In the quest to build robots that can walk, run, and navigate terrain as adeptly as animals, robotics engineers face an endless pursuit of emulating systems that were millions of years in the evolutionary making. A new study by an interdisciplinary team of scientists dissects why replicating the incredible mobility of the natural world remains an monumental challenge for even the most advanced robotic designs.

The research, published in Science Robotics, finds that while fabricated robotic components often outperform their biological counterparts based on typical engineering metrics, it is the exquisite integration and control of those components that allows animals to run circles around our best robots. At least for now.

"A wildebeest can migrate thousands of kilometers over rough terrain, a mountain goat can climb a sheer cliff face, and a cockroach can lose a leg yet keep scurrying - we have no robots capable of that endurance, agility and robustness," says Dr. Max Donelan of Simon Fraser University, a co-author on the study.

Donelan's team examined five key subsystems that enable legged robotic mobility - power, framing, actuation, sensing, and control systems. Their analysis reveals that in most areas, state-of-the-art engineering solutions demonstrated clear advantages over the biological equivalents found in animals.

For instance, modern electric motors can operate much more efficiently than muscle fibers, storing virtually unlimited energy density compared to the limited fuel tanks of biological bodies. Robotic actuators and sensors also outperformed natural counterparts like tendons and nervous systems in areas like speed, bandwidth, and precision.

"With only minor exceptions, the engineering subsystems outperform the biological equivalents – sometimes radically so," says Tom Libby of SRI International. "Yet at the full system level of mobility, animals are amazing capabilities that robots have yet to catch up to."

The Great Integrators 

What separates robots from rabbits, then, is biology's mastery of coherently integrating and coordinating disparate components into seamless mechanical control systems evolved over eons. This design prowess enables animals to perceive environments, deftly make real-time adjustments, and dynamically optimize their gaits for maximum speed, efficiency and robustness.

Robots, by contrast, are only recently emerging from relatively simplistic motion control systems. As the authors note, a robotic leg using today's most advanced sensors and actuators is still prone to buckling when navigating slightly uneven terrain that a mountain goat could deftly bound across.

"If you compare the relatively short time that robotics has had to develop mobility technology compared to the evolutionary timeframes for animal development, the robotic progress has actually been remarkably quick," says Dr. Sam Burden of the University of Washington. "Biology just had a massive head start that we are still playing catch-up to."

Robotics has immense potential to deliver machines that can go where wheeled vehicles cannot, handling complex search and delivery tasks in human-centric environments. But getting there requires fundamental advances in motion planning, dynamic transitions between gaits, environmental perception and other integration challenges robots have struggled with.

Building Better Robots Through Biology 

According to the researchers, roboticists may need to pivot from trying to reverse-engineer individual biological components to studying how evolution produced such masterfully integrated coordination and control systems. Could robotic "evolution" through techniques like machine learning hold the key?

As robotic mobility continues advancing through biological inspiration, some have speculated that robots could one day outperform even the most agile animals by exceeding biological limitations. For now, those dreams remain fables - while others worry advanced robots could eventually "rob" human workers of physically demanding jobs requiring dexterity.

For society to realize robotics' transformative potential while mitigating workforce risks, innovators may need to incorporate not just biology's mechanics, but also its foundations of diversity, resilience and sustainable coexistence into the technology roadmaps.

Billion-year evolutionary headstarts require long-view thinking. Meeting that challenge could produce robots capable of amazing feats - but preserving humanity's role in that future is the imperative.