Category robotics

By Leah Burrows

What would it take to transform a flat sheet into a human face? How would the sheet need to grow and shrink to form eyes that are concave into the face and a convex nose and chin that protrude?

How to encode and release complex curves in shape-shifting structures is at the center of research led by the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and Harvard’s Wyss Institute of Biologically Inspired Engineering.

Over the past decade, theorists and experimentalists have found inspiration in nature as they have sought to unravel the physics, build mathematical frameworks, and develop materials and 3D and 4D-printing techniques for structures that can change shape in response to external stimuli.

However, complex multi-scale curvature has remained out of reach.

Now, researchers have created the most complex shape-shifting structures to date — lattices composed of multiple materials that grow or shrink in response to changes in temperature. To demonstrate their technique, team printed flat lattices that shape morph into a frequency-shifting antenna or the face of pioneering mathematician Carl Friedrich Gauss in response to a change in temperature.

The research is published in the Proceedings of the National Academy of Sciences.

“Form both enables and constrains function,” said L Mahadevan, Ph.D., the de Valpine Professor of Applied Mathematics, and Professor of Physics and Organismic and Evolutionary Biology at Harvard. “Using mathematics and computation to design form, and a combination of multi-scale geometry and multi-material printing to realize it, we are now able to build shape-shifting structures with the potential for a range of functions.”

“Together, we are creating new classes of shape-shifting matter,” said Jennifer A. Lewis, Sc.D., the Hansjörg Wyss Professor of Biologically Inspired Engineering at Harvard. “Using an integrated design and fabrication approach, we can encode complex ‘instruction sets’ within these printed materials that drive their shape-morphing behavior.”

Lewis is also a Core Faculty member of the Wyss Institute.

To create complex and doubly-curved shapes — such as those found on a face — the team turned to a bilayer, multimaterial lattice design.

“The open cells of the curved lattice give it the ability to grow or shrink a lot, even if the material itself undergoes limited extension,” said co-first author Wim M. van Rees, Ph.D., who was a postdoctoral fellow at SEAS and is now an Assistant Professor at MIT.

To achieve complex curves, growing and shrinking the lattice on its own isn’t enough. You need to be able to direct the growth locally.

“That’s where the materials palette that we’ve developed comes in,” said J. William Boley, Ph.D., a former postdoctoral fellow at SEAS and co-first author of the paper. “By printing materials with different thermal expansion behavior in pre-defined configurations, we can control the growth and shrinkage of each individual rib of the lattice, which in turn gives rise to complex bending of the printed lattice both within and out of plane.” Boley is now an Assistant Professor at Boston University.

The researchers used four different materials and programmed each rib of the lattice to change shape in response to a change in temperature. Using this method, they printed a shape-shifting patch antenna, which can change resonant frequencies as it changes shape.

To showcase the ability of the method to create a complex surface with multiscale curvature, the researchers decided to print a human face. They chose the face of the 19th century mathematician who laid the foundations of differential geometry: Carl Friederich Gauss. The researchers began with a 2D portrait of Gauss, painted in 1840, and generated a 3D surface using an open-source artificial intelligence algorithm. They then programmed the ribs in the different layers of the lattice to grow and shrink, mapping the curves of Gauss’ face.

This inverse design approach and multimaterial 4D printing method could be extended to other stimuli-responsive materials and be used to create scalable, reversible, shape-shifting structures with unprecedented complexity.

“Application areas include, soft electronics, smart fabrics, tissue engineering, robotics and beyond,” said Boley.

“This work was enabled by recent advances in posing and solving geometric inverse problems combined with 4D-printing technologies using multiple materials. Going forward, our hope is that this multi-disciplinary approach for shaping matter will be broadly adopted,” said Mahadevan.

This research was co-authored by Charles Lissandrello, Mark Horenstein, Ryan Truby, and Arda Kotikian. It was supported by the National Science Foundation and Draper Laboratory.

