This is because modern robotic vision, including visual place recognition, typically relies on power-hungry machine learning models, similar to the ones used in AI like ChatGPT. By comparison, our ...

Neuromorphic computing integrates analog memory elements directly into processing units – similar to a human brain – eliminating the need for data transfer.

In our new study, we turned to the human brain to help us create ... but used much less energy. For robots that need to navigate, developing more compact, energy-efficient AI using neuromorphic ...

QUT Centre for Robotics researchers have developed a new robot navigation system.  Locational Encoding with Neuromorphic Systems (LENS) is set to transform how autonomous robots operate. At its ...

The system contains a sensor, chip and tiny AI model inspired by biological eyes and brains and uses a tenth of the energy of a camera-based system.

Inspired by nature, scientists created a self-powered device that recognizes color just like our eyes, paving the way for advanced machine vision.

It demonstrates that future robots can be smarter and more efficient by using movement to gather information, rather than relying on massive computing power ... such as differentiating between human ...

It demonstrates that future robots can be smarter and more efficient by using movement to gather information, rather than relying on massive computing power ... such as differentiating between human ...

Discover how neuromorphic computing mimics the brain to deliver ultra-efficient, adaptive AI for edge devices, robotics, ...

Brain-inspired chips can slash AI energy use by as much as 100-fold, but the road to mainstream deployment is far from ...

Here is how to explore real-time controllers and create better robots. Robotics is a resource-intensive field, especially ...