Multi-modal data-driven motion planning and synthesis
Mentar Mahmudi, Marcelo Kallmann
Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games, 2015, pp. 119--124.
Abstract: We present a new approach for whole-body motion synthesis that is able to generate high-quality motions for challenging mobile-manipulation scenarios. Our approach decouples the problem in specialized locomotion and manipulation skills, and proposes a multi-modal planning scheme that explores the search space of each skill together with the possible transition points between skills. In order to achieve high-quality results the locomotion skill is designed to be fully data-driven, while manipulation skills can be algorithmic or data-driven according to data availability and the complexity of the environment. Our method is able to automatically generate complex motions with precise manipulation targets among obstacles and in coordination with locomotion.
Article URL: http://doi.acm.org/10.1145/2822013.2822044
BibTeX format:
@inproceedings{10.1145-2822013.2822044,
  author = {Mentar Mahmudi and Marcelo Kallmann},
  title = {Multi-modal data-driven motion planning and synthesis},
  booktitle = {Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games},
  pages = {119--124},
  year = {2015},
}
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