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#439432 Nothing Can Keep This Drone Down

When life knocks you down, you’ve got to get back up. Ladybugs take this advice seriously in the most literal sense. If caught on their backs, the insects are able to use their tough exterior wings, called elytra (of late made famous in the game Minecraft), to self-right themselves in just a fraction of a second.

Inspired by this approach, researchers have created self-righting drones with artificial elytra. Simulations and experiments show that the artificial elytra can not only help salvage fixed-wing drones from compromising positions, but also improve the aerodynamics of the vehicles during flight. The results are described in a study published July 9 in IEEE Robotics and Automation Letters.

Charalampos Vourtsis is a doctoral assistant at the Laboratory of Intelligent Systems, Ecole Polytechnique Federale de Lausanne in Switzerland who co-created the new design. He notes that beetles, including ladybugs, have existed for tens of millions of years. “Over that time, they have developed several survival mechanisms that we found to be a source of inspiration for applications in modern robotics,” he says.

His team was particularly intrigued by beetles’ elytra, which for ladybugs are their famous black-spotted, red exterior wing. Underneath the elytra is the hind wing, the semi-transparent appendage that’s actually used for flight.

When stuck on their backs, ladybugs use their elytra to stabilize themselves, and then thrust their legs or hind wings in order to pitch over and self-right. Vourtsis’ team designed Micro Aerial Vehicles (MAVs) that use a similar technique, but with actuators to provide the self-righting force. “Similar to the insect, the artificial elytra feature degrees of freedom that allow them to reorient the vehicle if it flips over or lands upside down,” explains Vourtsis.

The researchers created and tested artificial elytra of different lengths (11, 14 and 17 centimeters) and torques to determine the most effective combination for self-righting a fixed-wing drone. While torque had little impact on performance, the length of elytra was found to be influential.

On a flat, hard surface, the shorter elytra lengths yielded mixed results. However, the longer length was associated with a perfect success rate. The longer elytra were then tested on different inclines of 10°, 20° and 30°, and at different orientations. The drones used the elytra to self-right themselves in all scenarios, except for one position at the steepest incline.

The design was also tested on seven different terrains: pavement, course sand, fine sand, rocks, shells, wood chips and grass. The drones were able to self-right with a perfect success rate across all terrains, with the exception of grass and fine sand. Vourtsis notes that the current design was made from widely available materials and a simple scale model of the beetle’s elytra—but further optimization may help the drones self-right on these more difficult terrains.

As an added bonus, the elytra were found to add non-negligible lift during flight, which offsets their weight.

Vourtsis says his team hopes to benefit from other design features of the beetles’ elytra. “We are currently investigating elytra for protecting folding wings when the drone moves on the ground among bushes, stones, and other obstacles, just like beetles do,” explains Vourtsis. “That would enable drones to fly long distances with large, unfolded wings, and safely land and locomote in a compact format in narrow spaces.” Continue reading

Posted in Human Robots

#439374 A model to predict how much humans and ...

Researchers at University of Michigan have recently developed a bi-directional model that can predict how much both humans and robotic agents can be trusted in situations that involve human-robot collaboration. This model, presented in a paper published in IEEE Robotics and Automation Letters, could help to allocate tasks to different agents more reliably and efficiently. Continue reading

Posted in Human Robots

#439366 Why Robots Can’t Be Counted On to Find ...

On Thursday, a portion of the 12-story Champlain Towers South condominium building in Surfside, Florida (just outside of Miami) suffered a catastrophic partial collapse. As of Saturday morning, according to the Miami Herald, 159 people are still missing, and rescuers are removing debris with careful urgency while using dogs and microphones to search for survivors still trapped within a massive pile of tangled rubble.

It seems like robots should be ready to help with something like this. But they aren’t.


A Miami-Dade Fire Rescue official and a K-9 continue the search and rescue operations in the partially collapsed 12-story Champlain Towers South condo building on June 24, 2021 in Surfside, Florida.

