Although many roboticists today turn to nature to inspire their designs, even bioinspired robots are usually fabricated from non-biological materials like metal, plastic and composites. But a new experimental robotic manipulator from the Computational Robot Design and Fabrication Lab ( CREATE Lab) in EPFL's School of Engineering turns this trend on its head: its main feature is a pair of langoustine abdomen exoskeletons. Although it may look unusual, CREATE Lab head Josie Hughes explains that combining biological elements with synthetic components holds significant potential not only to enhance robotics, but also to support sustainable technology systems. "Exoskeletons combine mineralized shells with joint membranes, providing a balance of rigidity and flexibility that allows their segments to move independently. These features enable crustaceans' rapid, high-torque movements in water, but they can also be very useful for robotics. And by repurposing food waste, we propose a sustainable cyclic design process in which materials can be recycled and adapted for new tasks."

Unless you've been living under a rock, you would've noticed that artificial neural networks are now used everywhere. They're impacting our everyday lives, from performing predictive tasks such as recommendations, facial recognition and object classification, to generative tasks such as machine translation and image, sound, video generation. But with all of these advances, the impressive feats in deep learning required a substantial amount of sophisticated engineering effort. Even if we look at the early AlexNet from 2012, which made deep learning famous when it won the ImageNet competition back then, we can see the careful engineering decisions that were involved in its design. Modern networks are often even more sophisticated, and require a pipeline that spans network architecture and careful training schemes.