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EnglishAbstract A methodology to plan the trajectories of robots that move in an n-dimensional Euclidean space, have to reach a target avoiding obstacles and are constrained to move in a region of the space is described. It is shown that if the positions of the obstacles are known then a Hamiltonian function can be constructed and used to define a collision-free trajectory. It is also shown that the method can be extended to the case in which the target or the obstacles (or both) move. Results of simulations for a pair of planar robots and a three degrees-of-freedom manipulator are finally reported.
| Titolo: | Hamiltonian path planning in constrained workspace | |
| Autori: | ||
| Data di pubblicazione: | 2017 | |
| Stato di pubblicazione: | Pubblicato | |
| Rivista: | ||
| Abstract: | Abstract A methodology to plan the trajectories of robots that move in an n-dimensional Euclidean space, have to reach a target avoiding obstacles and are constrained to move in a region of the space is described. It is shown that if the positions of the obstacles are known then a Hamiltonian function can be constructed and used to define a collision-free trajectory. It is also shown that the method can be extended to the case in which the target or the obstacles (or both) move. Results of simulations for a pair of planar robots and a three degrees-of-freedom manipulator are finally reported. | |
| Handle: | http://hdl.handle.net/11368/2890172 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1016/j.ejcon.2016.09.002 | |
| URL: | http://www.sciencedirect.com/science/article/pii/S0947358016301388 | |
| Appare nelle tipologie: | 1.1 Articolo in Rivista |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| 1-s2.0-S0947358016301388-main.pdf | Articolo principale | Documento in Versione Editoriale | Digital Rights Management non definito | Open Access Visualizza/Apri |
Utilizza questo identificativo per citare o creare un link a questo documento:
http://hdl.handle.net/11368/2890172
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