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Soft Magnetic Tactile Skin for Continuous Force and Location Estimation Using Neural Networks.

, , , , , and . IEEE Robotics Autom. Lett., 5 (3): 3892-3898 (2020)

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A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms., , and . J. Mach. Learn. Res., (2021)Combining active learning and reactive control for robot grasping., , , and . Robotics Auton. Syst., 58 (9): 1105-1116 (2010)A Comparison of Autoregressive Hidden Markov Models for Multimodal Manipulations With Variable Masses., and . IEEE Robotics Autom. Lett., 2 (2): 1101-1108 (2017)Learning Dynamic Tactile Sensing With Robust Vision-Based Training., , and . IEEE Trans. Robotics, 27 (3): 545-557 (2011)Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot., , , and . IAS, volume 302 of Advances in Intelligent Systems and Computing, page 1601-1611. Springer, (2014)A comparison of contact distribution representations for learning to predict object interactions., , , and . Humanoids, page 616-622. IEEE, (2015)Learning spatial preconditions of manipulation skills using random forests., and . Humanoids, page 676-683. IEEE, (2016)Towards Robotic Tree Manipulation: Leveraging Graph Representations., , , and . CoRR, (2023)Focused Adaptation of Dynamics Models for Deformable Object Manipulation., , , and . CoRR, (2022)Predicting object interactions from contact distributions., and . IROS, page 3361-3367. IEEE, (2014)