HAPCO: REAL TIME SIMULATION OF INTERACTION BETWEEN DEFORMABLE OBJECTS WITH HAPTIC FEEDBACK FOR SOLVING FRICTION MULTIPLE CONTACTS

2019 ◽  
Vol 38 (6) ◽  
pp. 1-13 ◽  
Author(s):  
Zangyueyang Xian ◽  
Xin Tong ◽  
Tiantian Liu

Author(s):  
Madusudanan Sathia Narayanan ◽  
Puneet Singla ◽  
Sudha Garimella ◽  
Wayne Waz ◽  
Venkat Krovi

Nonlinearities inherent in soft-tissue interactions create roadblocks to realization of high-fidelity real-time haptics-based medical simulations. While finite element (FE) formulations offer greater accuracy over conventional spring-mass-network models, computational-complexity limits achievable simulation-update rates. Direct interaction with sensorized physical surrogates, in offline or online modes, allows a temporary sidestepping of computational issues but hinders parametric analysis and true exploitation of a simulation-based testing paradigm. Hence, in this paper, we develop Radial-Basis Neural-Network approximations, to FE-model data within a Modified Resource Allocating Network (MRAN) framework. Real-time simulation of the reduced order neural-network approximations at high temporal resolution provided the haptic-feedback. Validation studies are being conducted to evaluate the kinesthetic realism of these models with medical experts.


2008 ◽  
Vol 32 (3) ◽  
pp. 293-306 ◽  
Author(s):  
Marcos García ◽  
Oscar D. Robles ◽  
Luis Pastor ◽  
Angel Rodríguez

1997 ◽  
Vol 21 (1-2) ◽  
pp. S1111-S1115
Author(s):  
P Lundstrøm

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