Animals can finely modulate their leg stiffness to interact with complex terrains and absorb sudden shocks. In feats like leaping and sprinting, animals demonstrate a sophisticated interplay of opposing muscle pairs that actively modulate joint stiffness, while tendons and ligaments act as biological springs storing and releasing energy. Although legged robots have achieved notable progress in robust locomotion, they still lack the refined adaptability inherent in animal motor control. Integrating mechanisms that allow active control of leg stiffness presents a pathway towards more resilient robotic systems. This paper proposes a novel mechanical design to integrate compliancy into robot legs based on tensegrity - a structural principle that combines flexible cables and rigid elements to balance tension and compression. Tensegrity structures naturally allow for passive compliance, making them well-suited for absorbing impacts and adapting to diverse terrains. Our design features a robot leg with tensegrity joints and a mechanism to control the joint's rotational stiffness by modulating the tension of the cable actuation system. We demonstrate that the robot leg can reduce the impact forces of sudden shocks by at least 34.7 % and achieve a similar leg flexion under a load difference of 10.26 N by adjusting its stiffness configuration. The results indicate that tensegrity-based leg designs harbors potential towards more resilient and adaptable legged robots.

Researchers are always looking for new ways to improve the agility, performance, and efficiency of walking robots. Most of the time, this focus has centered on motor advancements. But a team at ETH Zurich and the Max Planck Institute for Intelligent Systems (MPI-IS) is focused on an alternative approach--artificial, electrostatically-powered musculature inspired by animal biology and human anatomy. Both two- and four-legged robots have become pretty agile over the past few years thanks to design advancements in motor technologies and artificial intelligence. For many of them, however, energy requirements and costs remain a major hurdle, especially when it comes to AI systems needed to interpret vast quantities of environmental sensor data.

The robot's soft legs are filled with sensors that measure brain activity A soft robot inserted through a tiny hole in the skull can deploy six sensor-filled legs on the surface of the brain. A version of this soft robot has been successfully tested in a miniature pig and could be scaled up for human testing in the future. The concept offers a less invasive approach for placing electrodes on the brain's surface compared with the traditional method, in which surgeons cut a hole in the skull the size of the fully extended device. If it proves safe and effective in humans, it could eventually help monitor and even treat people who experience epileptic seizures or other neurological disorders. "There's actually a really large surface area that you can reach without doing a large craniotomy," says Stéphanie Lacour at the Swiss Federal Institute of Technology in Lausanne.

Animals run robustly in diverse terrain. This locomotion robustness is puzzling because axon conduction velocity is limited to a few ten meters per second. If reflex loops deliver sensory information with significant delays, one would expect a destabilizing effect on sensorimotor control. Hence, an alternative explanation describes a hierarchical structure of low-level adaptive mechanics and high-level sensorimotor control to help mitigate the effects of transmission delays. Motivated by the concept of an adaptive mechanism triggering an immediate response, we developed a tunable physical damper system. Our mechanism combines a tendon with adjustable slackness connected to a physical damper. The slack damper allows adjustment of damping force, onset timing, effective stroke, and energy dissipation. We characterize the slack damper mechanism mounted to a legged robot controlled in open-loop mode. The robot hops vertically and planar over varying terrains and perturbations. During forward hopping, slack-based damping improves faster perturbation recovery (up to 170%) at higher energetic cost (27%). The tunable slack mechanism auto-engages the damper during perturbations, leading to a perturbation-trigger damping, improving robustness at minimum energetic cost. With the results from the slack damper mechanism, we propose a new functional interpretation of animals' redundant muscle tendons as tunable dampers.