TY - JOUR
T1 - Three-Arm Collaborative Control With Magneto-Contact-Motion Decoupling for Magnetic-Assisted Surgical Robot
AU - Wang, Xingfang
AU - Huang, Xiao
AU - Jiang, Yifan
AU - Wang, Dong
AU - Li, Hui
AU - Jiang, Zhihong
N1 - Publisher Copyright:
© 1996-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
KW - Magnetic assistance
KW - multiphysics decoupling
KW - optimal control
KW - robot planning
KW - three-arm collaboration
UR - https://www.scopus.com/pages/publications/105027784439
U2 - 10.1109/TMECH.2025.3648395
DO - 10.1109/TMECH.2025.3648395
M3 - Article
AN - SCOPUS:105027784439
SN - 1083-4435
JO - IEEE/ASME Transactions on Mechatronics
JF - IEEE/ASME Transactions on Mechatronics
ER -