Yunlong Wu, Jinghua Li, Haoxiang Jin, Jiexin Zhang, Yanzhen Wang
{"title":"RBT-HCI: A Reliable Behavior Tree Planning Method with Human-Computer Interaction","authors":"Yunlong Wu, Jinghua Li, Haoxiang Jin, Jiexin Zhang, Yanzhen Wang","doi":"10.1109/ROBIO55434.2022.10011651","DOIUrl":null,"url":null,"abstract":"In this paper, we propose RBT-HCI, a reliable behavior tree (BT) planning method with human-computer interaction, aiming at generating an interpretable and human-acceptable BT. Compared with other BT generation methods, RBT-HCI can reliably plan a BT based on the knowledge base. When an available BT cannot be planned automatically, instead of terminating or relaxing the rules, RBT-HCI provides a new idea, which is to make decisions through human-computer interaction, thereby enhancing the reliability and robustness of the method. The effectiveness of RBT-HCI is verified by an example of robot grasping objects, showing that a reliable and robust planning result can be obtained through knowledge-based automatic planning and human-computer interaction.","PeriodicalId":151112,"journal":{"name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO55434.2022.10011651","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
In this paper, we propose RBT-HCI, a reliable behavior tree (BT) planning method with human-computer interaction, aiming at generating an interpretable and human-acceptable BT. Compared with other BT generation methods, RBT-HCI can reliably plan a BT based on the knowledge base. When an available BT cannot be planned automatically, instead of terminating or relaxing the rules, RBT-HCI provides a new idea, which is to make decisions through human-computer interaction, thereby enhancing the reliability and robustness of the method. The effectiveness of RBT-HCI is verified by an example of robot grasping objects, showing that a reliable and robust planning result can be obtained through knowledge-based automatic planning and human-computer interaction.