仿生視覺系統

Bio-inspired vision systems use biological principles to create more efficient sensing hardware, and Northwestern University's SpiderCam demonstrates how nature can improve machine vision. Inspired by the multiple retinal layers of jumping spiders, the camera estimates depth by comparing differences in image blur rather than relying on power-intensive sensors or projected light. The result is a passive 3D imaging system that generates real-time depth maps while consuming less than one watt of power, making it suitable for wearables, drones, robots, and augmented reality devices where battery life is critical. This approach highlights how biological models can solve engineering challenges through simpler, lower-energy designs.

For businesses, bio-inspired sensing technologies could reduce hardware costs, extend device operating time, and unlock new applications in portable electronics, industrial automation, logistics, healthcare, and robotics, where efficient depth perception enables smarter, always-on systems without significantly increasing energy demands.