Intuitive motion control is essential for virtual reality, allowing users to manipulate objects naturally while receiving realistic and responsive visual feedback. 3D Gaussian splatting provides real-time, photorealistic scene rendering, making it promising for virtual reality applications. Still, it falls short in accurate motion control of dynamic objects due to its unstructured global motion representation and redundant motion learning. To address these problems, we propose a motion hierarchical Gaussian based dynamic control method. First, a motion hierarchical Gaussian representation is introduced and initialized with semantic and deformation information. Then a motion hierarchical decomposition method is proposed to optimize the local motion in the representation. The representation is next optimized by a local motion analysis based refinement method. We also design a set of motion control operations for the motion hierarchical Gaussian. Experimental results show that our method achieves high-precision motion reconstruction, accurate motion decomposition, real-time, intuitively and immersive VR motion control.

Group navigation is a virtual reality (VR) technology designed to replace personal navigation, enhancing efficiency and aiding guided tours in path planning for other users. Group navigation techniques require users to have a clear understanding of navigation and travel modalities. Tour guides must ensure that users do not intersect with the environment or other users' models and must provide reasonable tour formations. To address these needs, we propose a scene-aware automatic formation generation method for fast and easy-to-use guided tours. First, we generate a limited number of candidate points for the exhibition and initialize the visiting group formation. Next, we optimize the formation to maximize view quality using our proposed viewpoint observation score. Finally, we match the visitors to the optimized formation to ensure a minimal view deflection angle. Moreover, we conducted a user study to evaluate the performance of our approach. Compared to the current method, our approach significantly increased navigation efficiency and view quality. Additionally, it substantially decreased the task load and improved the system usability for both tour guides and visitors.