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multi-robot

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VectorizedMultiAgentSimulator

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

  • Updated May 19, 2026
  • Python

One CLI for all your robots. Connect them, command them, and let them work together, each with an LLM for a brain (Claude, OpenAI, Gemini, Grok, or local via Ollama or vLLM), VLAs for arms and decision LLMs (Jev, Laya, Kev). Drives Microduck, Open Duck Mini, LeRobot, XLeRobot, AlohaMini, ToddlerBot, or any ROS 2 base from a laptop, offboard.

  • Updated Oct 16, 2026
  • Python

This project shows the area division process in Multi-Agent exploration using Cyclic Gradient Descent and also how Cooperative Perceptional Messages are used in V2V communication to share information among agents in about the environment.

  • Updated Dec 31, 2020
  • Python

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