Connect with us

Tech

Accounting for uncertainty to help engineers design complex systems

Published

on

Accounting for uncertainty to help engineers design complex systems



Designing a complex electronic device like a delivery drone involves juggling many choices, such as selecting motors and batteries that minimize cost while maximizing the payload the drone can carry or the distance it can travel.

Unraveling that conundrum is no easy task, but what happens if the designers don’t know the exact specifications of each battery and motor? On top of that, the real-world performance of these components will likely be affected by unpredictable factors, like changing weather along the drone’s route.

MIT researchers developed a new framework that helps engineers design complex systems in a way that explicitly accounts for such uncertainty. The framework allows them to model the performance tradeoffs of a device with many interconnected parts, each of which could behave in unpredictable ways.

Their technique captures the likelihood of many outcomes and tradeoffs, giving designers more information than many existing approaches which, at most, can usually only model best-case and worst-case scenarios.

Ultimately, this framework could help engineers develop complex systems like autonomous vehicles, commercial aircraft, or even regional transportation networks that are more robust and reliable in the face of real-world unpredictability.

“In practice, the components in a device never behave exactly like you think they will. If someone has a sensor whose performance is uncertain, and an algorithm that is uncertain, and the design of a robot that is also uncertain, now they have a way to mix all these uncertainties together so they can come up with a better design,” says Gioele Zardini, the Rudge and Nancy Allen Assistant Professor of Civil and Environmental Engineering at MIT, a principal investigator in the Laboratory for Information and Decision Systems (LIDS), an affiliate faculty with the Institute for Data, Systems, and Society (IDSS), and senior author of a paper on this framework.

Zardini is joined on the paper by lead author Yujun Huang, an MIT graduate student; and Marius Furter, a graduate student at the University of Zurich. The research will be presented at the IEEE Conference on Decision and Control.

Considering uncertainty

The Zardini Group studies co-design, a method for designing systems made of many interconnected components, from robots to regional transportation networks.

The co-design language breaks a complex problem into a series of boxes, each representing one component, that can be combined in different ways to maximize outcomes or minimize costs. This allows engineers to solve complex problems in a feasible amount of time.

In prior work, the researchers modeled each co-design component without considering uncertainty. For instance, the performance of each sensor the designers could choose for a drone was fixed.

But engineers often don’t know the exact performance specifications of each sensor, and even if they do, it is unlikely the senor will perfectly follow its spec sheet. At the same time, they don’t know how each sensor will behave once integrated into a complex device, or how performance will be affected by unpredictable factors like weather.

“With our method, even if you are unsure what the specifications of your sensor will be, you can still design the robot to maximize the outcome you care about,” says Furter.

To accomplish this, the researchers incorporated this notion of uncertainty into an existing framework based on category theory.

Using some mathematical tricks, they simplified the problem into a more general structure. This allows them to use the tools of category theory to solve co-design problems in a way that considers a range of uncertain outcomes.

By reformulating the problem, the researchers can capture how multiple design choices affect one another even when their individual performance is uncertain.

This approach is also simpler than many existing tools that typically require extensive domain expertise. With their plug-and-play system, one can rearrange the components in the system without violating any mathematical constraints.

And because no specific domain expertise is required, the framework could be used by a multidisciplinary team where each member designs one component of a larger system.

“Designing an entire UAV isn’t feasible for just one person, but designing a component of a UAV is. By providing the framework for how these components work together in a way that considers uncertainty, we’ve made it easier for people to evaluate the performance of the entire UAV system,” Huang says.

More detailed information

The researchers used this new approach to choose perception systems and batteries for a drone that would maximize its payload while minimizing its lifetime cost and weight.

While each perception system may offer a different detection accuracy under varying weather conditions, the designer doesn’t know exactly how its performance will fluctuate. This new system allows the designer to take these uncertainties into consideration when thinking about the drone’s overall performance.

And unlike other approaches, their framework reveals distinct advantages of each battery technology.

For instance, their results show that at lower payloads, nickel-metal hydride batteries provide the lowest expected lifetime cost. This insight would be impossible to fully capture without accounting for uncertainty, Zardini says.

While another method might only be able to show the best-case and worst-case performance scenarios of lithium polymer batteries, their framework gives the user more detailed information.

For example, it shows that if the drone’s payload is 1,750 grams, there is a 12.8 percent chance the battery design would be infeasible.

“Our system provides the tradeoffs, and then the user can reason about the design,” he adds.

