Energy-Based Kinematic Analysis on Magnetic Soft Continuum Robot with Asymmetric Magnetization
Junyeong Lee, Joowon Park, Sukho Park
AI summary
Problem
Magnetic soft continuum robots suffer from limited workspace due to constrained magnetic actuation forces, and the quantitative relationship between internal magnetization patterns and resulting workspace remains unclear.
Approach
The authors developed an energy-based kinematic model that minimizes total potential energy to predict equilibrium postures and workspace, validated via finite element analysis and physical experiments.
Key results
- Quantitative energy map predicting stable bending postures and snapping transitions
- Optimal linear asymmetric magnetization tip angle identified at 104°
- Experimental and FEA validation confirming workspace expansion predictions
- Asymmetric magnetization breaks symmetry constraints to enlarge effective workspace
Why it matters
Provides a practical design optimization framework for magnetic soft robots, enabling expanded workspace and precise motion control for minimally invasive surgical applications.
Abstract
Magnetically actuated soft continuum robots (MSCRs), which offer remote and wireless control via external magnetic fields along with high flexibility, have recently emerged as a promising technology for minimally invasive surgery (MIS). However, the magnetic actuation forces of MSCRs are generally limited, resulting in inherent workspace constraints. To overcome these limitations, various design strategies have been explored, including the development of an asymmetric magnetized soft continuum robot (AMSCR). Although AMSCRs have demonstrated a significantly larger workspace than conventional MSCRs, a quantitative relationship between the magnetization patterns of embedded magnetic particles and the resulting workspace has not yet been fully clarified. In this study, an energy-based kinematic analysis of AMSCR was conducted to address this issue. Specifically, the equilibrium posture of the AMSCR was determined by minimizing the total potential energy, considering different combinations of external magnetic field directions and internal magnetization patterns. Based on the resulting potential energy graph, the workspace of the AMSCR was quantitatively analyzed, and an optimal linear asymmetric magnetization pattern was identified. Furthermore, the proposed energy-based kinematic model was validated through finite element analysis (FEA) conducted using COMSOL Multiphysics, as well as through experiments performed on a fabricated AMSCR prototype. As a result, an optimal magnetization design method for linearly asymmetric AMSCRs was proposed and experimentally confirmed. The proposed approach is expected to be further applicable to the kinematic performance evaluation and design optimization of AMSCRs with various other magnetization patterns.