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oai:drops-oai.dagstuhl.de:5960 2024-03-06T10:37:22Z ddc:004 open_access

Path Planning for Simple Robots using Soft Subdivision Search Hsu, Ching-Hsiang Ryan, John Paul Yap, Chee Robot Path Planning Soft Predicates Resolution-Exact Algorithm Subdivision Search The concept of resolution-exact path planning is a theoretically sound alternative to the standard exact algorithms, and provides much stronger guarantees than probabilistic or sampling algorithms. It opens the way for the introduction of soft predicates in the context of subdivision algorithm. Taking a leaf from the great success of the Probabilistic Road Map (PRM) framework, we formulate an analogous framework for subdivision, called Soft Subdivision Search (SSS). In this video, we illustrate the SSS framework for a trio of simple planar robots: disc, triangle and 2-links. These robots have, respectively, 2, 3 and 4 degrees of freedom. Our 2-link robot can also avoid self-crossing. These algorithms operate in realtime and are relatively easy to implement. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ching-Hsiang Hsu and John Paul Ryan and Chee Yap 2016 Is Part Of LIPIcs, Volume 51, 32nd International Symposium on Computational Geometry (SoCG 2016) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.SoCG.2016.68 urn:nbn:de:0030-drops-59607 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2016.68 eng https://creativecommons.org/licenses/by/3.0/legalcode