Brain-inspired navigation: The answer from the brain

What is it about?

Imagine if robots and self-driving cars could navigate like animals do—using their own “internal GPS” instead of relying on satellites. This is the idea behind Brain-Inspired Navigation (BIN). Our research explores how to make machines smarter by copying the way animals’ brains process spatial information and navigate complex environments. In this comprehensive review, we look at how the brain's navigation circuitry works, the computational models that simulate brain navigational intelligence, and the latest advancements in creating BIN systems. We also discuss the hardware that makes these systems more efficient and how they can be used in real-world applications like underwater exploration, space travel, or emergency response. By learning from the brain, we hope to develop more robust, energy-efficient, and adaptive navigation systems for the future.

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Photo by Theo Laflamme on Unsplash

Photo by Theo Laflamme on Unsplash

Why is it important?

Our research provides a comprehensive review of Brain-Inspired Navigation (BIN), spanning from the neural basis of brain navigational intelligence to the latest computational models and hardware implementations. This work is unique in its interdisciplinary perspective, integrating insights from neuroscience, artificial intelligence, and engineering to develop intelligent navigation systems. As demand for autonomous systems grows and neuromorphic hardware advances, our study highlights BIN's potential for navigating complex environments without GPS, such as underwater, underground, or in space. By offering a clear roadmap for future innovations, our work aims to drive progress and inspire novel developments in future navigation.

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