Precision home robots learn with real-to-sim-to-real
CSAIL researchers introduce a novel approach allowing robots to be trained in simulations of scanned home environments, paving the way for customized household automation accessible to anyone.
CSAIL researchers introduce a novel approach allowing robots to be trained in simulations of scanned home environments, paving the way for customized household automation accessible to anyone.
Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
Read MoreBoston Dynamics, a leader in robotics, has revolutionized automation with its advanced machines like Atlas, Spot, and Stretch. The company’s success in diverse sectors like construction, oil and gas, and public safety signals a bright future for robotics. With the market projected to reach $74.1 billion by 2026, the integration of AI and machine learning will further drive innovation and adoption across industries.
Read MoreThe method uses language-based inputs instead of costly visual data to direct a robot through a multistep navigation task.
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