In the future, the researchers want to improve the computational efficiency of their problem-solving algorithms. They also want to extend this approach to situations where a system is designed by multiple parties that are collaborative and competitive, like a transportation network in which rail companies operate using the same infrastructure.

“As the complexity of systems grow, and involves more disparate components, we need a formal framework in which to design these systems. This paper presents a way to compose large systems from modular components, understand design trade-offs, and importantly do so with a notion of uncertainty. This creates an opportunity to formalize the design of large-scale systems with learning-enabled components,” says Aaron Ames, the Bren Professor of Mechanical and Civil Engineering, Control and Dynamical Systems, and Aerospace at Caltech, who was not involved with this research. 



Source link

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Tech

If You’re Building a Home Gym, Start With Dumbbells and a Yoga Mat

Published

on

If You’re Building a Home Gym, Start With Dumbbells and a Yoga Mat


To join or not to join a gym: That is the question. If you opt out of building a home gym, you can join a club and have access to more weights and machines. Friends and classes motivate you to keep coming, and that monthly bill keeps you disciplined. On the other hand, gym memberships are steep, workouts can get hijacked by bullies, and going to the gym is an additional commute.

My gym tardiness, however, will likely catch up to me. One of the most consistent messages from health and fitness experts today is that lifting weights has immeasurable benefits. Strength training allows us to keep doing the things we love well into our advanced years. It reduces blood sugar, lowers blood pressure, burns calories, and reduces inflammation. A recent review of studies in the British Journal of Sports Medicine by Harvard Medical School found that strength training is linked to lower risk for cardiovascular disease, diabetes, and cancer and provides a 10 to 17 percent lower overall risk of early death.

But you don’t need all the time and money in the world to have a great home gym. Reviews editor Adrienne So and I have been slowly adding to our existing, minimalist home gyms in our living rooms and garage—a roughly 10- by 10-foot patch in our basements and living rooms. There’s a ton of equipment out there, but for maximum results, I asked two physical therapists—Grace Fenske at Excel North Physical Therapy and Performance and Samuel Hayden at Limit Less Physical Therapy—for their recommendations.

Here’s a PT-recommended guide for an ultrasimple setup that will keep you pumped and motivated. Don’t see anything you like? Don’t forget to check out our existing guides to the Best Running Shoes, the Best Fitness Trackers, or the Best Walking Pads.

Jump To

Adjustable Dumbbells

Yes, these are very pricey. But people outgrow their small dumbbells very quickly, and if you bite the bullet early, adjustable dumbbells take up a lot less space than individual dumbbell or kettlebell sets. The Nüobell adjustable dumbbells required 38 patents and allow users to increase weight in increments of five pounds all the way up to 80 with a twist of the handle. Each dumbbell set replaces 32 individual dumbbells. In a cramped space, that’s a game changer.

The way that both Steph’s Nüobells and my Nike adjustable dumbbells work is that the full barbell fits into a cradle. (You can also mount the barbells in a stand.) When the user twists the handle to five pounds, the aluminum bar with grooves will grab onto the first hollowed-out plate, which is 2.5 pounds on each side of the barbell. With each subsequent turn of the handle the bar will pick up heavier weight in increments of five pounds. A safety hook at the bottom of the cradle ensures the barbell weight must be locked in place before lifting.

I like my Nike dumbbells because the end of the dumbbell is flat, which means I can rest it on its end on my thigh without putting a divot in my leg. Also, the plates aren’t round. If you have a big round dumbbell on the floor, or especially in your garage, it will find the nearest incline and roll away on top of a house pet or child. You can still take individual plates out of the rack if you need them for leverage under your heel or for mobility exercises. Whichever one you choose, though, both Steph and I recommend getting a floor stand to decrease strain on your back. —Adrienne So



Source link

Continue Reading

Tech

This AI Tool Will Tell You to Stop Slacking Off

Published

on

This AI Tool Will Tell You to Stop Slacking Off


I’ve tested a lot of software tools over the years designed to block distractions and keep you focused. None of them work perfectly, mostly because of context.

Reddit, for example, is something I should generally avoid during the workday, so I tend to block it—this is a good decision for me overall. The problem is that sometimes the only place I can find a particular piece of information online is in a Reddit thread, meaning that to get that information I need to turn off my distraction-blocking tool. Then I inevitably end up down some kind of rabbit hole.

