Abstract
Soft materials have opened new possibilities in robotics: the use of inherently adaptable mechanical structures allows soft robots to negotiate with uncertain and unstructured tasks. Nevertheless, their sizable elastic deformations pose a limitation to their modelling and control. Moreover, the maximum achievable stiffness is typically too low to provide performances comparable to those of their rigid-linked counterparts.The research presented in this thesis aims at overcoming these limitations and bridging the gap between traditional and soft robotics by proposing a novel design paradigm for a Variable Stiffness System (VSS) based on soft materials with the potential to be employed in a wide range of application areas. The proposed design takes inspiration from the antagonistic stiffening mechanism of muscles in nature, in which the balancing of two opposing contractile muscle forces allows to achieve infinite stable configurations.
A combination of flexible inflatable membranes and flexible, yet inextensible fabric sleeves is used to enable fine stiffness tuning, by mean of pneumatic actuation. The conjoint use of tendon-driven actuation is proposed to enable not only stiffness controllability, but also shape-shifting and shape-locking capabilities. The use of fabric allows for significantly higher pressures to be used, thus, larger forces can be exerted on the environment, still making use of soft materials.
This has led to contributions within the areas of industrial collaborative robots, where the concept of stiffness-controllable robotic link has been explored to enhance safety in Human-Robot Interaction (HRI); in surgical robotics where the use of the proposed antagonistic actuation mechanism has been investigated to improve the dexterity of laparoscopic tools; and in rehabilitation robotics, where the same mechanism is employed to improve the ergonomics of state-of-the-art exoskeletons for hand-rehabilitation. This thesis shows how this novel design concept can be applied to effectively improve or replace a wide range of state-of-the-art robotic systems.
| Date of Award | 2019 |
|---|---|
| Original language | English |
| Awarding Institution |
|
| Supervisor | Elizabeth Sklar (Supervisor) & Kaspar Althoefer (Supervisor) |