The picture above shows what the site of the collapse in Florida looks like. It’s highly unstructured, and would pose a challenge for most legged robots to traverse, although you could see a tracked robot being able to manage it. But there are already humans and dogs working there, and as long as the environment is safe to move over, it’s not necessary or practical to duplicate that functionality with a robot, especially when time is critical.

What is desperately needed right now is a way of not just locating people underneath all of that rubble, but also getting an understanding of the structure of the rubble around a person, and what exactly is between that person and the surface. For that, we don’t need robots that can get over rubble: we need robots that can get into rubble. And we don’t have them.

To understand why, we talked with Robin Murphy at Texas A&M, who directs the Humanitarian Robotics and AI Laboratory, formerly the Center for Robot-Assisted Search and Rescue (CRASAR), which is now a non-profit. Murphy has been involved in applying robotic technology to disasters worldwide, including 9/11, Fukushima, and Hurricane Harvey. The work she’s doing isn’t abstract research—CRASAR deploys teams of trained professionals with proven robotic technology to assist (when asked) with disasters around the world, and then uses those experiences as the foundation of a data-driven approach to improve disaster robotics technology and training.

According to Murphy, using robots to explore rubble of collapsed buildings is, for the moment, not possible in any kind of way that could be realistically used on a disaster site. Rubble, generally, is a wildly unstructured and unpredictable environment. Most robots are simply too big to fit through rubble, and the environment isn’t friendly to very small robots either, since there’s frequently water from ruptured plumbing making everything muddy and slippery, among many other physical hazards. Wireless communication or localization is often impossible, so tethers are required, which solves the comms and power problems but can easily get caught or tangled on obstacles.

Even if you can build a robot small enough and durable enough to be able to physically fit through the kinds of voids that you’d find in the rubble of a collapsed building (like these snake robots were able to do in Mexico in 2017), useful mobility is about more than just following existing passages. Many disaster scenarios in robotics research assume that objectives are accessible if you just follow the right path, but real disasters aren’t like that, and large voids may require some amount of forced entry, if entry is even possible at all. An ability to forcefully burrow, which doesn’t really exist yet in this context but is an active topic of research, is critical for a robot to be able to move around in rubble where there may not be any tunnels or voids leading it where it wants to go.

And even if you can build a robot that can successfully burrow its way through rubble, there’s the question of what value it’s able to provide once it gets where it needs to be. Robotic sensing systems are in general not designed for extreme close quarters, and visual sensors like cameras can rapidly get damaged or get so much dirt on them that they become useless. Murphy explains that ideally, a rubble-exploring robot would be able to do more than just locate victims, but would also be able to use its sensors to assist in their rescue. “Trained rescuers need to see the internal structure of the rubble, not just the state of the victim. Imagine a surgeon who needs to find a bullet in a shooting victim, but does not have any idea of the layout of the victims organs; if the surgeon just cuts straight down, they may make matters worse. Same thing with collapses, it’s like the game of pick-up sticks. But if a structural specialist can see inside the pile of pick-up sticks, they can extract the victim faster and safer with less risk of a secondary collapse.”

Besides these technical challenges, the other huge part to all of this is that any system that you’d hope to use in the context of rescuing people must be fully mature. It’s obviously unethical to take a research-grade robot into a situation like the Florida building collapse and spend time and resources trying to prove that it works. “Robots that get used for disasters are typically used every day for similar tasks,” explains Murphy. For example, it wouldn’t be surprising to see drones being used to survey the parts of the building in Florida that are still standing to make sure that it’s safe for people to work nearby, because drones are a mature and widely adopted technology that has already proven itself. Until a disaster robot has achieved a similar level of maturity, we’re not likely to see it take place in an active rescue.

