{"title":"CPS Testing using Stateless RRT","authors":"Abhinav Chawla, Stanley Bak","doi":"10.1109/iccps54341.2022.00042","DOIUrl":null,"url":null,"abstract":"Cyber-Physical Systems (CPS) are created as complex interactions of multiple physical systems and play a vital role in automating real-life systems. In this work, we present a testing methodology for CPS based on modified version of the Rapidly-exploring Random Tree (RRT) algorithm which is used traditionally to solve the motion planning problem in the context of the CPS testing problem. Directly using RRT for testing CPS requires storing the state of the CPS controller at each node of the RRT which is often memory intensive. Further, the simulator needs to support initialization from arbitrary states, which is not always possible, especially for complex simulation environments. We present our progress towards a modified RRT algorithm where the state of the controller is not required to be saved at each node, and show promising improvements in testing efficiency using a 9-D simulated point example system.","PeriodicalId":340078,"journal":{"name":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iccps54341.2022.00042","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Cyber-Physical Systems (CPS) are created as complex interactions of multiple physical systems and play a vital role in automating real-life systems. In this work, we present a testing methodology for CPS based on modified version of the Rapidly-exploring Random Tree (RRT) algorithm which is used traditionally to solve the motion planning problem in the context of the CPS testing problem. Directly using RRT for testing CPS requires storing the state of the CPS controller at each node of the RRT which is often memory intensive. Further, the simulator needs to support initialization from arbitrary states, which is not always possible, especially for complex simulation environments. We present our progress towards a modified RRT algorithm where the state of the controller is not required to be saved at each node, and show promising improvements in testing efficiency using a 9-D simulated point example system.