Intel commits to funding QUT Center robotics project


Intel’s Neuromorphic Computing Lab has QUT Center for Robotics researchers Dr. Tobias Fischer, Professor Michael Milford and PhD student Somayeh Hussaini to develop a project that will use Intel’s Loihi 2 neuromorphic research chip.

Based on the principles of biological neural computation, neuromorphic computing uses new algorithmic approaches that mimic how the human brain interacts with the world to deliver capabilities closer to human cognition intel.

The chip uses Spiking Neural Networks (SNNs), which are novel computer models very similar to the neurons in our brains that simulate natural learning by dynamically remapping neural networks to make decisions in response to learned patterns over time the time to meet.

“Simultaneous Localization and Mapping (SLAM) algorithms are at the heart of autonomous mobile vehicles operating in unknown, GPS-poor, or dynamic environments.” dr fisherman said.

“Our project will focus on visual location detection, a particularly challenging part of SLAM that requires robust detection and discrimination of hundreds of thousands of locations under different conditions,” added Fisher.

“This includes both ‘slow’ adaptation (urban vs. rural or day vs. night) and ‘quick’ adaptation (sudden rain, tunnel entry). Continuous fitting is very challenging because it’s impossible to cover all environmental variations in the training data,” he said.

Joint Director of the QUT Center for Robotics Michael Milford To solve this challenge, the QUT research team from the School of Electrical Engineering & Robotics took inspiration from the animal kingdom.

“Many animals demonstrate remarkable navigational abilities and solve large-scale memory formation and recognition problems with unprecedented efficiency, flexibility, and robustness,” commented Milford.

“New features of Intel’s Loihi 2 enable more complex neural models and are well positioned to implement the next generation of biologically inspired navigation and mapping algorithms that could surpass the current state of the art in this field.”

The QUT research project team worked with Intel Labs researchers Dr. Yulia Sandamirskaya and Dr. Garrick Orchard and software and algorithm manager Andreas Wild to develop algorithms.

“Neuromorphic computing opens up exciting new possibilities in computing, especially when it comes to robotics,” said Intel Neuromorphic Computing Lab Director Mike Davis.

“Loihi 2 greatly improves the speed, programmability, and capacity of neuromorphic computing, allowing it to support more difficult optimization problems.”


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