Sangam: A Confluence of Knowledge Streams

GRAPH-BASED METHODS FOR PATH PLANNING WITH DYNAMIC OBSTACLES USING LINEAR TEMPORAL LOGIC

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dc.contributor Herrmann, Jeffrey
dc.contributor Digital Repository at the University of Maryland
dc.contributor University of Maryland (College Park, Md.)
dc.contributor Systems Engineering
dc.creator Han, Wenqi
dc.date 2018-09-19T05:33:45Z
dc.date 2018-09-19T05:33:45Z
dc.date 2018
dc.date.accessioned 2022-05-20T08:38:07Z
dc.date.available 2022-05-20T08:38:07Z
dc.identifier https://doi.org/10.13016/M2C824J3V
dc.identifier http://hdl.handle.net/1903/21422
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/117593
dc.description Autonomous vehicles are expected to play a key role in rescue and transportation. Planning an optimal path with the minimum computational effort for these vehicles in their missions improves their efficiency and adds safety for the vehicles and third parties on the ground. The objective of this thesis is to study the computational effort of four planning methods that implement linear temporal logic (LTL) to translate the high-level mission requirements and environmental specifications. The Potential Field Method and the Critical Path method required less computational effort to find one of the shortest paths for the mission The Multigraph Network Planning method and the Critical Path method can find all the possible paths with predetermined path length. The Random Walk method required more computational effort and memory compared to the other three methods.
dc.format application/pdf
dc.format image/gif
dc.format image/gif
dc.format image/gif
dc.language en
dc.subject Operations research
dc.subject Artificial intelligence
dc.subject Aerospace engineering
dc.subject D star lite
dc.subject dynamic obstacle
dc.subject Linear Temporal Logic
dc.subject path plan
dc.subject ptential field
dc.title GRAPH-BASED METHODS FOR PATH PLANNING WITH DYNAMIC OBSTACLES USING LINEAR TEMPORAL LOGIC
dc.type Thesis


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