Learning Global Inverse Kinematics Solutions for a Continuum Robot

Author:

Thuruthel Thomas George,Falotico Egidio,Cianchetti Matteo,Laschi Cecilia

Publisher

Springer International Publishing

Reference15 articles.

1. Botond, B., Nguyen-Tuong, D., Csato, L., Bernhard, S. & Peters, J. (2011) Learning inverse kinematics with structured prediction. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 698−703).

2. D’Souza, A., Vijayakumar, S., & Schaal, S. (2001). Learning inverse kinematics. Proceedings, IEEE/RSJ International Conference on Intelligent Robots and Systems, 1, 298–303.

3. Foresee, F. D. & Hagan, M. T. (1997) Gauss-Newton approximation to Bayesian regularization. In Proceedings of the 1997 International Joint Conference on Neural Networks (pp. 1930–1935).

4. Giorelli, M., Renda, F., Calisti, M., Arienti, A., Ferri, G., & Laschi, C. (2015). Neural network and jacobian method for solving the inverse statics of a cable-driven soft arm with nonconstant curvature. IEEE Transactions on Robotics, 31(4), 823–834.

5. Jordan, M., & Rumelhart, D. (1992). Forward models: Supervised learning with distal teacher. Cognitive Science, 16, 307–354.

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