This paper investigates the use of Reinforcement Learning (RL) to train an Artificial Intelligence (AI) humanoid opponent to play a Virtual Reality (VR) table tennis game. A self-play RL algorithm is implemented to train an AI opponent through competing against itself in Unity environment. The simulation environment replicates key physics of table tennis, and the agent controls racket movements to hit the ball. Experimental result indicates that the agent progressively enhances its table tennis skills according to rising ELO rating and optimization of aggressive gameplay strategies. This research provides a valuable framework for utilizing RL to overcome limitations of scripted AI opponents in physics-based sports games. RL opens new possibilities for human-like AI that can provide dynamic and adaptive experiences in VR games.
We present a pilot study on expressive B-spline curves (XBSC), an extension of disk B-spline curves (DBSC). XBSC facilitates expressive drawings in terms of shape and color. For shape, colors on both sides of XBSC strokes are defined independently instead of using a single parameter for both sides as in DBSC. We perform coloring by considering the envelopes of XBSC as diffusion curves. Our results show that XBSC can be used to easily draw a wide range of images with fewer number of primitives compared to previous methods.
The goal of this VR system is to simulate a bowling game for adaption in muscular rehabilitation training. The virtual environment allows the user to pick up a bowling ball and hit the pins, followed by an update and display of the score they gained; and the players can alternate between each other to have a competition. Implemented on the Unity engine and SteamVR, the VR Toolkit is employed in modeling and script development. Technical innovations are made in generation of the grabbing and releasing controllers with adjustable colliders, and the respawn detector triggered when the ball hits the back of the bowling alley in the game. We present the specific tasks of muscular rehabilitation, conceptualization of VR techniques and the detailed implementation of the system.
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