Soft robots have shown great promise across a wide range of clinical procedures, such as colonoscopy and catheterization [1]. In contrast with traditional rigid robots, soft robots exhibit compliance and thus have the potential to reduce harm that could inadvertently be caused by the robot during surgery. Moreover, soft robots are able to reach confined spaces due to their ability to twist and bend with high curvature [2]. Despite their advantages, the deformation of a soft robot, which is leveraged to generate motion, significantly affects its mechanical characteristics. This is particularly the case for the stiffness of a soft robot, which varies across its workspace [3][4]. This variation introduces profound control challenges and limits performance [3]. To ad- dress this challenge, researchers have steered towards the development of variable stiffness mechanisms which are typically embedded in the structure of the soft robot. Despite the success of these methods, they are often difficult to fabricate and integrate into existing systems. As an alternative to embedding stiffening mechanisms, stiffness variation can be achieved by adjusting the geometry or topology of the robotic device. This has been successfully demonstrated for rigid robots across a number of research works, for instance by Simaan et al. [5] for a double planar parallel robot where the robot’s stiffness is tuned by adjusting the legs’ location across a fixed platform. To-date, such approaches have only been applied in rigid robotic systems [6].
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Alabdullah et al. (2024) studied this question.
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