Exploiting reprogrammable nonlinear structural springs for enhancing the manoeuvrability of a vibro-impact capsule robot

Vibro-impact capsule robots, propelled by rhythmic collisions of an internal mass triggered by an external magnetic field, are emerging as promising tools for minimally invasive surgery. This innovative actuation mechanism allows for delicate interaction with tissues, making them ideal candidates for navigating confined surgical spaces. However, their limited manoeuvrability and controllability remain significant hurdles, restricting their ability to navigate complex anatomies and perform precise interventions, ultimately hindering their broader clinical applications. This paper investigates the integration of reprogrammable structural springs in capsule robots, demonstrating how dynamic tuning can tailor the interaction between the inner mass and the capsule, thereby unlocking enhanced manoeuvrability and precise control of the capsule robot. A mathematical model describing the dynamic response of a vibro-impact capsule robot integrated with von Mises trusses (VMT), which are used to tailor the interaction between the inner mass and the capsule, is developed and verified using finite element modelling. Using the verified mathematical model, we explore how the transition between mono-stability and bi-stability of VMTs affects the capsule robot’s propelling performance. Our findings demonstrate that this state switch enables four distinct propulsion modes of the capsule robot. This work paves the way for a new paradigm in small-scale robot design by incorporating reprogrammable nonlinear structures. These structures empower the robots with unprecedented manoeuvrability and controllability within a compact, deployable form factor. • Developed an analytical model for von Mises truss (VMT) to explore design space. • Integrated VMT into a capsule robot and verified using finite element simulations. • Exploited mono-stability and bi-stability of VMTs for enhanced manoeuvrability. • Achieved four distinct locomotion modes through reprogrammable VMTs.