Object dynamics prediction and motion generation based on reliable predictability

Shun Nishide, Tetsuya Ogata, Ryunosuke Yokoya, Jun Tani, Kazunori Komatani, Hiroshi G. Okuno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Consistency of object dynamics, which is related to reliable predictability, is an important factor for generating object manipulation motions. This paper proposes a technique to generate autonomous motions based on consistency of object dynamics. The technique resolves two issues: construction of an object dynamics prediction model and evaluation of consistency. The authors utilize Recurrent Neural Network with Parametric Bias to self-organize the dynamics, and link static images to the self-organized dynamics using a hierarchical neural network to deal with the first issue. For evaluation of consistency, the authors have set an evaluation function based on object dynamics relative to robot motor dynamics. Experiments have shown that the method is capable of predicting 90% of unknown object dynamics. Motion generation experiments have proved that the technique is capable of generating autonomous pushing motions that generate consistent rolling motions.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
Pages1608-1614
Number of pages7
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Robotics and Automation, ICRA 2008 - Pasadena, CA
Duration: 2008 May 192008 May 23

Other

Other2008 IEEE International Conference on Robotics and Automation, ICRA 2008
CityPasadena, CA
Period08/5/1908/5/23

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ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering

Cite this

Nishide, S., Ogata, T., Yokoya, R., Tani, J., Komatani, K., & Okuno, H. G. (2008). Object dynamics prediction and motion generation based on reliable predictability. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 1608-1614). [4543431] https://doi.org/10.1109/ROBOT.2008.4543431