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MIT’s new algorithm helps robots collaborate to get work done



Algorithm Coordinates Robot Teams

Researchers at MIT have developed an algorithm that coordinates robot teams for missions such as mapping or search and rescue in challenging, unpredictable environments. Credit: Jose Luis Olivares, Massachusetts Institute of Technology

The algorithm allows teams of robots to complete missions such as mapping or search and rescue operations with minimal effort.

Sometimes one robot is not enough.

Consider a search and rescue mission to find a traveler lost in the woods. Rescuers may want to send a squad of wheeled robots to roam the forest, perhaps with drones surveying the area from above. The advantages of a team of robots are clear. But organizing this team is not easy. How to prevent robots from duplicating each other’s efforts and wasting energy on an intricate search path?

Massachusetts Institute of Technology Researchers have developed an algorithm that ensures the fruitful collaboration of groups of robots that collect information. Their approach is based on a balance between collected data and expended energy, making it impossible for a robot to perform a wasteful maneuver to obtain only a fraction of the information. The researchers say this assurance is vital to the success of robot teams in complex, unpredictable environments. “Our method is convenient because we know it won’t fail due to the worst performance of the algorithm,” says Xiaoyi Tsai, a graduate student in the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology (AeroAstro).

The study will be presented at the IEEE International Conference on Robotics and Automation in May. Tsai is the lead author of the article. Its co-authors include Jonathan Howe, professor of aeronautics and astronautics at the Massachusetts Institute of Technology. Brent Schlotfeldt and George J. Pappas of the University of Pennsylvania; and Nikolai Atanasov of the University of California, San Diego.

Robot teams often rely on one general rule of thumb when gathering information: the more, the better. “It was assumed that gathering more information would never hurt,” Tsai says. “If there is a certain amount of battery life, let’s just use everything to get as much as possible.” This task is often performed sequentially – each robot evaluates the situation one by one and plans its trajectory. This is a simple procedure and usually works well when information is the only goal. But problems arise when energy efficiency becomes an important factor.

Tsai says the benefits of collecting additional information often diminish over time. For example, if you already have 99 photos of the forest, it might not be worth sending the robot on a long quest to take the hundredth. “We want to know about the trade-off between information and energy,” Tsai says. “It’s not always good to have more robots moving around. In fact, things could be worse when you consider the cost of energy. “

Researchers have developed a robot team scheduling algorithm that optimizes the balance between energy and information. The “objective function” of the algorithm, which determines the value of the task proposed by the robot, takes into account the diminishing benefit from the collection of additional information and the increase in the cost of energy. Unlike previous scheduling methods, it doesn’t just assign tasks to robots sequentially. “It’s more of a collaborative effort,” Tsai says. “The robots themselves come up with a team plan.”

Cai’s method, called distributed local search, is an iterative approach that improves team productivity by adding or removing individual robot paths from the team’s overall plan. First, each robot independently generates a set of potential trajectories that it can follow. Each robot then proposes its own trajectories to the rest of the team. The algorithm then accepts or rejects each person’s proposal, depending on whether it increases or decreases the team’s objective function. “We let the robots plan their trajectories on their own,” Tsai says. “We only allow them to negotiate when they need to come up with a team plan. So this is pretty distributed computing. “

Distributed local search has proven its strength in computer simulations. The researchers compared their algorithm to competitors by coordinating the work of a simulated team of 10 robots. Although distributed local search took slightly longer computational time, it ensured the successful completion of the robot mission, in part because none of the team members got bogged down on a useless expedition for minimal information. “This is a more expensive method,” Tsai says. “But we are increasing productivity.”

According to Jeff Hollinger, a robotics scientist at the University of Oregon, a robotics at the University of Oregon who was not involved in the study, it could one day help robot teams solve real-world information gathering problems where energy is a limited resource. “These methods are applicable when the robot team needs to find a compromise between measurement quality and energy consumption. This will include aerial surveillance and ocean monitoring. ”

Tsai also points to potential applications in mapping and search and rescue operations that rely on efficient data collection. “Improving this core information gathering capability will be very effective,” he says. The researchers then plan to test their algorithm on teams of robots in the lab, including drones and wheeled robots.

