Jointly learning trajectory generation and hitting point prediction in robot table tennis

Huang, Y, Büchler, D, Koç, O et al. (2 more authors) (2017) Jointly learning trajectory generation and hitting point prediction in robot table tennis. In: 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids). IEEE-RAS 16th International Conference on Humanoid Robots, 15-17 Nov 2016, Cancun, México. IEEE , pp. 650-655.

Abstract

Metadata

Authors/Creators:
  • Huang, Y
  • Büchler, D
  • Koç, O
  • Schölkopf, B
  • Peters, J
Copyright, Publisher and Additional Information: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Trajectory; Robots; Kinematics; Correlation; Databases; Learning (artificial intelligence); Predictive models
Dates:
  • Published: 2 January 2017
  • Accepted: 21 September 2016
  • Published (online): 2 January 2017
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 01 May 2020 14:53
Last Modified: 29 May 2020 10:21
Status: Published
Publisher: IEEE
Identification Number: https://doi.org/10.1109/HUMANOIDS.2016.7803343

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