the Fetch team includes original pioneers from DeepMind, the AI company subsequently acquired by Google, as well as economics and cybersecurity professors from Cambridge and Sheffield universities.

CTO Toby Simpson – who was part of the initial DeepMind team – said, “Autonomous economic agents are set to revolutionise commerce. They’re digital entities that can transact independently of human intervention and can represent people, machines, or themselves.

“Imagine a world that connects anything to anything, and everything to everything, where data, services, and information get up on their own two feet and deliver themselves with incredible precision.

“The Fetch digital world acts as the ultimate value exchange dating agency: each AI agent sees a space optimised in real time just for them, where the important things are right there.

“Autonomous agents can work together, or alone, to build solutions to complex problems by joining a disparate array of potentially useful data and services into one seamless experience.” 

Economic inefficiency

According to co-founder and CEO Humayun Sheikh – who was a founding investor in DeepMind – this radical approach is necessary to address what he called the “inefficiency inherent in today’s economy”.

“Today’s centralised systems and marketplaces result in silos and there isn’t a means to enable complex economic activity,” he said.

“For the first time, Fetch delivers a self-organising digital world that enables the discoverability of data for decision-making, the trading of excess capacity, energy, and computation, or the storage, transfer, and transportation of digital or physical assets.

“When you have  a decentralised collective intelligence and AI operating in the right environment, which our open network provides, an autonomous system like Fetch can solve problems before they even arise.”

The company provides a number of working examples. In the travel sector, Fetch says it is working to reduce the burden of planning complex journeys by using expert autonomous agents to organise trips, predict missed connections, and dynamically reroute journeys, rearrange travel plans, and rebook reservations without intervention.

In the energy sector, Fetch said it is working to deliver the most effective energy solutions to households without the friction of switching suppliers, potentially analysing each appliance’s unique energy demands.

And in the supply chain, Fetch says it is working to help the trillion-dollar steel sector to self-manage and optimise its supply chain “autonomously and collaboratively”, from raw material to finished product, including stock management, transport, financing, and insurance.

Jamie Burke, CEO of VC firm Outlier Ventures explained why he has been backing Fetch since 2016: “For the first time we can genuinely say we have not smart contracts, but instead a smart ledger.

“To date, blockchains haven’t been capable of even rudimentary intelligence and anyone wanting to use today’s dumb ledgers for anything complex, dynamic or predictive has been left severely wanting.” 

Fetch plans to provide code on GitHub and announce a range of corporate partnerships over the coming months. Fetch will be providing a comprehensive SDK allowing the development of agents in languages such as C++ and Python, as well as a set of frameworks to allow Web developers to design, configure, and author agents.

Internet of Business says

A fascinating and innovative technology, developed by an impressive team. It’s early days in this new launch, of course, and we plan to bring you deeper analysis and an interview with the Fetch team shortly.

In the meantime, questions must arise around transparency, antitrust concerns, distributed resources, and the risk of such a system automating unorthodox activities. We hope to bring you answers to those questions soon. CM

Read more: Fintech firm launches blockchain platform for legal contracts

Read more: Blockchain: Lose the block and chain to be useful, Capacilon MD | Q&A

Read more: Blockchain: “not solution to 90 percent of problems”, warns expert

Read more: IoT 101: How blockchain transforms manufacturing, supply chains

Read more: Bitcoin blockchain contains porn, say researchers. Not news, say coders

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Waymo Plans to Deploy The Largest Fleet of Autonomous Vehicles by 2020

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Hypothetical bumper stickers from the year 2020: “AI, take the wheel!” and “How is my car driving?”

That is to say, autonomous cars are coming. And, in spite of some recent setbacks, it seems inevitable. Dozens of companies have poured millions of dollars (and several lawsuits) into their technology. Now one of the few questions still undecided: which company will dominate?

Alphabet spinoff Waymo is making a pretty serious bid for it. The company recently revealed an “electrifying partnership” (their words, not ours) with Jaguar Land Rover.

The self-driving car company plans to deploy up to 20,000 high-end vehicles by 2020. Compare that to its current fleet of 600 self-driving Chrysler minivans and you get a sense of the staggering scale (and pace) at which Waymo plans to level up.

Image Credit: Waymo

The vehicle in question — a $ 69,500 Jaguar i-Pace announced earlier this month — brings the fight right to Tesla’s door. The Jag will appeal to an audience that has been salivating over Tesla’s most recent offerings, and cost almost $ 10,000 less than the Tesla Model X.

If Waymo succeeds, it will supplant General Motors, which hopes to produce a paltry 2,500 of its Cruise AV, its production-ready vehicle that features no steering wheel or pedals. But, importantly, GM might get there first — the company has filed for permission with the Department of Transportation in the hope of getting its Cruise AV on the road by 2019.

 

Image Credit: GM

Might that progress be slowed in light of the recent fatal incident involving a self-driving Uber car and a pedestrian?

Waymo chief executive John Krafcik was quick to distinguish Uber’s cars from Waymo’s.

“…We have a lot of confidence that our technology would be robust and would be able to handle situations like that,” he said at a convention panel at the National Automobile Dealers Association.

Clearly, the incident isn’t slowing Waymo down. In fact, since Waymo is exempt from the Arizona governor’s ban on Uber’s AVs, it could even motor past the competition. Waymo’s competing ride-hailing service is set to launch in Phoenix, Arizona later this year, though the exact launch date and rates have not been announced.

