In an article for Financial Times, CSAIL Director Daniela Rus explains why humans should collaborate rather than compete with AI. “Technology and people do not have to be in competition,” writes Rus. “Collaborating with AI systems, we can augment and amplify many aspects of work and life.”
A robotic carpenter developed by CSAIL is pre-cutting wood for flat-pack furniture, making assembly safer and more efficient. Called AutoSaw, the idea “was not to replace human carpenters but to allow them to focus on more important tasks such as design,” writes Dave Lee for the BBC.
David Grossman of Popular Mechanics writes about AutoSaw, a system developed by CSAIL researchers that assists in custom build carpentry projects. The system is designed “to split the difference between machine-built quality and unique customization” and requires human assembly after the pieces are cut, explains Grossman.
Autosaw, the robotic carpenter developed by researchers from CSAIL, can cut pieces for furniture building, as long as you provide the raw materials. “It’ll cut pieces to shape, drill the necessary holes and even move them around the workshop for you,” writes Thomas Tamblyn for Huff Post.
A video from Financial Times highlights work being done by CSAIL to develop robot teams. Prof. Daniela Rus discusses how partnering robots has the potential to “form much more adaptive and complex systems that will be able to take on a wider set of tasks."
AutoSaw, developed in CSAIL, is “a new system of robot-assisted carpentry that could make the creation of custom furniture and fittings safer, easier, and cheaper,” writes James Vincent of The Verge. As postdoc Jeffrey Lipton explains, AutoSaw “shows how advanced robotics could fit into the workflow of a carpenter or joiner.”
CSAIL postdoc Jeffrey Lipton, along with Prof. Daniela Rus and PhD candidate Adriana Schulz, has developed AutoSaw, a software-driven carpentry system that readies wood pieces for hand assembly, writes Mark Wilson of Co.Design. “We’re moving toward a new manufacturing revolution with 3D printers and robots to make objects with unprecedented complexity,” says Schulz.
StandX, a robotic chair developed by MIT research scientist Simon Hong, helps users avoid back pain by nudging its occupant to shift positions, writes Scott Kirsner for The Boston Globe. Hong, who invented the chair to deal with his own back pain, says his is proactive because with others “you can change position, but you do it only when you feel pain."
Developed by researchers at MIT and Cornell, the new Robotic Modeling Assistant (RoMA) uses an augmented reality headset that allows designers to more efficiently create 3D prototypes with CAD software. “A robotic arm then goes to work constructing a skeletal model using a simple plastic depositing 3D printer mounted on its hand,” explains Brian Heater for TechCrunch.
On WGBH’s Under The Radar, Amy Traverso, food editor at Yankee Magazine, speaks with host Callie Crossley about Spyce, the robotic kitchen developed by MIT students that will soon become an actual restaurant in Boston. “It’s going to be a fast-casual chain in Downtown Crossing and the consulting chef is Daniel Boulud,” explains Traverso.
Researchers in CSAIL are developing a steering program for drones that allows them to process uncertainty and avoid hitting objects while flying autonomously. Called Nanomap, the drone uses depth measurements to determine the safest path. “This technique creates an on the fly map that lets the drone handle uncertainty as opposed to being ready in every situation,” writes John Biggs for TechCrunch.
Brian Heater for TechCrunch covers how researchers are creating a system that will allow robots to develop motor skills and process abstract concepts. “With this system, the robots can perform complex tasks without getting bogged down in the minutia required to complete them,” Heater writes.
CSAIL researchers have developed a new navigation method that allows drones to process less data, have faster reaction times, and dodge obstacles without creating a map of the environment they’re in, writes James Vincent of The Verge. “Because we’re not taking hundreds of measurements and fusing them together, it’s really fast,” said graduate student Peter Florence.
A drone navigation system developed by CSAIL researchers doesn’t rely on intricate maps that show the location of obstacles, but adjusts for uncertainties, reports Martin Finucane of The Boston Globe. The system could be used in “in fields from search-and-rescue and defense to package delivery,” notes Finucane.
CSAIL researchers have developed a mapping system for autonomous drones, writes Andrew Tarantola of Endgadet. Using depth-sensing technology to measure their immediate surroundings, the drone can “understand generally where it is in relation to obstacles and anticipate how it will need to change course to avoid them,” Tarantola explains.