A Flexible Hybrid Framework for Modeling Complex Manipulation Tasks
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 |
Bibtex Type: | Conference Paper (inproceedings) |
Address: | Piscataway, NJ, USA |
DOI: | 10.1109/ICRA.2011.5980237 |
Event Name: | IEEE International Conference on Robotics and Automation (ICRA 2011) |
Event Place: | Shanghai, China |
Digital: | 0 |
Electronic Archiving: | grant_archive |
ISBN: | 978-1-61284-386-5 |
Language: | en |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
BibTex
@inproceedings{7049, title = {A Flexible Hybrid Framework for Modeling Complex Manipulation Tasks}, journal = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2011)}, abstract = {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.}, pages = {1856-1861 }, publisher = {IEEE}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Piscataway, NJ, USA}, month = may, year = {2011}, slug = {7049}, author = {Kroemer, O. and Peters, J.}, month_numeric = {5} }