An international team has explored how in future aerial robots could process construction materials precisely in the air -- an approach with great potential for difficult-to-access locations or work at great heights. The flying robots are not intended to replace existing systems on the ground, but rather to complement them in a targeted manner for repairs or in disaster areas, for instance.
New research can transform how hospitals triage, risk-stratify, and counsel patients to save lives.
Helping music professionals explore the potential of generative AI
Helping music professionals explore the potential of generative AI
Helping music professionals explore the potential of generative AI
Helping music professionals explore the potential of generative AI
Helping music professionals explore the potential of generative AI
Helping music professionals explore the potential of generative AI
Helping music professionals explore the potential of generative AI
For a robot, the real world is a lot to take in. Making sense of every data point in a scene can take a huge amount of computational effort and time. Using that information to then decide how to best help a human is an even thornier exercise.
The core innovation of our new patent lies in its self-supervised approach to depth estimation. What that means is, the AI learns to judge the depth of an item it needs to pick up by using its own sensor data and the feedback it gets from its actions.
New research led by Imperial College London and co-authored by the University of Bristol, has revealed that aerial robotics could provide wide-ranging benefits to the safety, sustainability and scale of construction.
Inspired by the movements of a tiny parasitic worm, engineers have created a 5-inch soft robot that can jump as high as a basketball hoop. Their device, a silicone rod with a carbon-fiber spine, can leap 10 feet high even though it doesn't have legs. The researchers made it after watching high-speed video of nematodes pinching themselves into odd shapes to fling themselves forward and backward.
Inspired by the movements of a tiny parasitic worm, Georgia Tech engineers have created a 5-inch soft robot that can jump as high as a basketball hoop.
After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists combine elements of different methods to improve algorithms or create new ones.