Název:	Motion planning for geometric models in data visualization
Autoři:	Szkandera, Jakub
Datum vydání:	2019
Nakladatel:	Západočeská univerzita v Plzni
Typ dokumentu:	report zpráva
URI:	http://www.kiv.zcu.cz/cz/vyzkum/publikace/technicke-zpravy/ http://hdl.handle.net/11025/35993
Klíčová slova:	plánování cesty;plánování pohybu;skupinový přístup;klastrový přístup
Klíčová slova v dalším jazyce:	path planning;motion planning;group approach;cluster approach
Abstrakt v dalším jazyce:	A finding of path is an important task in many research areas and it is a common problem solved in a wide range of applications. New problems of finding path appear and complex problems persist, such as a real-time plan- ning of paths for huge crowds in dynamic environments, where the properties according to which the cost of a path is evaluated as well as the topology of paths may change. The task of finding a path can be divided into path planning and motion planning, which implicitly respects the collision with surroundings in the environment. Within the first group this thesis focuses on path planning on graphs for crowds. The main idea is to group members of the crowd by their common initial and target positions and then plan the path for one representative member of each group. These representative members can be navigated by classic approaches and the rest of the group will follow them. If the crowd can be divided into a few groups this way, the proposed approach will save a huge amount of computational and memory demands in dynamic environments. In the second area, motion planning, we are dealing with another problem. The task is to navigate the ligand through the protein or into the protein, which turns out to be a challenging problem because it needs to be solved in 3D with the collision detection.
Práva:	© Západočeská univerzita v Plzni
Vyskytuje se v kolekcích:	Zprávy / Reports (KIV)

Všechny záznamy v DSpace jsou chráněny autorskými právy, všechna práva vyhrazena.