Ref: “Collecting Non-Monotonic Energy Efficient Information for Diverse Robot Teams” Xiaoi Tsai, Brent Schlotfeldt, Kasra Hosussi, Nikolai Atanasov, George J. Pappas and Jonathan P. Howe, March 26, 2021, Computer Science> Robotics
arXiv: 2101.11093

This study was funded in part by Boeing and the DCIST CRA of the Army Research Laboratory.

Originally reported by Source link

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Farming robots are the future – we must prepare now to avoid dystopia



Dystopian Farm Robots

This illustration shows the scenario of a utopian farming robot. Credit: Natalis Lorenz.

This is no longer science fiction, farm robots are already here – and they have created two possible extremes for the future of agriculture and its impact on the environment, says agricultural economist Thomas Daum in an article published July 13, 2021 in Science & Society. Journal Trends in ecology and evolution… One of them is a utopia, in which entire parks of small intelligent robots work in harmony with nature to produce a variety of organic crops. Another is a dystopia in which large, tractor-like robots conquer the landscape with heavy machinery and artificial chemicals.

He describes the utopian scenario as a mosaic of rich green fields, streams, wild flora and fauna, where fleets of small robots powered by sustained energy flutter around the fields, their buzzing mingling with the chirping of insects and the song of birds. “It’s like a Garden of Eden,” says Daum (@ThomDaum), a research associate at the University of Hohenheim in Germany who studies agricultural development strategies. “Small robots can help conserve biodiversity and combat climate change in ways that have never been possible before.”

He suggests that a utopian scenario that is too laborious for conventional farming, but possible with robots working around the clock, 7 days a week, is likely to benefit the environment in many ways. Plants would be more varied and the soil richer in nutrients. Thanks to micro-spraying of biopesticides and laser weed removal, nearby water, insect populations and soil bacteria will also become healthier. Organic crop yields, which are now often lower than traditional crop yields, will be higher and the impact of agriculture on the environment will be greatly reduced.

Dystopian farm robots

This illustration shows the scenario of a dystopian farming robot. Credit: Natalis Lorenz.

However, he believes that a parallel future with negative environmental consequences is quite possible. In this scenario, he says, large but technologically crude robots will bulldoze the natural landscape, and multiple monocultural cultures will dominate the landscape. Large fences would isolate people, farms and wildlife from each other. Once people are removed from farms, agrochemicals and pesticides can be used more widely. The ultimate goals will be structure and control: qualities that these simpler robots excel at, but which are likely to have detrimental effects on the environment.

While he notes that it’s unlikely the future will be limited to pure utopia or pure dystopia, by creating these two scenarios, Daum hopes to spark a conversation in what he sees as a crossroads in time. “Both utopia and dystopia are possible from a technological point of view. But without the right policy barriers, we could end up in a dystopia without even wanting to, if we don’t discuss it now, ”says Daum.

But this impact is not just limited to the environment – it affects normal people as well. “Robotic farming can also specifically impact you as a consumer,” he says. “In utopia, we don’t just grow crops – we have a lot of fruits and vegetables, the relative prices of which will fall, so a healthier diet will become more affordable.”

The small robots described in Daum’s utopian scenario would also be more suitable for small farmers who would find it easier to afford or share them through services like Uber. On the contrary, he argues that a family farm is less likely to survive in a dystopian scenario: only large producers, he says, will be able to manage huge tracts of land and high costs for large machinery.

In parts of Europe, Asia and Africa, where there are currently many small farms, deliberate efforts to implement a utopian scenario offer clear advantages. The situation is more difficult in countries such as the United States, Russia or Brazil, which have historically been dominated by large farms producing large volumes of low-value grains and oilseeds. There, small robots that are less efficient at performing energy-intensive tasks like threshing corn may not always be the most cost-effective option.

