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Researchers from MIT CSAIL came up with PIGINet, a novel machine learning-based system that improves household robots' efficiency by using multimodal input sequences to anticipate and select feasible task plans, reducing planning time and enabling adaptability in diverse environments.
An MIT-led team introduces a new computational method that facilitates the dense placement of objects inside a rigid container.
A new framework known as MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single cohesive system. The work was developed by researchers from MIT and Google.
FlexBoard is a flexible breadboard that enables rapid prototyping of objects with interactive sensors, actuators, and displays on curved and deformable surfaces, such as a ball or clothes.
SoftZoo is an open-source platform developed at MIT CSAIL that simulates wildlife for soft robotics co-design more systematically and computationally, thus better advancing the development of relevant algorithms.