A 6DOF gravity compensation scheme for a phantom premium using a neural network.
Current uses of haptic hardware such as the Phantom Premium 6DOF for surgical simulators lack the desired interface transparency and could cause artefacts in the training regime of a student training on a simulator. This problem is addressed and two neural networks are used to find a mapping between handle coordinates and orientation and force output required to counteract gravitational forces. A close fit to the data is achieved for both networks (errors of 0.00149 and 0.0157 between training and predicted forces) and 3DOF gravity compensation is achieved. A 6DOF simulator is created but requires further work to improve it accuracy.
Birtwisle
Matthew
M
School of Computing, University of Leeds, UK. matthewb@comp.leeds.ac.uk
Bulpitt
Andy
A
D003198:Computer Simulation; D013502:General Surgery / Q000193:education; D006112:Gravitation; D006801:Humans; D016571:Neural Networks, Computer; D012984:Software; D006113:United Kingdom