ANYmal in Nature's top 10 papers
Our Science Robotics paper on the ANYmal robot is featured in a list of "10 remarkable papers" published in 2019, compiled by Nature
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Robots on the run — by Hod Lipson
Young animals gallop across fields, climb trees and immediately find their feet with enviable grace after they fall. And like our primate cousins, humans can deploy opposable thumbs and fine motor skills to complete tasks such as effortlessly peeling a clementine or feeling for the correct key in a dark hallway. Although walking and grasping are easy for many living things, robots have been notoriously poor at gaited locomotion and manual dexterity. Even a robot that performs beautifully in simulation will stumble and fall after a few encounters with seemingly minor physical obstacles. Writing in Science Robotics, Hwangbo et al. report that a data-driven approach to designing robotic software can improve the locomotion skills of robots. They demonstrate their method using the ANYmal robot — a medium-dog-sized quadrupedal system. Original research: external pageSci. Robot. 4, eaau9354 (2019)call_made.