A novel machine learning framework makes it faster and easier to train robots that can perform tasks with unprecedented precision.
A fresh design approach to high-performing variable-stiffness rotating joints could enable humans to work safely alongside robots in industrial manufacturing environments.
A deep learning technique developed by A*STAR researchers uses WiFi data to help robots find their way around.
By breaking complex actions into their basic components, researchers have developed a versatile framework that enables robots to learn from human demonstrators.
Horizontal Technology Programme Offices will bring A*STAR’s deep capabilities to bear on real-world issues facing Singapore and the wider world, says Deputy Chief Executive (Research), Andy Hor.
Researchers at A*STAR have designed a hybrid machine learning model to enhance touch capabilities in robots.
An algorithm gives robots an instinctive understanding of how to use tools
A new class of collaborative robots may be the future of industrial remanufacturing
Polymeric materials that stretch out when electrically stimulated can benefit from realistic numerical simulations
Joint laboratories created by A*STAR and the National University of Singapore are set to advance Singapore’s manufacturing industry through robotics and automation