Empirical Inference

A Flexible Hybrid Framework for Modeling Complex Manipulation Tasks

2011

Conference Paper

ei


Future service robots will need to perform a wide range of tasks using various objects. In order to perform complex tasks, robots require a suitable internal representation of the task. We propose a hybrid framework for representing manipulation tasks, which combines continuous motion planning and discrete task-level planning. In addition, we use a mid-level planner to optimize individual actions according to the plan. The proposed framework incorporates biologically-inspired concepts, such as affordances and motor primitives, in order to efficiently plan for manipulation tasks. The final framework is modular, can generalize well to different situations, and is straightforward to expand. Our demonstrations also show how the use of affordances and mid-level planning can lead to improved performance.

Author(s): Kroemer, O. and Peters, J.
Journal: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2011)
Pages: 1856-1861
Year: 2011
Month: May
Day: 0
Publisher: IEEE

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1109/ICRA.2011.5980237
Event Name: IEEE International Conference on Robotics and Automation (ICRA 2011)
Event Place: Shanghai, China

Address: Piscataway, NJ, USA
Digital: 0
ISBN: 978-1-61284-386-5
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF
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BibTex

@inproceedings{7049,
  title = {A Flexible Hybrid Framework for Modeling Complex Manipulation Tasks},
  author = {Kroemer, O. and Peters, J.},
  journal = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2011)},
  pages = {1856-1861 },
  publisher = {IEEE},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Piscataway, NJ, USA},
  month = may,
  year = {2011},
  doi = {10.1109/ICRA.2011.5980237 },
  month_numeric = {5}
}