{"title":"虚拟现实狩猎中自主动物的集体智慧","authors":"Kangqiao Zhao, F. Lin, S. H. Soon","doi":"10.1109/VRW52623.2021.00010","DOIUrl":null,"url":null,"abstract":"In the scenario of a VR hunting game, autonomous behaviour of in-game animals is essential. In this study, new adaptive steering algorithms are designed for autonomous animals to navigate around the environment, with a research focus on collective intelligence in decision making and tactical actions. Advanced strategies for a group of autonomous animals are developed in order to simulate a more realistic forest environment. Computational experiments and comparisons with animation results are presented, accompanied by a demo video, which show significant advantages over previous work. The new models and algorithms can also be used for autonomous motion controls for other XR-based training.","PeriodicalId":256204,"journal":{"name":"2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Collective Intelligence of Autonomous Animals in VR Hunting\",\"authors\":\"Kangqiao Zhao, F. Lin, S. H. Soon\",\"doi\":\"10.1109/VRW52623.2021.00010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the scenario of a VR hunting game, autonomous behaviour of in-game animals is essential. In this study, new adaptive steering algorithms are designed for autonomous animals to navigate around the environment, with a research focus on collective intelligence in decision making and tactical actions. Advanced strategies for a group of autonomous animals are developed in order to simulate a more realistic forest environment. Computational experiments and comparisons with animation results are presented, accompanied by a demo video, which show significant advantages over previous work. The new models and algorithms can also be used for autonomous motion controls for other XR-based training.\",\"PeriodicalId\":256204,\"journal\":{\"name\":\"2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VRW52623.2021.00010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VRW52623.2021.00010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Collective Intelligence of Autonomous Animals in VR Hunting
In the scenario of a VR hunting game, autonomous behaviour of in-game animals is essential. In this study, new adaptive steering algorithms are designed for autonomous animals to navigate around the environment, with a research focus on collective intelligence in decision making and tactical actions. Advanced strategies for a group of autonomous animals are developed in order to simulate a more realistic forest environment. Computational experiments and comparisons with animation results are presented, accompanied by a demo video, which show significant advantages over previous work. The new models and algorithms can also be used for autonomous motion controls for other XR-based training.