Trabajo presentado en la IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), celebrada en Madrid, del 1 al 5 de octubre de 2018 ; In recent years the topic of combining motion and symbolic planning to perform complex tasks in the field of robotics has received a lot of attention. The underlying idea is to have access at once to the reasoning capabilities of a task planner and to the ability of the motion planner to verify that the plan is feasible from a physical and geometrical point of view. The present work describes a framework to perform manipulation tasks that require the use of two robotic manipulators. To do so we employ a Hierarchical Task Network (HTN) planner interleaved with geometric constraint verification. In this framework we also consider observation actions and handle noisy perceptions from a probabilistic perspective. These ideas are put into practice by means of an experimental set-up in which two Barrett WAM robots have to cooperatively solve a geometric puzzle. Our findings provide further evidence that considering explicitly physical constraints during task planning, rather than deferring their validation to the moment of execution, is advantageous in terms of execution time and breadth of situations that can be handled. ; This work is partially funded by the European project IMAGINE (Robots Understanding their Actions by Imagining their Effects), H2020- ICT-2016-1-731761, by the Spanish Ministry of Science and Innovation HuMoUR TIN2017-90086-R and the Spanish State Research Agency through the Maria de Maeztu Seal of Excellence to IRI (MDM-2016-0656) ; Peer reviewed
Interleaving hierarchical task planning and motion constraint testing for dual-arm manipulation
2019-01-07
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Task analysis , Planning , Uncertainty , Shape , Manipulators , Cameras
DDC: | 629 |
Hierarchical Task-Priority Control for Human-Robot Co-manipulation
Springer Verlag | 2020
|Hybrid Hierarchical Motion Planning
AIAA | 2008
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