By Kourosh Hakhamaneshi

In this post, we share some recent promising results regarding the applications of Deep Learning in analog IC design. While this work targets a specific application, the proposed methods can be used in other black box optimization problems where the environment lacks a cheap/fast evaluation procedure.

So let’s break down how the analog IC design process is usually done, and then how we incorporated deep learning to ease the flow.

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At its core, the Coapt Gen2 system uses algorithmic pattern classification to determine wearers' intuitive, real-time intent for moving the joints of a prosthetic arm and/or hand.

The good news is progress is being made as the industry's best minds address each issue when it comes up. The one thing we can say with confidence is that tomorrow's vehicle will run on data...tons and tons of data which is comforting for flash industry people.

One of the biggest urban legends growing up in New York City were rumors about alligators living in the sewers. This myth even inspired a popular children’s book called “The Great Escape: Or, The Sewer Story,” with illustrations of reptiles crawling out of apartment toilets. To this day, city dwellers anxiously look at manholes wondering what lurks below. This curiosity was shared last month by the US Defense Department with its appeal for access to commercial underground complexes.

The US military’s research arm, DARPA, launched the Subterranean (or SubT) Challenge in 2017 with the expressed goal of developing systems that enhance “situational awareness capabilities” for underground missions. While the prospect of armies utilizing machines to patrol sunken complexes conjures up images of the Matrix, in reality one of the last frontiers to be explored on Earth is below the surface. As SubT moves closer to its culminating event planned for 2021, the agency is beginning the first phase of three planned real-world tests. According to the contest description the initial focus area will be “human-made tunnel systems,” followed by “underground urban environments such as mass transit and municipal infrastructure,” and then concluding with “naturally occurring cave networks.” This summer DARPA issued a Request For Information for subsurface infrastructure in the interest of “global security and disaster-related search and rescue missions.”

Competing technologists will have the chance to win $2 million for hardware inventions and $750,000 for software innovations that “disruptively and positively impact how the underground domain is leveraged.” The types of solutions being considered include platforms “to rapidly map, navigate, and search unknown complex subterranean environments to locate objects of interest.” In further explaining the objectives, Timothy Chung, DARPA program manager, said: “One of the main limitations facing warfighters and emergency responders in subterranean environments is a lack of situational awareness; we often don’t know what lies beneath.” Chung’s boss, Fred Kennedy, Director of the Tactical Technology Office, confirmed, “We’ve reached a crucial point where advances in robotics, autonomy, and even biological systems could permit us to explore and exploit underground environments that are too dangerous for humans. Instead of avoiding caves and tunnels, we can use surrogates to map and assess their suitability for use.” Kennedy even coined a catch phrase for the challenge – “making the inaccessible accessible.” 

In an abandoned Pennsylvania coal mine, on a sweltering August afternoon, eleven teams from across the globe came with 64 terrestrial robots, 20 unmanned aerial vehicles and one autonomous blimp to compete in the first wave of the SubT Challenge. The course included four events each lasting an hour deep inside the mine, which was originally built by the Pittsburgh Coal Company in 1910. Each team’s fleet of machines had to autonomously locate, identify and record 20 items or artifacts. The only team to score in double digits in all four independent runs was Explorer of Carnegie Mellon University. CMU is a DARPA Challenge favorite with a winning record that includes the 2007 Urban Challenge and 2015 Robotics Challenge. This year it had the distinct advantage of being local, scouting out the location beforehand to better plan its tactics for live competition. As Courtney Linder of Popular Mechanics writes, “Explorer regularly practiced at the Tour-Ed Mine in Tarentum, which is normally only frequented by tourists who want to check out a coal mine formerly owned by Allegheny Steel. They periodically flew drones and watched their ground robots exploring the cavernous, maze-like depths.”

