Unified motion planner for fishes with various swimming styles

We propose a unified motion planner that reproduces variations in swimming styles based on the differences in the fish skeletal structures or the variations in the swimming styles based on changes in environmental conditions. The key idea in our method, based on biology, is the following. We considered the common decision-making mechanism in fish that allows them to instantly decide "where and how to swim." The unified motion planner comprises two stages. In the first stage, where to swim to is decided. Using a probability distribution generated by integrating the perceptual information, the short-term target position and target speed are decided. In the second stage, how to swim is decided. A style of swimming that matches the information for transitioning from the current speed to the target speed is selected. Using the proposed method, we demonstrate 12 types of CG models with completely different sizes and skeletal structures, such as manta ray, tuna, and boxfish, as well as a scene where a school of a few thousand fish swim realistically. Our method is easy to integrate into existing graphics pipelines. In addition, in our method, the movement characteristics can easily be changed by adjusting the parameters. The method also has a feature where the expression of an entire school of fish, such as tornado or circling, can be designated top-down.