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https://doi.org/10.17559/TV-20160118150332

Task planning based on the interpretation of spatial structures

Marko Švaco   ORCID icon orcid.org/0000-0002-6761-4336 ; University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Ivana Lučića 5, 10000 Zagreb, Croatia
Bojan Jerbić   ORCID icon orcid.org/0000-0003-1811-5669 ; University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Ivana Lučića 5, 10000 Zagreb, Croatia
Bojan Šekoranja ; University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Ivana Lučića 5, 10000 Zagreb, Croatia

Puni tekst: engleski, pdf (2 MB) str. 427-434 preuzimanja: 124* citiraj
APA 6th Edition
Švaco, M., Jerbić, B. i Šekoranja, B. (2017). Task planning based on the interpretation of spatial structures. Tehnički vjesnik, 24 (2), 427-434. https://doi.org/10.17559/TV-20160118150332
MLA 8th Edition
Švaco, Marko, et al. "Task planning based on the interpretation of spatial structures." Tehnički vjesnik, vol. 24, br. 2, 2017, str. 427-434. https://doi.org/10.17559/TV-20160118150332. Citirano 20.08.2019.
Chicago 17th Edition
Švaco, Marko, Bojan Jerbić i Bojan Šekoranja. "Task planning based on the interpretation of spatial structures." Tehnički vjesnik 24, br. 2 (2017): 427-434. https://doi.org/10.17559/TV-20160118150332
Harvard
Švaco, M., Jerbić, B., i Šekoranja, B. (2017). 'Task planning based on the interpretation of spatial structures', Tehnički vjesnik, 24(2), str. 427-434. https://doi.org/10.17559/TV-20160118150332
Vancouver
Švaco M, Jerbić B, Šekoranja B. Task planning based on the interpretation of spatial structures. Tehnički vjesnik [Internet]. 2017 [pristupljeno 20.08.2019.];24(2):427-434. https://doi.org/10.17559/TV-20160118150332
IEEE
M. Švaco, B. Jerbić i B. Šekoranja, "Task planning based on the interpretation of spatial structures", Tehnički vjesnik, vol.24, br. 2, str. 427-434, 2017. [Online]. https://doi.org/10.17559/TV-20160118150332
Puni tekst: hrvatski, pdf (2 MB) str. 427-434 preuzimanja: 111* citiraj
APA 6th Edition
Švaco, M., Jerbić, B. i Šekoranja, B. (2017). Algoritam planiranja zasnovan na interpretaciji prostornih struktura. Tehnički vjesnik, 24 (2), 427-434. https://doi.org/10.17559/TV-20160118150332
MLA 8th Edition
Švaco, Marko, et al. "Algoritam planiranja zasnovan na interpretaciji prostornih struktura." Tehnički vjesnik, vol. 24, br. 2, 2017, str. 427-434. https://doi.org/10.17559/TV-20160118150332. Citirano 20.08.2019.
Chicago 17th Edition
Švaco, Marko, Bojan Jerbić i Bojan Šekoranja. "Algoritam planiranja zasnovan na interpretaciji prostornih struktura." Tehnički vjesnik 24, br. 2 (2017): 427-434. https://doi.org/10.17559/TV-20160118150332
Harvard
Švaco, M., Jerbić, B., i Šekoranja, B. (2017). 'Algoritam planiranja zasnovan na interpretaciji prostornih struktura', Tehnički vjesnik, 24(2), str. 427-434. https://doi.org/10.17559/TV-20160118150332
Vancouver
Švaco M, Jerbić B, Šekoranja B. Algoritam planiranja zasnovan na interpretaciji prostornih struktura. Tehnički vjesnik [Internet]. 2017 [pristupljeno 20.08.2019.];24(2):427-434. https://doi.org/10.17559/TV-20160118150332
IEEE
M. Švaco, B. Jerbić i B. Šekoranja, "Algoritam planiranja zasnovan na interpretaciji prostornih struktura", Tehnički vjesnik, vol.24, br. 2, str. 427-434, 2017. [Online]. https://doi.org/10.17559/TV-20160118150332

Sažetak
In this research, a new task planning algorithm is developed for building a desired object configuration from a given initial unordered object state. The task of the planning algorithm is to find a feasible set of actions, i.e. a finite number of discrete transformations, which can rearrange the objects into a desired ordered final state. The environment is interpreted through the position and orientation of the objects. The solution to the planning problem is proposed as a two-step method. First, a constructive heuristic generates an initial set of good solutions. The constructive heuristic uses only mutations for making an initial population of state transitions. A genetic algorithm is developed for optimizing the initial set of solutions. The genetic algorithm is characterized by a parallel evolutionary strategy, with the aim of spatial transformation of unordered object states into ordered object states. The algorithm can be used for solving the task planning problems represented in the two-dimensional space. Verification of the planning algorithm is done in a virtual environment.

Ključne riječi
genetic algorithms; robotics; task planning

Hrčak ID: 179852

URI
https://hrcak.srce.hr/179852

[hrvatski]

Posjeta: 418 *