Keeping in mind that there are no existing robots that fulfill all of the above criteria for actual use, we asked Murphy to describe her ideal disaster robot for us. “It would look like a very long, miniature ferret,” she says. “A long, flexible, snake-like body, with small legs and paws that can grab and push and shove.” The robo-ferret would be able to burrow, to wiggle and squish and squeeze its way through tight twists and turns, and would be equipped with functional eyelids to protect and clean its sensors. But since there are no robo-ferrets, what existing robot would Murphy like to see in Florida right now? “I’m not there in Miami,” Murphy tells us, “but my first thought when I saw this was I really hope that one day we’re able to commercialize Japan’s Active Scope Camera.”

The Active Scope Camera was developed at Tohoku University by Satoshi Tadokoro about 15 years ago. It operates kind of like a long, skinny, radially symmetrical bristlebot with the ability to push itself forward:

The hose is covered by inclined cilia. Motors with eccentric mass are installed in the cable and excite vibration and cause an up-and-down motion of the cable. The tips of the cilia stick on the floor when the cable moves down and propel the body. Meanwhile, the tips slip against the floor, and the body does not move back when it moves up. A repetition of this process showed that the cable can slowly move in a narrow space of rubble piles.

“It's quirky, but the idea of being able to get into those small spaces and go about 30 feet in and look around is a big deal,” Murphy says. But the last publication we can find about this system is nearly a decade old—if it works so well, we asked Murphy, why isn’t it more widely available to be used after a building collapses? “When a disaster happens, there’s a little bit of interest, and some funding. But then that funding goes away until the next disaster. And after a certain point, there’s just no financial incentive to create an actual product that’s reliable in hardware and software and sensors, because fortunately events like this building collapse are rare.”

Photo: Center for Robot-Assisted Search and Rescue

Dr. Satoshi Tadokoro inserting the Active Scope Camera robot at the 2007 Berkman Plaza II (Jacksonville, FL) parking garage collapse.

The fortunate rarity of disasters like these complicates the development cycle of disaster robots as well, says Murphy. That’s part of the reason why CRASAR exists in the first place—it’s a way for robotics researchers to understand what first responders need from robots, and to test those robots in realistic disaster scenarios to determine best practices. “I think this is a case where policy and government can actually help,” Murphy tells us. “They can help by saying, we do actually need this, and we’re going to support the development of useful disaster robots.”

Robots should be able to help out in the situation happening right now in Florida, and we should be spending more time and effort on research in that direction that could potentially be saving lives. We’re close, but as with so many aspects of practical robotics, it feels like we’ve been close for years. There are systems out there with a lot of potential, they just need all help necessary to cross the gap from research project to a practical, useful system that can be deployed when needed. Continue reading

Posted in Human Robots

#439357 How the Financial Industry Can Apply AI ...


THE INSTITUTE Artificial intelligence is transforming the financial services industry. The technology is being used to determine creditworthiness, identify money laundering, and detect fraud.

AI also is helping to personalize services and recommend new offerings by developing a better understanding of customers. Chatbots and other AI assistants have made it easier for clients to get answers to their questions, 24/7.

Although confidence in financial institutions is high, according to the Banking Exchange, that’s not the case with AI. Many people have raised concerns about bias, discrimination, privacy, surveillance, and transparency.

Regulations are starting to take shape to address such concerns. In April the European Commission released the first legal framework to govern use of the technology, as reported in IEEE Spectrum. The proposed European regulations cover a variety of AI applications including credit checks, chatbots, and social credit scoring, which assesses an individual’s creditworthiness based on behavior. The U.S. Federal Trade Commission in April said it expects AI to be used truthfully, fairly, and equitably when it comes to decisions about credit, insurance, and other services.

To ensure the financial industry is addressing such issues, IEEE recently launched a free guide, “Trusted Data and Artificial Intelligence Systems (AIS) for Financial Services.” The authors of the nearly 100-page playbook want to ensure that those involved in developing the technologies are not neglecting human well-being and ethical considerations.

More than 50 representatives from major banks, credit unions, pension funds, and legal and compliance groups in Canada, the United Kingdom, and the United States provided input, as did AI experts from academia and technology companies.

