IEEE Virtual Reality（IEEE VR）2020会议于3月22日—26日召开。我院计算机软件研究所董天阳教授、范菁教授，以及研究生陈贤威、宋一凡、应文渊在虚拟现实方向的论文《Dynamic Artificial Potential Fields for Multi-User Redirected Walking》在会上发表并进行了口头报告，这是我校首次作为第一完成单位在IEEE VR会议上发表长文论文。

为用户提供逼真的无限空间感知和虚拟环境的自然行走功能是当前虚拟现实技术研究的热点之一。为了解决共享同一物理空间多用户漫游的碰撞问题，该论文在动态人工势场构建方法研究的基础上，提出了一种面向大规模虚拟场景漫游的多用户重定向行走方法。该方法能够产生排斥力将用户“推离”障碍物和其他用户，并利用吸引力将用户“吸引”到无障碍的物理空间，有助于增强用户的VR体验。

IEEE VR会议创始于1993年，是国际虚拟现实领域的顶级会议，也是中国计算机学会发布的《CCF推荐国际学术会议和期刊目录》中“计算机图形学与多媒体”领域的A类会议。IEEE VR 2020会议的长文录取率约为21%。今年的IEEE VR会议以线上VR方式召开，在VR平台上支持听众与讲者、听众与听众之间的互动。

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题目：Dynamic Artificial Potential Fields for Multi-User Redirected Walking

作者：Tianyang Dong  Xianwei Chen   Yifan Song   Wenyuan Ying   Jing Fan

摘要：

Immersive Virtual Reality (VR) systems that combine Head Mounted Displays (HMDs) and a position tracking system support the multiple users or participants to collaborate in the same physical space for a large-scale virtual environment. Because the multiple users sharing the same physical space are in a dynamic state, the key technique of multi-user VR system is how to solve the problem of potential collisions among the users who are moving both virtually and physically. In order to solve the collision problem caused by such dynamic changes, this work presents a new strategy of multi-user redirected walking using dynamic artificial potential fields, which generates repulsion to ‘push’ users away from obstacles and other users, and uses gravity to ‘attract’ users to an open or unobstructed space. In this method, the users not only get repulsive forces from walls, but also from other users and their future states that are called avatars. At the same time, the users will get gravitational force from the steering target. The target selection considers the size of open space, the distance between the steering target and the boundary of physical space, and the distance between the steering target and the center of the physical space. Therefore, the system can steer users to an open area in the physical space to further reduce collisions. To verify the validity of our method, we developed a software to statistically analyze the influence of different factors, such as the physical space size and the number of users. Data from experiments shows that our method reduces the potential user resets by about 20%.