This is the exact problem Fomi, a macOS distraction-blocking tool, is built to solve. The application asks you what you’re working on, then watches everything you do on your Mac desktop—every app you open—and uses AI to analyze what’s on your screen. The tool can tell, from context, whether you’re using a particular website productively or as a distraction.

Zach Yang, part of the team behind the app, tells me on Discord he dreamed up the app after talking with a friend who was studying for an MBA. “He needed YouTube for study videos, so web/app blockers didn’t work, and once he was watching, recommendations would often pull him away,” Yang says. “That’s when I started thinking about using AI to solve this. I built a small prototype to test whether current models were capable of distinguishing distraction from actual work, and the results were good enough that I decided to turn it into a real project.”

Fomi offers a three-day free trial. If you decide you like it, subscription plans cost $8 per month. However, since the tool uploads screenshots of your desktop to an AI model in the cloud, there are privacy concerns you will need to weigh before deciding if a tool like this is right for you.

Watch This Space

I’ve been trying out this application for a couple of days. The first time you launch it, you’re asked what you do day-to-day and what kind of tools you use to do it. Then, when it’s time to focus, you tell the software what you’re working on and which tools you plan to use while doing it.

As you work, a green dot and a timer appear at the top of the screen, surrounding your MacBook’s notch. If you switch to a potentially distracting application, the dot changes to yellow. If you start engaging in things that are clearly distractions, the dot turns red and an animated tomato splats across the screen. You’ll see a custom message telling you to get to work—the app calls out your specific distraction.

Courtesy of Justin Pot



Source link

Continue Reading

Tech

UKRI sets out strategy to make UK an AI leader by 2031 | Computer Weekly

Published

on

UKRI sets out strategy to make UK an AI leader by 2031 | Computer Weekly


UK Research and Innovation (UKRI) has laid out a strategy to help the UK boost its artificial intelligence (AI) capabilities, underpinned by research, access to shared assets, and support for innovators and universities.

It has published a six-point plan with a target completion date of 2031, by which time it says the research it supports will make the UK a global leader in explainable, human‑in‑the‑loop systems, agentic AI, edge computing and sustainable models. The 2031 target date also sets out ambitions for faster, reproducible science across disciplines through UKRI‑supported national AI testbeds and shared methods, as well as growing the research and innovation workforce to produce more deep technical experts and those who can drive AI companies and research groups.

From a data access perspective, UKRI’s goal is to open more environmentally sustainable compute and data foundations that provide equitable access to AI research resources through UKRI‑enabled infrastructure and new models released based on these resources, reusable, privacy‑respecting datasets, and Trusted Research Environments (TREs) that accelerate discovery and ensure data providers benefit from their contributions.

The UKRI’s AI safety objectives for 2031 include the UK becoming a co‑leader on global standards for safer, greener AI through UKRI international partnerships.

It also aims to foster a culture where the UK develops and fully harnesses the power of AI to drive economic growth, improve lives and livelihoods, and tackle major global and societal challenges.

Discussing the strategy, Charlotte Deane, senior responsible owner for the UKRI AI programme and executive chair of the Engineering and Physical Sciences Research Council, spoke about the UK’s strengths in mathematics, which puts it in a strong position to grow its AI ambitions. “We must make bold choices in areas where the UK can genuinely lead the world. UKRI will play a central role in backing the full innovation pathway from fundamental research to prototypes to scale-up,” she said.

“By uniting universities, businesses, industry and government, we can unlock the potential we have long had but have not yet fully mobilised,” Deane added.

Among the UKRI initiatives currently deployed are the Radar AI system, which detects faults on the railway network in real time, and the IXI Brain Atlas, which is supporting more than 40 clinical trials into degenerative diseases such as Alzheimer’s. 

Commenting on the strategy, UK AI minister Kanishka Narayan said: “The potential of combining our AI expertise with our peerless R&D community is a game-changer. This plan will harness AI to accelerate both the pace and possibility of scientific endeavour. 

“We are already seeing AI change the game for what’s possible in fields from health to energy and beyond. Boldly backing this technology is how we push our great British innovators to further success, and build a path to breakthroughs that boost our health, wealth and wellbeing.”

Deputy prime minister David Lammy, who is leading the UK delegation at the India AI Impact Summit, said: “The UK is backing its pioneering AI leadership with more than £1.6bn in investment to make sure the best of British expertise develops the next wave of AI innovations. Together, we are turning potential into progress, and that’s the ambition I am bringing to the AI Summit in India this week.”



Source link

Continue Reading

Trending