Connects LLMs to Eclipse SUMO traffic simulation, enabling AI agents to automate traffic network generation, demand modeling, signal optimization, simulation execution, and real-time TraCI control through natural language.
Enables interactive design, execution, and analysis of SUMO traffic simulations through natural language, providing tools for scenario generation, policy experimentation, result analysis, and visualization.
Integrates SUMO traffic simulation with the Model Context Protocol for autonomous driving applications, enabling simulation environment interaction and model context management.
Universal bridge between AI agents and Autoware autonomous driving stack, enabling AI-driven mission planning, real-time vehicle control, and adaptive decision-making.
Enables AI interaction with embodied humans, autonomous vehicles, and drones through the HUTB simulator. Supports voice/chat control, weather conditions, perspective switching, and recording features.
Enables AI agents to automate COMSOL Multiphysics simulations, including model management, geometry building, physics configuration, meshing, solving, and results visualization through the MCP protocol.
