Learning-based Inverse Kinematics from Shape as Input for Concentric Tube Continuum Robots
Nan Liang,Reinhard M. Grassmann,Sven Lilge,Jessica Burgner-Kahrs,Nan Liang,Reinhard M. Grassmann,Sven Lilge,Jessica Burgner-Kahrs
We introduce a methodology to compute the inverse kinematics for concentric tube continuum robots from a desired shape as input. We demonstrate that it is possible to accurately learn joint parameters using neural networks for a discrete point-wise shape representation with different discretization. In comparison to a vanilla numerical method, the learning-based method is preferred in terms of acc...
