N. Hemken, F. Jacob, Fabian Peller-Konrad, Rainer Kartmann, T. Asfour, H. Hartenstein
{"title":"Poster: How to Raise a Robot - Beyond Access Control Constraints in Assistive Humanoid Robots","authors":"N. Hemken, F. Jacob, Fabian Peller-Konrad, Rainer Kartmann, T. Asfour, H. Hartenstein","doi":"10.1145/3589608.3595078","DOIUrl":null,"url":null,"abstract":"Humanoid robots will be able to assist humans in their daily life, in particular due to their versatile action capabilities. However, while these robots need a certain degree of autonomy to learn and explore, they also should respect various constraints, for access control and beyond. We explore incorporating privacy and security constraints (Activity-Centric Access Control and Deep Learning Based Access Control) with robot task planning approaches (classical symbolic planning and end-to-end learning-based planning). We report pre-liminary results on their respective trade-offs and conclude that a hybrid approach will most likely be the method of choice.","PeriodicalId":74509,"journal":{"name":"Proceedings of the ... ACM symposium on access control models and technologies. ACM Symposium on Access Control Models and Technologies","volume":"32 1","pages":"55-57"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... ACM symposium on access control models and technologies. ACM Symposium on Access Control Models and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3589608.3595078","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
Humanoid robots will be able to assist humans in their daily life, in particular due to their versatile action capabilities. However, while these robots need a certain degree of autonomy to learn and explore, they also should respect various constraints, for access control and beyond. We explore incorporating privacy and security constraints (Activity-Centric Access Control and Deep Learning Based Access Control) with robot task planning approaches (classical symbolic planning and end-to-end learning-based planning). We report pre-liminary results on their respective trade-offs and conclude that a hybrid approach will most likely be the method of choice.