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.
AI Platforms & Frameworks
Development Environment
#autonomous vehicles
#robotics simulation
#Gazebo simulator
#ROS-Integration
#vehicle dynamics
#multi-agent systems
#racing strategies
#Educational tools
#algorithm prototyping
#Real-time Visualization
#Data Logging
#collision detection
#custom tracks
#control algorithms
#realistic physics
#head-to-head racing
#Sensor-Emulation
#open-source software
#performance evaluation
...
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.
AI Platforms & Frameworks
Development Environment
#autonomous vehicles
#robotics simulation
#Gazebo simulator
#ROS-Integration
#vehicle dynamics
#multi-agent systems
#racing strategies
#Educational tools
#algorithm prototyping
#Real-time Visualization
#Data Logging
#collision detection
#custom tracks
#control algorithms
#realistic physics
#head-to-head racing
#Sensor-Emulation
#open-source software
#performance evaluation
...
Featured
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:
AI design agent automates workflow creating images, videos, 3D models up to 10x faster.
AI-driven chatbot for top OnlyFans creators.
Aixbt is a tokenized AI Agent optimizing revenue across applications.
theGist AI Workspace unifies work apps with AI for improved productivity.
Generate brand visuals and copy using AI to boost e-commerce sales.
GPTConsole is an AI agent designed for streamlined conversation and task automation.
GenSphere is an AI agent that automates data analysis and provides insights for informed decision-making.
Nullify automates the entire AppSec program for security teams using AI-driven solutions.
Refly.AI empowers non-technical creators to automate workflows using natural language and a visual canvas.
Langbase is an AI agent that generates and analyzes natural language content efficiently.
AiTerm: AI Terminal Assistant converting natural language to commands.
Generate intriguing facts effortlessly with our AI-powered tool.
Automate your job applications and find the perfect job with AI technology.
Intellika AI enables seamless automation of data analysis and reporting for businesses.
ScholarRoll helps students find and apply for scholarships easily.
OneReach AI simplifies interactions by automating customer engagement through intelligent messaging.
Phoenix AI Assistant helps streamline tasks using intelligent automation and personalized support.
Flowith is a canvas-based agentic workspace which offers free 🍌Nano Banana Pro and other effective models...
Letta is an AI agent that handles email responses efficiently and accurately.
Windsurf AI Agent helps optimize windsurfing conditions and gear recommendations.
Cody AI helps developers write, review, and understand code efficiently.
A solution for building customizable AI agents with LangChain on AWS Bedrock, leveraging foundation models and custom tools.
scenario-go is a Go SDK for defining complex LLM-driven conversational workflows, managing prompts, context, and multi-step AI tasks.
A ROS-based framework for multi-robot collaboration enabling autonomous task allocation, planning, and coordinated mission execution in teams.
An open-source visual IDE enabling AI engineers to build, test, and deploy agentic workflows 10x faster.
LangGraph Learn offers an interactive GUI to design and execute graph-based AI agent workflows, visualizing language model chains.
AIDE provides AI-powered code generation, debugging, documentation and package management within an integrated web IDE.
A methodology offering twelve best practices to design, configure, and deploy scalable, maintainable AI Agents.
A Python framework for constructing multi-step reasoning pipelines and agent-like workflows with large language models.
SARL is an agent-oriented programming language and runtime providing event-driven behaviors and environment simulation for multi-agent systems.
AI Library is a developer platform for building and deploying customizable AI agents using modular chains and tools.
RModel is an open-source AI agent framework orchestrating LLMs, tool integration, and memory for advanced conversational and task-driven applications.
Provides a FastAPI backend for visual graph-based orchestration and execution of language model workflows in LangGraph GUI.
CodeBeaver is an AI agent that assists in coding and debugging tasks efficiently.
AveHR is an AI-driven human resources agent for streamlining HR tasks.
OpenSpiel provides a library of environments and algorithms for research in reinforcement learning and game theoretic planning.
An autonomous AI agent that writes, tests, and refactors code projects using LLMs with iterative test-driven development.
All-in-one AI video creation studio that turns any text and images into full videos up to 30 minutes.