Abstract
Magnetic-assisted surgical robots reduce incision size and physical collisions through noncontact manipulation, showing great potential in minimally invasive surgery. However, multiarm systems face critical magneto-contact-motion coupling challenges (e.g., ensuring magnetic, contact, and motion safety among multiple arms during precise control), limiting robots’ medical applications. A novel three-arm collaborative control method based on a coupled magnetic model and multiconstraint optimization is proposed to solve these challenges. A dipole-based magnetic model is built to describe multimagnetic interactions, combining with Bayesian optimization to dynamically predict the coupled magnetic forces. Using the above magnetic model, a sampling-based optimization framework is built to handle multiple constraints including task synchronization, motion safety, magnetic limitation, and contact force tracking, decoupling magneto-contact-motion multiphysics in real time. Experimental results show that the three-arm system can precisely and safely perform simulated surgical tasks like lesion exposure and organ mobilization, using a foot pedal, validating the proposed method’s magnetic-assisted efficiency and collaborative safety.
| Original language | English |
|---|---|
| Journal | IEEE/ASME Transactions on Mechatronics |
| DOIs | |
| Publication status | Accepted/In press - 2026 |
| Externally published | Yes |
Keywords
- Magnetic assistance
- multiphysics decoupling
- optimal control
- robot planning
- three-arm collaboration
Fingerprint
Dive into the research topics of 'Three-Arm Collaborative Control With Magneto-Contact-Motion Decoupling for Magnetic-Assisted Surgical Robot'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver