Wu P.-TYu C.-AChan S.-HChiang M.-LLI-CHEN FU2021-09-022021-09-02201921530858https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081163020&doi=10.1109%2fIROS40897.2019.8968455&partnerID=40&md5=f35f777ff85c7763e3aa6213852aa959https://scholars.lib.ntu.edu.tw/handle/123456789/581386In this paper, we propose a novel system architecture called multi-layer environmental affordance map for social and service companion robots. Based on this architecture, robots can organize the perception and inference information efficiently and generate social friendly navigation strategies. In other words, robots are able to strengthen their perception and inference abilities to interact with domestic environment and users under our efficient framework. The main feature of this architecture is that the relations between layers can be viewed as affordances to improve the accuracy and the robustness of the detection and inference. The results show that our architecture achieves robust indoor localization, scene localization, human event detection and socially friendly navigation in real time under limited computational resource. ? 2019 IEEE.Architecture; Intelligent robots; Navigation; Social robots; Affordances; Companion robot; Computational resources; Domestic environments; Event detection; Indoor localization; Navigation strategies; System architectures; Indoor positioning systems[SDGs]SDG11conference paper10.1109/IROS40897.2019.89684552-s2.0-85081163020