Accelerating Proximity Queries Accelerating Proximity Queries for Non-convex Geometries in a Robot Cell Context

dc.contributor.authorThorén, Joakim
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineering (Chalmers)en
dc.description.abstractSampling-based motion-planners, for example rapidly exploring dense tree (RRT) based planners, depend on fast proximity queries. Regrettably, bounding volume tests are significant bottlenecks of proximity queries. Sampling-based motion-planners are therefore accelerated by reducing the number of bounding volume tests. To this end, a novel algorithm called Forest Proximity Query (FPQ) is developed. Contrary to previous research, FPQ traverses several pairs of BVHs simultaneously, effectively exploiting an actuality that only a single minimal separation distance — out of several possible separation distances — is required during sampling-based motion-planning. An implementation of FPQ show that FPQ performs up to 67% fewer BV tests in comparison to the well-known Proximity Query Package, increasing proximity querying performance by up to 46%. In conclusion, FPQ is successful in its attempt at improving performance of sampling-based motion-planners.
dc.subjectInformations- och kommunikationsteknik
dc.subjectData- och informationsvetenskap
dc.subjectInformation & Communication Technology
dc.subjectComputer and Information Science
dc.titleAccelerating Proximity Queries Accelerating Proximity Queries for Non-convex Geometries in a Robot Cell Context
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
local.programmeComplex adaptive systems (MPCAS), MSc
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