Prof. Russ Tedrake and Max Bajracharya '21 MEng '21 speak with TechCrunch reporter Brian Heater about the impact of generative AI on the future of robotics. “Generative AI has the potential to bring revolutionary new capabilities to robotics,” says Tedrake. “Not only are we able to communicate with robots in natural language, but connecting to internet-scale language and image data is giving robots a much more robust understanding and reasoning about the world.”
Researchers from MIT and elsewhere have developed a new 3D printing process that “allows users to create more elastic materials along with rigid ones using slow-curing polymers,” reports Tony Ho Tran for the Daily Beast. The researchers used the system to create a, “3D printed hand complete with bones, ligaments, and tendons. The new process also utilizes a laser sensor array developed by researchers at MIT that allows the printer to actually ‘see’ what it’s creating as it creates it.”
Prof. Arnaud Costinot and Prof. Iván Werning speak with TechCrunch reporter Brian Heater about their research examining the potential impact of a robot tax on automation and jobs. “The potential wages people can earn may become more unequal with new technologies and the idea is that the tax can mitigate these effects,” Costinot and Werning explain. “In a sense, one can think of this as pre-distribution, affecting earnings before taxes, instead of redistribution.”
Prof. Daniela Rus, director of CSAIL, speaks with TechCrunch reporter Brain Heater about liquid neural networks and how this emerging technology could impact robotics. “The reason we started thinking about liquid networks has to do with some of the limitations of today’s AI systems,” says Rus, “which prevent them from being very effective for safety, critical systems and robotics. Most of the robotics applications are safety critical.”
Researchers at MIT have developed PIGINet (Plans, Images, Goal and Initial facts), a neural network designed to bring task and motion planning to home robotics, reports Brian Heater for Tech Crunch. “The system is largely focused on kitchen-based activities at present. It draws on simulated home environments to build plans that require interactions with various different elements of the environment, like counters, cabinets, the fridge, sinks, etc,” says Heater.
Researchers at MIT have developed a new artificial intelligence system aimed at helping autopilot avoid obstacles while maintaining a desirable flight path, reports Kyle Wiggers for TechCrunch. “Any old algorithm can propose wild changes to direction in order to not crash, but doing so while maintaining stability and not pulping anything inside is harder,” writes Wiggers.
MIT scientists have found that the “motions of undulating animals and the states of quantum objects can be described using strikingly similar equations,” writes Karmela Padavic-Callaghan for New Scientist. The similarity “allowed the team to use mathematical tools previously developed by quantum physicists to analyze the animals,” notes Padavic-Callaghan. “For instance, the team quantified how differently a snake-like robot and a C. elegans move and created a diagram that placed them on a spectrum of other undulating creatures.”
MIT researchers have developed a new robotic gripper that is able to grasp objects using reflexes, reports Mashable. “The Robo-Gripper has proximity and contact sensors which allows it to react to surfaces near objects to better grab them. The technology may allow these machines to be used in homes or other unique, unstructured environments.”
MIT researchers have developed SoftZoo, “an open framework platform that simulated a variety of 3D model animals performing specific tasks in multiple environmental settings,” reports Andrew Paul for Popular Science. “This computational approach to co-designing the soft robot bodies and their brains (that is, their controllers) opens the door to rapidly creating customized machines that are designed for a specific task,” says CSAIL director, Prof. Daniela Rus.
Researchers at MIT have developed “SoftZoo,” a platform designed to “study the physics, look and locomotion and other aspects of different soft robot models,” reports Brian Heater for TechCrunch. “Dragonflies can perform very agile maneuvers that other flying creatures cannot complete because they have special structures on their wings that change their center of mass when they fly,” says graduate student Tsun-Hsuan Wang. “Our platform optimizes locomotion the same way a dragonfly is naturally more adept at working through its surroundings.”
TechCrunch reporter Brian Heater spotlights how MIT researchers have developed a new approach to robotic gripping that incorporates reflexes to help grasp and sort objects. “The new system is built around an arm with two multi-joint fingers,” writes Heater. “There’s a camera on the base and sensors on the tips that record feedback. The system uses that data to adjust accordingly.”
Researchers at MIT have created a four-legged robot called DribbleBot, reports Caroline Goggin for WHDH. The robot “can dribble a soccer ball under the same conditions as humans, using onboard sensors to travel across different types of terrain.”
Popular Science reporter Andrew Paul spotlights how researchers from MIT CSAIL have developed a soccer-playing robot, dubbed DribbleBot, that can handle a variety of real-world terrains. “DribbleBot showcases extremely impressive strides in articulation and real-time environmental analysis. Using a combination of onboarding computing and sensing, the team’s four-legged athlete can reportedly handle gravel, grass, sand, snow, and pavement, as well as pick itself up if it falls.”
MIT researchers have created “Dribblebot,” a four-legged robot capable of playing soccer across varying terrain, reports Brian Heater for TechCrunch.
Researchers at MIT have created a four-legged robot capable of dribbling a soccer ball and running across a variety of terrains, reports Ross Cristantiello for Boston.com. “Researchers hope that they will be able to teach the robot how to lift a ball over a step in the future,” writes Cristantiello. “They will also explore how the technology behind DribbleBot can be applied to other robots, allowing machines to quickly transport a range of objects around outside using legs and arms.”