Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308670143> ?p ?o ?g. }
- W4308670143 endingPage "11" @default.
- W4308670143 startingPage "1" @default.
- W4308670143 abstract "Assembly planning is the core of automating product assembly, maintenance, and recycling for modern industrial manufacturing. Despite its importance and long history of research, planning for mechanical assemblies when given the final assembled state remains a challenging problem. This is due to the complexity of dealing with arbitrary 3D shapes and the highly constrained motion required for real-world assemblies. In this work, we propose a novel method to efficiently plan physically plausible assembly motion and sequences for real-world assemblies. Our method leverages the assembly-by-disassembly principle and physics-based simulation to efficiently explore a reduced search space. To evaluate the generality of our method, we define a large-scale dataset consisting of thousands of physically valid industrial assemblies with a variety of assembly motions required. Our experiments on this new benchmark demonstrate we achieve a state-of-the-art success rate and the highest computational efficiency compared to other baseline algorithms. Our method also generalizes to rotational assemblies (e.g., screws and puzzles) and solves 80-part assemblies within several minutes." @default.
- W4308670143 created "2022-11-14" @default.
- W4308670143 creator A5012706585 @default.
- W4308670143 creator A5018010391 @default.
- W4308670143 creator A5039112646 @default.
- W4308670143 creator A5057506352 @default.
- W4308670143 creator A5065859286 @default.
- W4308670143 creator A5067025277 @default.
- W4308670143 creator A5079002770 @default.
- W4308670143 creator A5086301079 @default.
- W4308670143 date "2022-11-30" @default.
- W4308670143 modified "2023-10-15" @default.
- W4308670143 title "Assemble Them All" @default.
- W4308670143 cites W1967312749 @default.
- W4308670143 cites W1969196471 @default.
- W4308670143 cites W1978769391 @default.
- W4308670143 cites W1997857829 @default.
- W4308670143 cites W2002548850 @default.
- W4308670143 cites W2029126008 @default.
- W4308670143 cites W2036269249 @default.
- W4308670143 cites W2077956684 @default.
- W4308670143 cites W2086807633 @default.
- W4308670143 cites W2093692784 @default.
- W4308670143 cites W2099100661 @default.
- W4308670143 cites W2128990851 @default.
- W4308670143 cites W2135343371 @default.
- W4308670143 cites W2141664020 @default.
- W4308670143 cites W2151645094 @default.
- W4308670143 cites W2158782408 @default.
- W4308670143 cites W2160883580 @default.
- W4308670143 cites W2163185513 @default.
- W4308670143 cites W2724314443 @default.
- W4308670143 cites W2796864868 @default.
- W4308670143 cites W2890651645 @default.
- W4308670143 cites W2960095795 @default.
- W4308670143 cites W2961368225 @default.
- W4308670143 cites W2964333597 @default.
- W4308670143 cites W2967129319 @default.
- W4308670143 cites W2968116426 @default.
- W4308670143 cites W2972931660 @default.
- W4308670143 cites W2980109758 @default.
- W4308670143 cites W2983951224 @default.
- W4308670143 cites W2990747716 @default.
- W4308670143 cites W2997885238 @default.
- W4308670143 cites W3048456101 @default.
- W4308670143 cites W3075117108 @default.
- W4308670143 cites W3091677803 @default.
- W4308670143 cites W3109467707 @default.
- W4308670143 cites W3109952375 @default.
- W4308670143 cites W3124478152 @default.
- W4308670143 cites W3137832514 @default.
- W4308670143 cites W3164860655 @default.
- W4308670143 cites W3181222244 @default.
- W4308670143 cites W3182027409 @default.
- W4308670143 cites W3185376398 @default.
- W4308670143 cites W3195717292 @default.
- W4308670143 cites W3201299100 @default.
- W4308670143 cites W3217122878 @default.
- W4308670143 cites W4200412188 @default.
- W4308670143 cites W4249992830 @default.
- W4308670143 cites W847326694 @default.
- W4308670143 doi "https://doi.org/10.1145/3550454.3555525" @default.
- W4308670143 hasPublicationYear "2022" @default.
- W4308670143 type Work @default.
- W4308670143 citedByCount "3" @default.
- W4308670143 countsByYear W43086701432023 @default.
- W4308670143 crossrefType "journal-article" @default.
- W4308670143 hasAuthorship W4308670143A5012706585 @default.
- W4308670143 hasAuthorship W4308670143A5018010391 @default.
- W4308670143 hasAuthorship W4308670143A5039112646 @default.
- W4308670143 hasAuthorship W4308670143A5057506352 @default.
- W4308670143 hasAuthorship W4308670143A5065859286 @default.
- W4308670143 hasAuthorship W4308670143A5067025277 @default.
- W4308670143 hasAuthorship W4308670143A5079002770 @default.
- W4308670143 hasAuthorship W4308670143A5086301079 @default.
- W4308670143 hasBestOaLocation W43086701431 @default.
- W4308670143 hasConcept C104114177 @default.
- W4308670143 hasConcept C11413529 @default.
- W4308670143 hasConcept C13280743 @default.
- W4308670143 hasConcept C136197465 @default.
- W4308670143 hasConcept C154945302 @default.
- W4308670143 hasConcept C15744967 @default.
- W4308670143 hasConcept C166957645 @default.
- W4308670143 hasConcept C185798385 @default.
- W4308670143 hasConcept C205649164 @default.
- W4308670143 hasConcept C2524010 @default.
- W4308670143 hasConcept C2776505523 @default.
- W4308670143 hasConcept C2780767217 @default.
- W4308670143 hasConcept C33923547 @default.
- W4308670143 hasConcept C41008148 @default.
- W4308670143 hasConcept C48103436 @default.
- W4308670143 hasConcept C542102704 @default.
- W4308670143 hasConcept C90673727 @default.
- W4308670143 hasConcept C95457728 @default.
- W4308670143 hasConceptScore W4308670143C104114177 @default.
- W4308670143 hasConceptScore W4308670143C11413529 @default.
- W4308670143 hasConceptScore W4308670143C13280743 @default.
- W4308670143 hasConceptScore W4308670143C136197465 @default.