“While it is true that the preconditions for small robots are more complex in these areas,” he says, “even with large robots – or a mixture of small and large ones – we can take steps towards utopia with practices like interbreeding, having hedges. agroforestry and the shift from large farms to smaller plots of land owned by large farmers. Some of these methods may even pay off to farmers when robots can do their job as previously unprofitable methods become profitable. ”

To do this, Daum said, you need to act now. While some aspects of the utopian scenario, such as laser weeding, are already developed and ready for widespread adoption, funding must go to other aspects of machine learning and artificial intelligence in order to develop robots intelligent enough to adapt to complex unstructured farming systems. Policy changes are also needed and can take the form of subsidies, regulations, or taxes. “In the European Union, for example, farmers receive money when they perform certain landscape services, such as growing many trees or rivers on their farms,” he says.

While it may seem like a dystopian scenario is more likely, it is not the only way forward. “I think utopia is achievable,” says Daum. “It won’t be as easy as a dystopia, but it’s quite possible.”

Link: “Farming robots: ecological utopia or dystopia?” Thomas Daum, July 13, 2021 Trends in ecology and evolution
DOI: 10.1016 / j.tree.2021.06.002

This work was supported by the “Companion Research Program for Agricultural Innovation”, which is funded by the German Federal Ministry for Economic Cooperation and Development (BMZ).

Originally reported by Source link

The featured images are, as they appear on the original report.

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Dynamic control of THz wavefronts due to rotation of layers of cascade metasurfaces



Metadevice for Dynamically Controlling THz Wavefronts

Meta-device for dynamic control of THz wavefronts by rotating layers of cascade metasurfaces. Credit: Shanghai University.

Cascading metasurfaces for dynamic control of THz wave fronts

Electromagnetic (EM) waves in terahertz (THz) mode are used for critical applications in communications, security imaging, and bio and chemical sensing. This widespread applicability has led to significant technological progress. However, due to the weak interaction between natural materials and THz waves, conventional THz devices are usually cumbersome and ineffective. Although ultra-compact active devices in the THz range do exist, modern electronic and photonic approaches to dynamic control are ineffective.

Recently, the rapid development of metasurfaces has opened up new opportunities for creating highly efficient ultra-compact devices in the THz range for dynamic wavefront control. Ultra-thin metamaterials formed by subwavelength planar microstructures (i.e., metaatoms), metasurfaces allow tuning optical responses to control the fronts of electromagnetic waves. By creating metasurfaces that have certain predefined phase profiles for transmitted or reflected waves, scientists have demonstrated exciting wave manipulation effects such as abnormal light deflection, polarization manipulation, photon spin hall and holograms.

Dynamic beam steering metaservice

Demonstration of the dynamic beam steering meta-device: (a) Schematic of the meta-device, which consists of two layers of transmissive metasurfaces aligned with a motorized turntable. (b) top view (left) and (c) bottom view (right) of a SEM image of the fabricated meta-device. (d) Diagram of the experimental setup shown to characterize the meta-device. (e) Experimental and (f) simulated far-field scattering power distribution with a meta device illuminated with 0.7 THz LCP light and evolving along path I at different times. (g) Evolution of the directions of the transmitted waves on the sphere of direction k when the meta device moves along Path I and Path II, with the solid line (asterisks) denoting the results of the simulation (experiment). Here, the blue area denotes the solid angle for beam steering coverage. Credit: X. Cai et al., Doi 10.1117 / 1.AP.3.3.036003.

Moreover, the integration of active elements with individual meta-atoms within passive metasurfaces allows the creation of “active” meta-devices that can dynamically manipulate the fronts of electromagnetic waves. While active elements in deep subwavelengths are easy to find in microwave mode (e.g. PIN diodes and varactors) and successfully contribute to active meta-devices for beam steering, programmable holograms, and dynamic imaging, they are difficult to create at frequencies above THz. … This difficulty stems from size limitations and significant ohmic losses in electronic circuits. Although terahertz frequencies can drive terahertz beams uniformly, they usually cannot dynamically manipulate terahertz wave fronts. Ultimately this is due to the lack of local tuning capabilities at subwavelength depth scales in this frequency domain. Therefore, developing new approaches to avoid local customization is a priority.

As reported in Advanced PhotonicsResearchers from Shanghai University and Fudan University have developed a general structure and meta-devices to achieve dynamic control of THz wave fronts. Instead of locally controlling individual meta-atoms in the THz metasurface (for example, via a PIN diode, varactor, etc.), They change the polarization of the light beam using rotating multilayer cascade metasurfaces. They demonstrate that rotating different layers (each exhibiting a specific phase profile) in a cascade meta-device at different speeds can dynamically change the effective Jones matrix property of the entire device, achieving unusual manipulations with the wavefront and polarization characteristics of terahertz rays. Two meta-devices are demonstrated: the first meta-device can effectively redirect a normally incident THz beam for scanning in a wide range of solid angles, and the second can dynamically manipulate both the wavefront and polarization of the THz beam.

This paper proposes an attractive alternative way to achieve inexpensive dynamic control of THz waves. The researchers hope this work will inspire future applications of terahertz radars as well as bio and chemical sensing and imaging.

Reference: “Dynamic control of terahertz wavefronts with cascading metasurfaces” Xiaodong Tsai, Rong Tang, Haoyang Zhou, Qiushi Li, Shaoji Ma, Dongyi Wang, Tong Liu, Xiaohui Lin, Wei Tang, Qiong He, Shii Xiao, and Lei Zhou, June 26 … 2021, Advanced Photonics
DOI: 10.1117 / 1.AP.3.3.036003

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Take part in ESA Space Camp 2021



Take part in ESA Space Camp 2021

Space App Camp 2021. Credit: ESA.

ESA invites up to 25 dedicated mobile app developers and AI and machine learning specialists related to Earth observation from space to join this year’s Space App Camp, which will be a virtual event for eight weeks, from July 20 to September 20. …

The Space App Camp aims to make Earth observation data and services available to a wide range of citizens using their smartphones or personal devices. Numerous Earth observation satellites, including Copernicus Sentinel missions, collect a huge amount of data. This big data from space uncovers information about the atmosphere, land and water of our planet and offers countless possibilities for creating compelling, even transformative applications when combined with mobile applications.

Space App Camp attendees will experience Copernicus data and learn how big data from space can enrich mobile apps with a dedicated Earth observation data API. The 2021 virtual edition revolves around an expanded collaboration with ESA’s F-Lab, whose mission is to accelerate future Earth observation through new transformational ideas, and to select, develop, test and develop the most promising concepts.

2020 space camp winner

Quifer (aQuifer sUrveillance by sentInel InterFERometry) won the top prize in Space App Camp 2020. It uses terrain data from the Copernicus Sentinel-1 mission, combined with big data and artificial intelligence to monitor water use. Credit: ESA.

Although this is the tenth Space app campThis is the first time the camp has offered an expanded mentoring program that includes an end-to-end training and mobile software development scheme lasting eight weeks, supported by experts in Earth observation, artificial intelligence, intellectual property protection and business. development.

Winners will be awarded cash prizes of up to € 2,500 and a unique Earth observation support package that will allow them to continue working on their winning app idea. They will also be invited to participate in ESA exhibitions. Φ-week and Living Planet Symposium, with all expenses covered.

There is also a unique prize in the form of an Earth Observation Support Package worth around € 3,500. This includes technical advice on Earth observation data, eight hours of software development services, access to a global network of Earth observation experts in application and technical fields, and support from professional ESA business developers.

Carlos Garcia, member of the 2020 winning team, says: “The ESA Space App Camp is a great opportunity to build an app from scratch with guidance from tier 1 professionals. Although everything was virtual in my year, it was a fantastic learning experience – blocking the week and dedicating myself to building a meaningful app. “

The deadline for applications is July 8, 2021. Interested students, entrepreneurs, researchers, developers, and economists can register online individually or in a team (up to four people). This year’s edition is specifically targeted at contributors with profiles in mobile app development, Earth observation app development, machine learning, artificial intelligence, and business development.

To participate in the 8-week mentoring program from July 20 to September 20, 2021, up to 25 participants will be selected, within which special training and development sessions will be held every two weeks.

Since Space App Camp was created 10 years ago, about 480 developers from 30 countries have applied to participate and more than 60 applications have been developed. Some of them have already found use in commercially viable applications.

Originally reported by Source link

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