We’ll see whether, in the end, Waymo’s Jaguar i-Pace proves more appealing or luxurious to consumers who don’t want to ride around in a Chrysler minivan. Let’s face it: minivans are not that cool, even if they are self-driving.

 

 

The post Waymo Plans to Deploy The Largest Fleet of Autonomous Vehicles by 2020 appeared first on Futurism.

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Arizona Bans Uber’s Autonomous Vehicles Following Pedestrian Death

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Uber’s autonomous vehicles are no longer welcome in Arizona.

That’s according to the state’s governor Doug Ducey.

Around 10 PM on March 18, one of Uber’s autonomous vehicles struck a woman as she crossed a road in Tempe, Arizona. She later died from her injuries at a local hospital. This was the first time an AV caused a pedestrian fatality.

Yesterday, Ducey sent a letter to Uber CEO Dara Khosrowshahi responding to the incident:

As governor, my top priority is public safety. Improving public safety has always been the emphasis of Arizona’s approach to autonomous vehicle testing, and my expectation is that public safety is also the top priority for all who operate this technology in the state of Arizona. The incident that took place on March 18 is an unquestionable failure to comply with this expectation…

In the best interests of the people of my state, I have directed the Arizona Department of Transportation to suspend Uber’s ability to test and operate autonomous vehicles on Arizona’s public roadways.

Immediately following the crash, Uber suspended all autonomous vehicle testing nationwide.

The Technologies That Power Self-Driving Cars [INFOGRAPHIC]
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But what’s remarkable is that Ducey restricted the penalty to the one company responsible: Uber. Waymo, General Motors, Mobileye, and various other AV manufacturers are also testing in the state; in the wake of the pedestrian death, Ducey could have chosen to ban all AV testing outright. Instead, he chose to allow  to continue their testing in the state.

In fact, the other companies still allowed soon be able to take those test to the next level. Less than three weeks before the Uber incident, Ducey signed an executive order giving companies permission to test their AVs without a human driver behind the wheel.

It’s still possible that other states will suspend Uber, or other AV testing. But so far, fears that the incident would hinder the maturation of autonomous vehicle technology seem to be unfounded.

The post Arizona Bans Uber’s Autonomous Vehicles Following Pedestrian Death appeared first on Futurism.

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Uber suspended from autonomous vehicle testing in Arizona following fatal crash

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Uber has been suspended from testing autonomous vehicles in the state of Arizona following last week’s fatal crash in the city of Tempe, according to the Associated Press. The accident, which occurred at night and coincided with autonomous test driver Rafaela Vasquez looking down right before the moment of impact, left pedestrian 49-year-old Elaine Herzberg dead.

It is likely the first death caused by a self-driving vehicle, and the aftermath of the event has been severe for Uber, with the company immediately suspending self-driving operations in the state amid a US National Transportation Safety Board investigation. The Tempe Police Department is also conducting an investigation, which will eventually be turned over to the Maricopa…

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Uber says a single metric isn’t a clear indication of an autonomous car’s safety

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Drivers still had to take over once every 13 miles in Arizona, according to new documents The New York Times obtained.

In the days since a self-driving Uber vehicle killed a pedestrian in Tempe, Ariz., local police and federal agencies have yet determine whether Uber’s technology was at fault.

But new documents obtained by The New York Times show Uber’s technology had made little progress in the last year. The story details the series of setbacks the company faced in trying to get self-driving cars to market, including careless safety drivers who are supposed to take over test cars in case of emergencies.

The key stat underpinning the report is what’s known as “miles per intervention,” or the number of miles the car can drive on its own before the safety driver has to take over the car. The Times story cites internal documents showing Uber was unable to meet its goal of driving an average of 13 miles without a driver having to take back control as of March.

That’s not much better than its rate of intervention this time last year. In March 2017, documents Recode obtained showed Uber’s safety operators had to take back control of the cars an average of once per every 0.8 miles.

Uber wanted to spell out what this metric means and doesn’t mean in the wake of the fatality and sent this statement:

MPI is not a measure of the overall safety of our testing operations, and shouldn’t be interpreted as such. Miles per intervention is one of many metrics that we use to track our system’s improvement, but without context it can be one of the least useful. For example, depending on where and how it’s tested, the same software could result in significantly different MPI. Additionally, companies may define interventions differently from each other.

In other words, miles per intervention is a broad metric that includes most of the times drivers have had to take back control from the system over the course of a week.

The reasons for these interventions can include navigating unclear lane markings, the system overshooting a turn or driving in inclement weather. The stat excludes accidental disengagements, end-of-route disengagements and early takeovers.

Other metrics include the average number of miles between “critical” interventions — when a driver has to avoid causing harm, such as hitting pedestrians or causing material property damage and the average number of autonomous miles between “bad experiences” — things like jerky motions or hard braking, which are more likely to cause discomfort than damage.

Then there’s the total number of miles driven autonomously. The documents the Times obtained indicated Uber had driven 3 million miles as of March.

While other companies may define interventions differently, Uber’s rate of intervention in Arizona is far more frequent than that of its competitors’. For example, Alphabet’s self-driving company, Waymo, had a rate of 5,600 miles per intervention in California.

Still, this is by no means an indication that the technology was at fault in the fatal crash. It is, however, an indication of Uber’s slow technological progress with its self-driving cars.

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