2026-09-20T05:00:54Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1391062022-01-15T03:02:00Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Kaelbling, Leslie P.
Curtis, Shiloh
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-01-14T14:50:16Z
2022-01-14T14:50:16Z
2021-06
2021-06-17T20:13:06.916Z
https://hdl.handle.net/1721.1/139106
Navigation in multi-floor, multi-building environments is increasingly important in robotics. For wheeled robots, these environments can be conveniently modeled as a set of 2D maps, representing floors, connected by “wormholes”, which represent elevators and other between-floor connections. The full topological structure of the space can thus be described as a weighted graph. However, existing planning algorithms for multi-floor environments modeled in this way do not extend the guarantees on completeness and optimality provided by the underlying motion planning algorithms used within the 2D maps.
This work proposes a new algorithm, HRG*, for probabilistically complete and asymptotically optimal multi-floor path planning that carries these guarantees, together with a reference implementation whose performance is characterized in comparison to the native version.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
A Hierarchical Algorithm for Probabilistically Complete Path Planning in Multi-Floor Environments
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
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unknown
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<Abstract>Navigation in multi-floor, multi-building environments is increasingly important in robotics. For wheeled robots, these environments can be conveniently modeled as a set of 2D maps, representing floors, connected by “wormholes”, which represent elevators and other between-floor connections. The full topological structure of the space can thus be described as a weighted graph. However, existing planning algorithms for multi-floor environments modeled in this way do not extend the guarantees on completeness and optimality provided by the underlying motion planning algorithms used within the 2D maps.
This work proposes a new algorithm, HRG*, for probabilistically complete and asymptotically optimal multi-floor path planning that carries these guarantees, together with a reference implementation whose performance is characterized in comparison to the native version.</Abstract>
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