Collision-free path planning
dc.contributor.advisor | James H. Oliver | |
dc.contributor.author | Chen, Shiang-Fong | |
dc.contributor.department | Mechanical Engineering | |
dc.date | 2018-08-23T16:04:54.000 | |
dc.date.accessioned | 2020-06-30T07:13:00Z | |
dc.date.available | 2020-06-30T07:13:00Z | |
dc.date.copyright | Wed Jan 01 00:00:00 UTC 1997 | |
dc.date.issued | 1997 | |
dc.description.abstract | <p>Motion planning is an important challenge in robotics research. Efficient generation of collision-free motion is a fundamental capability necessary for autonomous robots;In this dissertation, a fast and practical algorithm for moving a convex polygonal robot among a set of polygonal obstacles with translations and rotations is presented. The running time is O(c((n + k)N + nlogn)), where c is a parameter controlling the precision of the results, n is the total number of obstacle vertices, k is the number of intersections of configuration space obstacles, and N is the number of obstacles, decomposed into convex objects. This dissertation exploits a simple 3D passage-network to incorporate robot rotations as an alternative to complex cell decomposition techniques or building passage networks on approximated 3D C-space obstacles;A common approach in path planning is to compute the Minkowski difference of a polygonal robot model with the polygonal obstacle environment. However such a configuration space is valid only for a single robot orientation. In this research, multiple configuration spaces are computed between the obstacle environment and the robot at successive angular orientations spanning [pi] . Although the obstacles do not intersect, each configuration space may contain intersecting configuration space obstacles (C-space obstacles). For each configuration space, the algorithm finds the contour of the intersected C-space obstacles and the associated passage network by slabbing the collision-free space. The individual configuration spaces are then related to one another by a heuristic called "proper links" that exploit spatial coherence. Thus, each level is connected to the adjacent levels by proper links to construct a 3D network. Dijkstra's algorithm is used to search for the shortest path in the 3D network. Finally, the path is projected onto the plane to show the final locus of the path.</p> | |
dc.format.mimetype | application/pdf | |
dc.identifier | archive/lib.dr.iastate.edu/rtd/11449/ | |
dc.identifier.articleid | 12448 | |
dc.identifier.contextkey | 6455323 | |
dc.identifier.doi | https://doi.org/10.31274/rtd-180813-10480 | |
dc.identifier.s3bucket | isulib-bepress-aws-west | |
dc.identifier.submissionpath | rtd/11449 | |
dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/64707 | |
dc.language.iso | en | |
dc.source.bitstream | archive/lib.dr.iastate.edu/rtd/11449/r_9725400.pdf|||Fri Jan 14 18:50:27 UTC 2022 | |
dc.subject.disciplines | Mechanical Engineering | |
dc.subject.keywords | Mechanical engineering | |
dc.title | Collision-free path planning | |
dc.type | dissertation | |
dc.type.genre | dissertation | |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | 6d38ab0f-8cc2-4ad3-90b1-67a60c5a6f59 | |
thesis.degree.level | dissertation | |
thesis.degree.name | Doctor of Philosophy |
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