Building 2D skeletal animation for body control in unity with machine learning

Machine learning has emerged as a popular technique for generating realistic animations in the video game industry. This paper aims to explore the application of machine learning in creating 2D skeletal animation for body control in Unity. The goal is to develop a model that can accurately predict the movements of the character's skeleton based on input parameters. To achieve this, the approach involves collecting a dataset of motion capture data, selecting an appropriate machine learning algorithm, creating an animation environment in Unity, training the machine learning model, and testing its accuracy. Each step is described in detail, along with an evaluation of the effectiveness of the method. Overall, the paper presents a promising approach to improve the efficiency and realism of 2D skeletal animation in video games.