The biggest hurdles for teams competing below ground are the lack of Global Position System (GPS) signals and WIFI communications. To safely navigate the cavernous course of these GPS-denied environments, SubT machines had to rely solely on a fusion of on-board sensors, including: LIDAR, cameras and radar. In explaining how his team won to the Pittsburgh Post-Gazette, CMU lead, Sebastian Scherer said they employed up to eight robots that created its own WIFI network to “talk” to each other while simultaneously mapping the environment with its sensors. Deploying a swarm approach, the robots acted as a collective unit working together to fill in data gaps, which meant that even if one went offline it was still able to pilot using its onboard systems and previously downloaded maps. Leading up to the competition the CMU team utilized computer simulations to strategize its approach, but understood the limitations of exclusively planning in the virtual world. As Scherer’s collaborator, Matt Travers, explains, “Our system may work perfectly in simulation and the first time we deploy, we may take the exact same software from the simulation and put it in the robot and it drives right into a wall and you go figure out why.” CMU’s geographic proximity to the test site seemingly played a critical role in their team achieving high scores.

While Explorer walked off with some nominal prize money, all eleven teams are committed to the same goal of full autonomy regardless of the environment and manual input. As Travers exclaims, “We’d like to build a system that’s going to be agnostic to the types of mobility challenges that we’ll face. And this is certainly a difficult thing to do.” Reflecting on the August gathering, the creativity of invention unified a global community towards a single purpose of saving lives. In the words of the program’s organizer, Chung, “We are inspired by the need to conduct search and rescue missions in a variety of underground environments, whether in response to an incident in a highly populated area, a natural disaster, or for mine rescue.” The next round will take place in February quite possibly in the sewers of New York City (alligators and all). As Chung cautions the contestants, “Prepare for a few new surprises. The SubT Challenge could be compared to a triathlon. DARPA is not looking just for the strongest swimmer, runner, or cyclist, but rather integrated solutions that can do all three.”

AI is everywhere. Today it helps you find something faster using your smartphone and voice assistant. Besides that, many other sectors use AI and machine learning to improve their working processes and make them smarter.

Spot is a small four-legged robot that resembles—well, a dog. It might not fetch your slippers, but it is very versatile. It weighs about 66 pounds, about what a large dog weighs.

Student teams are developing an autonomous rover and payload-deploying drone to find and safely destroy hidden munitions that kill or maim as many as 20,000 people around the world each year.

The European Robotics League (ERL) presents the SciRoc Challenge, a new robotics competition on smart cities that occurs every two years in a European city. Funded by the European Commission’s Horizon 2020 framework programme, the first SciRoc challenge takes place in the city of Milton Keynes, United Kingdom. In the context of smart shopping, robots interact with the Milton Keynes Data Hub (MK:DataHub) in a shopping mall. They update stock lists, take customers’ orders or find out the location of a person in need. On the third day of the competition, teams continued competing in the five different episodes and the public could see the first trials in the emergency category. The aerial teams were ready to start delivering autonomously the first-aid kit to the mannequin placed inside the flying arena!

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The European Robotics League (ERL) presents the SciRoc Challenge, a new robotics competition on smart cities that occurs every two years in a European city. Funded by the European Commission’s Horizon 2020 framework programme, the first SciRoc challenge takes place in the city of Milton Keynes, United Kingdom. In the context of smart shopping, robots interact with the Milton Keynes Data Hub (MK:DataHub) in a shopping mall. They update stock lists, take customers’ orders or find out the location of a person in need. On the third day of the competition, teams continued competing in the five different episodes and the public could see the first trials in the emergency category. The aerial teams were ready to start delivering autonomously the first-aid kit to the mannequin placed inside the flying arena!

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As robots grow in popularity, expect to see them in more common, repeatable tasks – like oil changes and tire replacements and rotations – to create increased efficiencies in service operations.

Box opening robots, while on a smaller scale, can eliminate the need for workers to handle blades. Unfortunately, box opening robots are not as common as the more traditional six-axis or SCARA robot models.

Backed by True Ventures and Ubiquity Ventures, the Austin-based robotics company is announcing its first full-time hospital customer implementing the robot full-time

Local manufacturers don't want to run 1-2 parts because it interrupts their workflow. They would much rather get an order for 1,000 pieces than have to stop, load material for your job, setup the machine, cut it, ship it etc.

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