“This IEEE finance playbook is a milestone achievement and provides a much-needed practical road map for organizations globally to develop their trusted data and ethical AI systems.”

“We are in the business of trust. A primary goal of financial services organizations is to use client and member data to generate new products and services that deliver value,” Sami Ahmed says. He is a member of IEEE industry executive steering committee that oversaw the playbook’s creation.

Ahmed is senior vice president of data and advanced analytics of OMERS, Ontario’s municipal government employees’ pension fund and one of the largest institutional investors in Canada.

“Best-in-class guidance assembled from industry experts in IEEE’s finance playbook,” he says, “addresses emerging risks such as bias, fairness, explainability, and privacy in our data and algorithms to inform smarter business decisions and uphold that trust.”

The playbook includes a road map to help organizations develop their systems. To provide a theoretical framework, the document incorporates IEEE’s “Ethically Aligned Design” report, the IEEE 7000 series of AI standards and projects, and the Ethics Certification Program for Autonomous and Intelligent Systems.

“Design looks completely different when a product has already been developed or is in prototype form,” says John C.Havens, executive director of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. “The primary message of ethically aligned design is to use the methodology outlined in the document to address these issues at the outset.”

Havens adds that although IEEE isn’t well known by financial services regulatory bodies, it does have a lot of credibility in harnessing the technical community and creating consensus-based material.

“That is why IEEE is the right place to publish this playbook, which sets the groundwork for standards development in the future,” he says.

IEEE Member Pavel Abdur-Rahman, chair of the IEEE industry executive steering committee, says the document was necessary to accomplish three things. One was to “verticalize the discussion within financial services for a very industry-specific capability building dialog. Another was to involve industry participants in the cocreation of this playbook, not only to curate best practices but also to develop and drive adoption of the IEEE standards into their organizations.” Lastly, he says, “it’s the first step toward creating recommended practices for MLOps [machine-learning operations], data cooperatives, and data products and marketplaces.

Abdur-Rahman is the head of trusted data and AI at IBM Canada.

The playbook has two sections, a road map for how to build trusted AI systems and resources from experts.

The road map helps organizations identify where they are in the process of adopting responsible ethically aligned design: early, developing, advanced, or mature stage. This section also outlines 20 ways that trusted data and AI can provide value to operating units within a financial organization. Called use cases, the examples include cybersecurity, loan and deposit pricing, improving operational efficiency, and talent acquisition. Graphs are used to break down potential ethical concerns for each use case.

The key resources section includes best practices, educational videos, guidelines, and reports on codes of conduct, ethical challenges, building bots responsibly, and other topics. Among the groups contributing resources are the European Commission, IBM, the IEEE Standards Association, Microsoft, and the World Economic Forum. Also included is a report on the impact the coronavirus pandemic has had on the financial services industry in Canada. Supplemental information includes a list of 84 documents on ethical guidelines.

“We are at a critical junction of industrial-scale AI adoption and acceleration,” says Amy Shi-Nash, a member of the steering committee and the global head of analytics and data science for HSBC. “This IEEE finance playbook is a milestone achievement and provides a much-needed practical road map for organizations globally to develop their trusted data and ethical AI systems.”

To get an evaluation of the readiness of your organization’s AI system, you can anonymously take a 20-minute survey.

IEEE membership offers a wide range of benefits and opportunities for those who share a common interest in technology. If you are not already a member, consider joining IEEE and becoming part of a worldwide network of more than 400,000 students and professionals. Continue reading

Posted in Human Robots

#439297 5 Modern Technologies That Can Become a ...

A hundred years ago, it was difficult to imagine that humanity would be able to fly into space, create artificial intelligence, and instantly exchange information. Modern technology has greatly changed the way the current generation of people lives. But there are still incredible discoveries that humanity has not yet made. Among them is the solution …

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Posted in Human Robots