F1Tenth Two-Agent Simulator is an open-source ROS-integrated environment for testing and benchmarking two autonomous racecar agents. It provides realistic 1/10th scale vehicle dynamics, customizable control stacks, real-time visualization, and logging support for multi-agent coordination and competition scenarios.
Promote this Tool
Update this Tool
F1Tenth Two-Agent Simulator
F1Tenth Two-Agent Simulator is an open-source ROS-integrated environment for testing and benchmarking two autonomous racecar agents. It provides realistic 1/10th scale vehicle dynamics, customizable control stacks, real-time visualization, and logging support for multi-agent coordination and competition scenarios.
Ads
What is F1Tenth Two-Agent Simulator?
The F1Tenth Two-Agent Simulator is a specialized simulation framework built on ROS and Gazebo to emulate two 1/10th scale autonomous vehicles racing or cooperating on custom tracks. It supports realistic tire-model physics, sensor emulation, collision detection, and data logging. Users can plug in their own planning and control algorithms, adjust agent parameters, and run head-to-head scenarios to evaluate performance, safety, and coordination strategies under controlled conditions.
Who will use F1Tenth Two-Agent Simulator?
- Autonomous driving researchers
- Robotics and control engineers
- Graduate students in robotics
- AI/ML algorithm developers
- University robotics course instructors
How to use the F1Tenth Two-Agent Simulator?
- Step1: Install ROS (Noetic or Melodic) and Gazebo on a Linux machine.
- Step2: Clone the repository: git clone https://github.com/JZ76/f1tenth_simulator_two_agents.git
- Step3: Build the workspace: catkin_make in the workspace root.
- Step4: Source the workspace: source devel/setup.bash.
- Step5: Launch the simulator: roslaunch f1tenth_simulator two_agents.launch.
- Step6: Configure agent controllers via ROS parameters or replace control nodes.
- Step7: Start training or evaluation routines and monitor in Rviz/Gazebo.
- Step8: Collect logs and analyze performance metrics.
Platform
- Linux
F1Tenth Two-Agent Simulator's Core Features & Benefits
The Core Features
- Dual-agent simulation in Gazebo
- ROS integration for sensor and control nodes
- Realistic vehicle dynamics and tire models
- Customizable planning and control interfaces
- Real-time 3D visualization and logging
The Benefits
- Rapid prototyping of multi-agent algorithms
- Benchmarking head-to-head racing strategies
- Open-source and extensible architecture
- Reproducible experiments with logging
- Educational tool for autonomous driving courses
F1Tenth Two-Agent Simulator's Main Use Cases & Applications
- Comparing collision avoidance algorithms in multi-agent scenarios
- Benchmarking reinforcement learning controllers for racing
- Teaching autonomous vehicle control in robotics courses
- Evaluating cooperative mapping and navigation strategies
- Testing real-time planning under dynamic track conditions
FAQs of F1Tenth Two-Agent Simulator
F1Tenth Two-Agent Simulator Company Information
F1Tenth Two-Agent Simulator Reviews
5/5
F1Tenth Two-Agent Simulator's Main Competitors and alternatives?
Carla Simulator
LGSVL Simulator
Microsoft AirSim
TORCS
Gazebo multi-robot racing setups
You may also like:
Run coding agents in a persistent cloud workspace with shared files, previews, team context, and no local setup required.
Diagrid keeps AI agent workflows running through crashes, preserves state, and cryptographically proves every completed execution step.
Run coding agents locally with swappable models, tools, sandboxes, and session logs through a TypeScript plugin runtime.
Loopa is an AI agent platform that automates research, content creation, analysis, and workflow execution.
An autonomous AI agent that executes long tasks across apps, websites, and cloud computers end to end.
Hosted OpenClaw agent: one-click deploy, 500+ models, secure infrastructure, and automated agent management for teams and developers.
Enterprise-ready agent runtime that unifies Discord, web, and terminal with secure RAG, memory, and tool execution.
OpenClaw is an open-source, locally-run personal AI assistant that automates tasks via chat apps and plugins.
Managed Openclaw workspace to deploy local-first AI agents, hire AI staff, and join the Moltbook ecosystem.
CoTester is an enterprise-grade AI testing agent that reliably generates, runs, and self-heals automated tests.
Conversational AI assistant automating research, browser tasks, web scraping, and file management through natural language.
Gobii lets teams create 24/7 autonomous digital workers to automate web research and routine tasks.
AI design agent automates workflow creating images, videos, 3D models up to 10x faster.
SJinn is an AI-powered agent creating image, video, audio, and 3D content from descriptions.
Eigent is an open-source AI workforce platform managing complex workflows via multi-agent collaboration.
NVIDIA Omniverse Audio2Face transforms 3D character animations with AI-driven facial and emotional expressions.