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Large-scale simulation with realistic nonlinear dynamic models is crucial foralgorithms development for swarm robotics. However, existing platforms aremainly developed based on Object-Oriented Programming (OOP) and either usesimple kinematic models to pursue a large number of simulating nodes orimplement realistic dynamic models with limited simulating nodes. In thispaper, we develop a simulator based on Data-Oriented Programming (DOP) thatutilizes GPU parallel computing to achieve large-scale swarm roboticsimulations. Specifically, we use a multi-process approach to simulateheterogeneous agents and leverage PyTorch with GPU to simulate homogeneousagents with a large number. We test our approach using a nonlinear quadrotormodel and demonstrate that this DOP approach can maintain almost the samecomputational speed when quadrotors are less than 5,000. We also provide twoexamples to present the functionality of the platform.

Potato: A Data-Oriented Programming 3D Simulator for Large-Scale Heterogeneous Swarm Robotics