Robotics

Ariel Ekblaw, director of the MIT Media Lab Space Exploration Initiative, speaks with Wired reporter Ramin Skibba on a panel discussion on the future of space exploration. “In the future, instead of thinking about space habitats and life in space as a domain where it’s just about survival, which it has certainly been until recently, we’re at this inflection point,” says Ekblaw. “We can begin to think about thriving in space, designing space architecture that is welcoming to more of the public that doesn’t just look like a science lab on orbit and so to be able to do that, we need responsive space habitats, really capable integration of all kinds of different systems, and AI will have a huge role in that.”

Prof. Ritu Raman has developed centimeter-scale robots that use biological muscle, reports Liam Drew for Nature. “Raman is now developing muscle systems connected to neurons that can trigger contraction, just as they exist in animals,” writes Drew. “In the longer term, she aims to use networks of biological neurons that can sense external stimuli as well, enabling them to move in response to environmental cues.”

Researchers from MIT and elsewhere have developed a new AI technique for teaching robots to pack items into a limited space while adhering to a range of constraints, reports Nick Hilden for Scientific American. “We want to have a learning-based method to solve constraints quickly because learning-based [AI] will solve faster, compared to traditional methods,” says graduate student Zhutian “Skye” Yang.

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.”

MIT CSAIL researchers have developed a new air safety system, called Air-Guardian, that is designed to serve as a “proactive co-pilot, enhancing safety during critical moments of flight,” reports Jace Dela Cruz for Tech Times. 

Maria Telleria ’08, SM’10, PhD ’13 speaks with Forbes contributor Stuart Anderson about her experience immigrating to the U.S. as a teenager, earning her PhD at MIT, and co-founding a company. “I don’t think I would have had these opportunities if I could not have come to the United States,” said Telleria. “I think it helped me grow by being exposed to two cultures. When you have had to think in two different ways, I think it makes you better understand other people and why they’re different. Coming to America has been an amazing opportunity.”

Forbes reporter Rob Toews spotlights Prof. Daniela Rus, director of CSAIL, and research affiliate Ramin Hasani and their work with liquid neural networks. “The ‘liquid’ in the name refers to the fact that the model’s weights are probabilistic rather than constant, allowing them to vary fluidly depending on the inputs the model is exposed to,” writes Toews.

Using techniques inspired by kirigami, a Japanese paper-cutting technique, MIT researchers have developed a “a novel method to manufacture plate lattices – high performance materials useful in automotive and aerospace designs,” reports Andrew Paul for Popular Science. “The kirigami-augmented plate lattices withstood three times as much force as standard aluminum corrugation designs,” writes Paul. “Such variations show immense promise for lightweight, shock-absorbing sections needed within cars, planes, and spacecraft." 

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 a soft robot that can be controlled by a weak magnetic field and travel through tiny spaces within the human body, reports Andrew Paul for Popular Science. “Because of their soft materials and relatively simple manipulation, researchers believe such mechanisms could be used in biomedical situations, such as inching through human blood vessels to deliver a drug at a precise location,” explains Paul.

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 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.”