用强化学习动态优化混合现实中的3D界面位置。
Adaptive 3D UI Placement in Mixed Reality Using Deep Reinforcement Learning
- 基于用户姿态和环境的强化学习自动调整虚拟界面位置。
- 实验表明该方法能持续提升用户任务表现的奖励值。
- 适合研究个性化交互与智能界面部署的学者参考。
混合现实（MR）可通过将虚拟内容持续融合到用户的物理环境视图中来辅助任务。然而，由于MR体验具有动态性，如何最佳地放置这些内容始终是一个挑战。与以往研究优化方法不同，本文探索强化学习（RL）在感知用户姿态及周围环境的前提下，实现连续的3D内容定位。通过初步探索与评估，结果表明RL能够有效定位内容以最大化用户在移动中的奖励。同时，本文指出了未来研究方向，旨在利用强化学习实现MR中个性化的最优界面与内容布局。
原文摘要 · Abstract (English)
Mixed Reality (MR) could assist users' tasks by continuously integrating virtual content with their view of the physical environment. However, where and how to place these content to best support the users has been a challenging problem due to the dynamic nature of MR experiences. In contrast to prior work that investigates optimization-based methods, we are exploring how reinforcement learning (RL) could assist with continuous 3D content placement that is aware of users' poses and their surrounding environments. Through an initial exploration and preliminary evaluation, our results demonstrate the potential of RL to position content that maximizes the reward for users on the go. We further identify future directions for research that could harness the power of RL for personalized and optimized UI and content placement in MR.
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