An augmented reality-enabled digital twin system for reconfigurable soft robots: Visualization, simulation and interaction

Abstract

In the rapidly evolving field of soft robotics, the development of new materials, structural designs, and conceptual frameworks has led to the rise of soft robot technology, which is now moving towards a highly versatile modular architecture with potential uses across various industries. However, one of the main hurdles faced in this domain is the shape-morphing challenge, as existing visualization and simulation tools struggle to adequately represent the complex and continued deformation behaviors of soft robots. Furthermore, there is a distinct lack of intuitive, user-friendly platforms for visualizing and interactively controlling the shape-shifting capabilities of these robots. In response to these challenges, this paper introduces an innovative digital twin (DT) system for reconfigurable soft robots set within an augmented reality (AR) environment. This system facilitates a more natural and accurate depiction of 3D soft deformations and provides an intuitive interface for simulation. We utilize a parameterized curve-driven method to dynamically adapt the DT in the AR space, ensuring smooth transitions between various 3D shape-morphing states. We identify three fundamental shape-morphing patterns – stretching, bending, and twisting – and create advanced visualization tools to precisely demonstrate these morphological changes. To enhance the real-time representation of shape-morphing, we employ sensor fusion to detect and depict the soft robot’s structural changes as parameterized curves. Our system is fully operational in an AR environment, empowering users to conduct immersive examinations and simulate reconfigurations of real-world soft robotic systems.