The field of modern robotics is replete with human-engineered machines that emulate the animal kingdom. From robot dogs patrolling stadiums to exploration bots inspired by daddy long-legs, there is no shortage of mechanized animal doppelgangers traversing the globe. Thanks to advancements in AI systems, synthetic materials, and 3D printing, these machines have significantly improved their ability to traverse obstacles through running, climbing, and shimmying. These feats are often undertaken for scientific exploration or public assistance. Despite these technological strides and billions of dollars invested in the robotics industry, mechanized machines still generally lag behind their biological counterparts in a head-to-head race. A new study, published this week in the journal Science Robotics, explores this fundamental observation. The research team examined five distinct “subsystems” associated with running and compared their performance in animals and their robotic counterparts. Animals, with their intricate network of bones and tissues, initially appear inferior to machines on an individual component level. However, the researchers discovered that animals’ true advantage lies in their sophisticated and interconnected control over their bodies. This seamless interoperability makes animals more than the sum of their individual parts. “With only minor exceptions, the engineering subsystems outperform the biological equivalents—and sometimes radically outperformed them,” explained Tom Libby, Senior Research Engineer at SRI International and co-author of the paper. “But what’s also very, very clear is that, when you compare animals to robots at the whole system level, in terms of movement, animals are amazing. And robots have yet to catch up.” Each of the five researchers focused on a specific subsystem associated with running in both animals and machines. These systems were categorized as power, frame, actuation, sensing, and control. In almost all these categories, machines outperformed animals individually. For instance, in the case of frames, robots with lightweight yet robust carbon fiber bodies could support larger mass structures without buckling, unlike animal bones. Similarly, the researchers determined that a robot’s computer-aided control system surpasses an animal’s nervous system in terms of overall latency and bandwidth. However, despite robots seemingly possessing stronger, more durable individual parts, animals demonstrate a superior ability to make them work seamlessly as a cohesive “whole.” This difference becomes apparent when animals and robots are tested in real-world scenarios. While newer robots can undoubtedly accelerate quickly and even execute certain acrobatic feats, they pale in comparison to their biological counterparts in terms of fluidity and adaptability. Robots may struggle to navigate rough terrain, while animals can effortlessly overcome obstacles like mud, snow, vegetation, and rubble without hesitation. “A wildebeest can migrate for thousands of [kilometers] over rough terrain, a mountain goat can climb up a literal cliff, finding footholds that don’t even seem to be there, and cockroaches can lose a leg and not slow down,” remarked Max Donelan, a professor in the Department of Biomedical Physiology and Kinesiology at Simon Fraser University. “We have no robots capable of anything like this endurance, agility and robustness.” Another significant advantage animals possess is time. Unlike advanced robots that have only made significant strides in recent decades, animals have benefited from millions, or in some cases, billions of years of evolution. As the researchers note, animals have a “substantial headstart over engineering.” On the other hand, robots have made remarkable progress in narrowing this gap at an astonishing pace. The researchers express optimism that robots will eventually surpass animals in running capabilities. “It [advances in robots] will move faster, because evolution is undirected,” said University of Washington Department of Electrical & Computer Engineering Associate Professor Sam Burden. “There are ways that we can move much more quickly when we engineer robots than we can through evolution—but evolution has a massive head start.” The researchers believe that these findings can inform the future development of running robots. Equipped with this knowledge, robot makers may prioritize component integration over the sole pursuit of more powerful and robust hardware. “The lesson we take from biology is that, although further improvements to components and subsystems are beneficial, the greatest opportunity to improve running robots is to make better use of existing parts,” the researchers concluded.