Sequential path planning for a formation of mobile robots with split and merge
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F17%3A00319123" target="_blank" >RIV/68407700:21730/17:00319123 - isvavai.cz</a>
Výsledek na webu
<a href="http://ieeexplore.ieee.org/document/8285722/" target="_blank" >http://ieeexplore.ieee.org/document/8285722/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/LA-CCI.2017.8285722" target="_blank" >10.1109/LA-CCI.2017.8285722</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Sequential path planning for a formation of mobile robots with split and merge
Popis výsledku v původním jazyce
An algorithm for robot formation path planning is presented in this paper. Given a map of the working environment, the algorithm finds a path for a formation taking into account possible split of the formation and its consecutive merge. The key part of the solution works on a graph and sequentially employs an extended version of Dijkstra's graph-based algorithm for multiple robots. It is thus deterministic, complete, computationally inexpensive, and finds a solution for a fixed source node to other node in the graph. Moreover, the presented solution is general enough to be incorporated into high-level tasks like cooperative surveillance and it can benefit from state-of-the-art formation motion planning approaches, which can be used for evaluation of edges of an input graph. The performed experimental results demonstrate behavior of the method in complex environments for formations consisting of tens of robots.
Název v anglickém jazyce
Sequential path planning for a formation of mobile robots with split and merge
Popis výsledku anglicky
An algorithm for robot formation path planning is presented in this paper. Given a map of the working environment, the algorithm finds a path for a formation taking into account possible split of the formation and its consecutive merge. The key part of the solution works on a graph and sequentially employs an extended version of Dijkstra's graph-based algorithm for multiple robots. It is thus deterministic, complete, computationally inexpensive, and finds a solution for a fixed source node to other node in the graph. Moreover, the presented solution is general enough to be incorporated into high-level tasks like cooperative surveillance and it can benefit from state-of-the-art formation motion planning approaches, which can be used for evaluation of edges of an input graph. The performed experimental results demonstrate behavior of the method in complex environments for formations consisting of tens of robots.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
R - Projekt Ramcoveho programu EK
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI)
ISBN
978-1-5386-3734-0
ISSN
—
e-ISSN
—
Počet stran výsledku
6
Strana od-do
—
Název nakladatele
IEEE
Místo vydání
New Jersey
Místo konání akce
Arequipa
Datum konání akce
8. 11. 2017
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—