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Engineers, using artificial intelligence and wearable cameras, now aim to help robotic exoskeletons walk by themselves.
Increasingly, researchers around the world are developing lower-body exoskeletons to help people walk. These are essentially walking robots users can strap to their legs to help them move.
One problem with such exoskeletons: They often depend on manual controls to switch from one mode of locomotion to another, such as from sitting to standing, or standing to walking, or walking on the ground to walking up or down stairs. Relying on joysticks or smartphone apps every time you want to switch the way you want to move can prove awkward and mentally taxing, says Brokoslaw Laschowski, a robotics researcher at the University of Waterloo in Canada.
Scientists are working on automated ways to help exoskeletons recognize when to switch locomotion modes — for instance, using sensors attached to legs that can detect bioelectric signals sent from your brain to your muscles telling them to move. However, this approach comes with a number of challenges, such as how how skin conductivity can change as a person’s skin gets sweatier or dries off.
Now several research groups are experimenting with a new approach: fitting exoskeleton users with wearable cameras to provide the machines with vision data that will let them operate autonomously. Artificial intelligence (AI) software can analyze this data to recognize stairs, doors, and other features of the surrounding environment and calculate how best to respond.
Laschowski leads the ExoNet project, the first open-source database of high-resolution wearable camera images of human locomotion scenarios. It holds more than 5.6 million images of indoor and outdoor real-world walking environments. The team used this data to train deep-learning algorithms; their convolutional neural networks can already automatically recognize different walking environments with 73 percent accuracy “despite the large variance in different surfaces and objects sensed by the wearable camera,” Laschowski notes.
According to Laschowski, a potential limitation of their work their reliance on conventional 2-D images, whereas depth cameras could also capture potentially useful distance data. He and his collaborators ultimately chose not to rely on depth cameras for a number of reasons, including the fact that the accuracy of depth measurements typically degrades in outdoor lighting and with increasing distance, he says.
In similar work, researchers in North Carolina had volunteers with cameras either mounted on their eyeglasses or strapped onto their knees walk through a variety of indoor and outdoor settings to capture the kind of image data exoskeletons might use to see the world around them. The aim? “To automate motion,” says Edgar Lobaton an electrical engineering researcher at North Carolina State University. He says they are focusing on how AI software might reduce uncertainty due to factors such as motion blur or overexposed images “to ensure safe operation. We want to ensure that we can really rely on the vision and AI portion before integrating it into the hardware.”
In the future, Laschowski and his colleagues will focus on improving the accuracy of their environmental analysis software with low computational and memory storage requirements, which are important for onboard, real-time operations on robotic exoskeletons. Lobaton and his team also seek to account for uncertainty introduced into their visual systems by movements .
Ultimately, the ExoNet researchers want to explore how AI software can transmit commands to exoskeletons so they can perform tasks such as climbing stairs or avoiding obstacles based on a system’s analysis of a user's current movements and the upcoming terrain. With autonomous cars as inspiration, they are seeking to develop autonomous exoskeletons that can handle the walking task without human input, Laschowski says.
However, Laschowski adds, “User safety is of the utmost importance, especially considering that we're working with individuals with mobility impairments,” resulting perhaps from advanced age or physical disabilities.
“The exoskeleton user will always have the ability to override the system should the classification algorithm or controller make a wrong decision.” Continue reading
3D printed houses have been popping up all over the map. Some are hive-shaped, some can float, some are up for sale. Now this practical, cost-cutting technology is being employed for another type of building: a school.
Located on the island of Madagascar, the project is a collaboration between San Francisco-based architecture firm Studio Mortazavi and Thinking Huts, a nonprofit whose mission is to increase global access to education through 3D printing. The school will be built on the campus of a university in Fianarantsoa, a city in the south central area of the island nation.
According to the World Economic Forum, lack of physical infrastructure is one of the biggest barriers to education. Building schools requires not only funds, human capital, and building materials, but also community collaboration and ongoing upkeep and maintenance. For people to feel good about sending their kids to school each day, the buildings should be conveniently located, appealing, comfortable to spend several hours in, and of course safe. All of this is harder to accomplish than you might think, especially in low-income areas.
Because of its comparatively low cost and quick turnaround time, 3D printing has been lauded as a possible solution to housing shortages and a tool to aid in disaster relief. Cost details of the Madagascar school haven’t been released, but if 3D printed houses can go up in a day for under $10,000 or list at a much lower price than their non-3D-printed neighbors, it’s safe to say that 3D printing a school is likely substantially cheaper than building it through traditional construction methods.
The school’s modular design resembles a honeycomb, where as few or as many nodes as needed can be linked together. Each node consists of a room with two bathrooms, a closet, and a front and rear entrance. The Fianarantsoa school with just have one node to start with, but as local technologists will participate in the building process, they’ll learn the 3D printing ins and outs and subsequently be able to add new nodes or build similar schools in other areas.
Artist rendering of the completed school. Image Credit: Studio Mortazavi/Thinking Huts
The printer for the project is coming from Hyperion Robotics, a Finnish company that specializes in 3D printing solutions for reinforced concrete. The building’s walls will be made of layers of a special cement mixture that Thinking Huts says emits less carbon dioxide than traditional concrete. The roof, doors, and windows will be sourced locally, and the whole process can be completed in less than a week, another major advantage over traditional building methods.
“We can build these schools in less than a week, including the foundation and all the electrical and plumbing work that’s involved,” said Amir Mortazavi, lead architect on the project. “Something like this would typically take months, if not even longer.”
The roof of the building will be equipped with solar panels to provide the school with power, and in a true melding of modern technology and traditional design, the pattern of its walls is based on Malagasy textiles.
Thinking Huts considered seven different countries for its first school, and ended up choosing Madagascar for the pilot based on its need for education infrastructure, stable political outlook, opportunity for growth, and renewable energy potential. However, the team is hoping the pilot will be the first of many similar projects across multiple countries. “We can use this as a case study,” Mortazavi said. “Then we can go to other countries around the world and train the local technologists to use the 3D printer and start a nonprofit there to be able to build schools.”
Construction of the school will take place in the latter half of this year, with hopes of getting students into the classroom as soon as the pandemic is no longer a major threat to the local community’s health.
Image Credit: Studio Mortazavi/Thinking Huts Continue reading