Matthias Bentert, Daniel Coimbra Salomao, Alex Crane, Yosuke Mizutani, Felix Reidl, Blair D. Sullivan
{"title":"Graph Inspection for Robotic Motion Planning: Do Arithmetic Circuits Help?","authors":"Matthias Bentert, Daniel Coimbra Salomao, Alex Crane, Yosuke Mizutani, Felix Reidl, Blair D. Sullivan","doi":"arxiv-2409.08219","DOIUrl":null,"url":null,"abstract":"We investigate whether algorithms based on arithmetic circuits are a viable\nalternative to existing solvers for Graph Inspection, a problem with direct\napplication in robotic motion planning. Specifically, we seek to address the\nhigh memory usage of existing solvers. Aided by novel theoretical results\nenabling fast solution recovery, we implement a circuit-based solver for Graph\nInspection which uses only polynomial space and test it on several realistic\nrobotic motion planning datasets. In particular, we provide a comprehensive\nexperimental evaluation of a suite of engineered algorithms for three key\nsubroutines. While this evaluation demonstrates that circuit-based methods are\nnot yet practically competitive for our robotics application, it also provides\ninsights which may guide future efforts to bring circuit-based algorithms from\ntheory to practice.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We investigate whether algorithms based on arithmetic circuits are a viable
alternative to existing solvers for Graph Inspection, a problem with direct
application in robotic motion planning. Specifically, we seek to address the
high memory usage of existing solvers. Aided by novel theoretical results
enabling fast solution recovery, we implement a circuit-based solver for Graph
Inspection which uses only polynomial space and test it on several realistic
robotic motion planning datasets. In particular, we provide a comprehensive
experimental evaluation of a suite of engineered algorithms for three key
subroutines. While this evaluation demonstrates that circuit-based methods are
not yet practically competitive for our robotics application, it also provides
insights which may guide future efforts to bring circuit-based algorithms from
theory to practice.