A learnt approach for the design of magnetically actuated shape forming soft tentacle robots

Soft continuum robots have the potential to revolutionize minimally invasive surgery. The challenges for such robots are ubiquitous; functioning within sensitive, unstructured and convoluted environments which are inconsistent between patients. As such, there exists an open design problem for robots of this genre. Research currently exists relating to the design considerations of on-board actuated soft robots such as fluid and tendon driven manipulators. Magnetically reactive robots, however, exhibit off-board actuation and consequently demonstrate far greater potential for miniaturization and dexterity. In this letter we present a soft, magnetically actuated, slender, shape forming ‘tentacle-like’ robot. To overcome the associated design challenges we also propose a novel design methodology based on a Neural Network trained using Finite Element Simulations. We demonstrate how our design approach generates static, two-dimensional tentacle profiles under homogeneous actuation based on predefined, desired deformations. To demonstrate our learnt approach, we fabricate and actuate candidate tentacles of 2 mm diameter and 42 mm length producing shape profiles within 8% mean absolute percentage error of desired shapes. With this proof of concept, we make the first step towards showing how tentacles with bespoke magnetic profiles may be designed and manufactured to suit specific anatomical constraints.