Trajectory Optimization for the Handling of Elastically Coupled Objects via Reinforcement Learning and Flatness-Based Control

Author:

Kaczor Daniel,Bensch Martin,Schappler Moritz,Ortmaier Tobias

Publisher

Springer Berlin Heidelberg

Reference14 articles.

1. BECKMANN, D., SCHAPPLER, M., DAGEN, M., AND ORTMAIER, T. New approach using flatness-based control in high speed positioning: Experimental results. In International Conference on Industrial Technology (2015), IEEE, pp. 351–356.

2. CHEN, S. J. Time-Optimized Generation of Robot Trajectories Considering Object Dynamic Constraints. Universität Karlsruhe, 2007. PhD thesis.

3. FAUST, A., PALUNKO, I., CRUZ, P., FIERRO, R., AND TAPIA, L. Learning swingfree trajectories for UAVs with a suspended load. In International Conference on Robotics and Automation (may 2013), IEEE.

4. HASSELT, H. V. Double q-learning. In Advances in Neural Information Processing Systems 23, J. D. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. S. Zemel, and A. Culotta, Eds. Curran Associates, Inc., 2010, pp. 2613–2621.

5. JI LIN, L. Self-improving reactive agents based on reinforcement learning, planning and teaching. In Machine Learning (1992), pp. 293–321.

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