Bio-inspired robotic eyes better estimate motion

Event cameras mimic the human eye to allow robots to navigate their environment. Science of Intelligence PI Guillermo Gallego, together with Shintaro Shiba and Yoshimitsu Aoki from Keio University in Japan, recently found a new approach to help minimize the related computational costs. 


The new method used event camera data, just like the previous method, but also uses something called “prior knowledge”, a sort of robotic common sense that automatically removes data that is deemed “unrealistic”, thereby lightening the process and reducing computational effort. This discovery is important for future research and may find applications in areas such as driverless cars and autonomous drones.

Learn more about the approach and its possible future applications in this Advanced Science News article.


Reference: Shintaro Shiba, Yoshimitsu Aoki, and Guillermo Gallego, A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework, Advanced Intelligent Systems (2022). DOI: 10.1002/aisy.202200251


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