A Compliant Robotic Leg Based on Fibre Jamming

Humans possess a remarkable ability to react to sudden and unpredictable perturbations through immediate mechanical responses, which harness the visco-elastic properties of muscles to perform auto-corrective movements to maintain balance. In this paper, we propose a novel design of a robotic leg inspired by this mechanism. We develop multi-material fibre jammed tendons, and demonstrate their use as passive compliant mechanisms to achieve variable joint stiffness and improve stability. Through numerical simulations and extensive experimentation, we demonstrate the ability for our system to achieve a wide range of potentially beneficial compliance regimes. We show the role and contribution of each tendon quantitatively by evaluating their individual force contribution in resisting rotational perturbations. We also perform walking experiments with programmed bioinspired gaits that varying the stiffness of the tendons throughout the gait cycle, demonstrating a stable and consistent behaviour. We show the potential of such systems when integrated into legged robots, where compliance and shock absorption can be provided entirely through the morphological properties of the leg.

Automated design of pneumatic soft grippers through design-dependent multi-material topology optimization

In recent years, soft robotic grasping has rapidly spread through the academic robotics community and pushed into industrial applications. At the same time, multimaterial 3D printing has become widely available, enabling monolithic manufacture of devices containing rigid and elastic section. We propose a novel design technique which leverages both of these technologies and is able to automatically design bespoke soft robotic grippers for fruit-picking and similar applications. We demonstrate the novel topology optimisation formulation which generates multi-material soft gippers and is able to solve both the internal and external pressure boundaries, and investigate methods to produce air-tight designs. Compared to existing methods, it vastly expands the searchable design space whilst increasing simulation accuracy.