{"title":"具有时空和热约束的3D打印最佳刀具路径规划","authors":"Zahra Rahimi Afzal, P. Prabhakar, P. Prabhakar","doi":"10.1109/ICC47138.2019.9123182","DOIUrl":null,"url":null,"abstract":"In this paper, we address the problem of synthesizing optimal path plans in 2D subject to spatio-temporal and thermal constraints. Our solution consists of reducing the path planning problem to a Mixed Integer Linear Programming (MILP) problem. The challenge is in encoding the “implication” constraints in the path planning problem using only conjunctions that are permitted by the MILP formulation. Our experimental analysis using an implementation of the encoding in a Python toolbox demonstrates the feasibility of our approach in generating the optimal plans.","PeriodicalId":231050,"journal":{"name":"2019 Sixth Indian Control Conference (ICC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimal tool path planning for 3D printing with spatio-temporal and thermal constraints\",\"authors\":\"Zahra Rahimi Afzal, P. Prabhakar, P. Prabhakar\",\"doi\":\"10.1109/ICC47138.2019.9123182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we address the problem of synthesizing optimal path plans in 2D subject to spatio-temporal and thermal constraints. Our solution consists of reducing the path planning problem to a Mixed Integer Linear Programming (MILP) problem. The challenge is in encoding the “implication” constraints in the path planning problem using only conjunctions that are permitted by the MILP formulation. Our experimental analysis using an implementation of the encoding in a Python toolbox demonstrates the feasibility of our approach in generating the optimal plans.\",\"PeriodicalId\":231050,\"journal\":{\"name\":\"2019 Sixth Indian Control Conference (ICC)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Sixth Indian Control Conference (ICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICC47138.2019.9123182\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Sixth Indian Control Conference (ICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICC47138.2019.9123182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal tool path planning for 3D printing with spatio-temporal and thermal constraints
In this paper, we address the problem of synthesizing optimal path plans in 2D subject to spatio-temporal and thermal constraints. Our solution consists of reducing the path planning problem to a Mixed Integer Linear Programming (MILP) problem. The challenge is in encoding the “implication” constraints in the path planning problem using only conjunctions that are permitted by the MILP formulation. Our experimental analysis using an implementation of the encoding in a Python toolbox demonstrates the feasibility of our approach in generating the optimal plans.