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Overview

MVSim simulates wheeled robots and vehicles with realistic physics, sensors, and multi-agent support. It is designed to be fast enough for large-scale experiments while remaining accurate enough for dynamics and sensor research.

Key properties:

• Fully configured via XML world files — no code changes needed for most experiments.
• Works standalone, as a ROS 2 node, or embedded in a C++ / Python application.
• Headless mode for CI pipelines and Docker containers.
• Multi-vehicle worlds with mutual sensing (robots see each other in LiDAR).

https://github.com/user-attachments/assets/766db164-2d16-44f4-acbf-2f15b73c1ab3

https://github.com/user-attachments/assets/93c95aeb-71e9-4c35-b1dc-ba895c79daf7

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Features

Vehicle dynamics

Model	Description
differential	2-wheel or 4-wheel differential drive (e.g. TurtleBot, Jackal)
ackermann	Car-like Ackermann steering with kinematic or dynamic control
ackermann_drivetrain	Ackermann + realistic mechanical differentials (open / Torsen, 2WD / 4WD)
Articulated	Trailer-style articulated vehicles

Controllers available: raw torque, twist PID, ideal twist.

Friction models: default Coulomb, Ward-Iagnemma (off-road), ellipse (slip angle + slip ratio).

Sensors

Sensor	Notes
3D LiDARs	Velodyne VLP-16, Ouster OS1, Hesai Helios-32 (26°/31°/70° FOV)
2D LiDAR	Generic + RPLidar A2; optional GPU-based 3D ray-tracing
RGB camera	Pinhole model, configurable intrinsics
RGBD camera	Depth + color (RealSense / Xtion-style), publishes pointcloud, depth image
IMU	White noise + bias random-walk (Forster 2016 model)
GNSS / GPS	Requires georeferenced world; configurable noise

World elements

• Occupancy grid maps (image or MRPT binary)
• Elevation meshes (terrain with height)
• Textured 3D blocks and custom meshes (.dae, .obj)
• Friction zones (spatially-varying mu, rolling resistance)
• Multi-storey environments
• Lighting configuration
• Remote resource caching

Interfaces

• ROS 2 — full topic / TF / parameter interface (see mvsim_node docs)
• ZMQ / Protobuf — language-agnostic pub/sub for custom clients
• Python — direct API access
• C++ library — embed the simulator in your application

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Installation

ROS 2 (recommended)

sudo apt install ros-$ROS_DISTRO-mvsim

Then follow the first-steps guide.

Build from source

git clone https://github.com/MRPT/mvsim.git --recursive

See full installation instructions for cmake and colcon build options.

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Quick start

Standalone:

mvsim launch mvsim_tutorial/demo_warehouse.world.xml
mvsim launch mvsim_tutorial/demo_2robots.world.xml
mvsim launch mvsim_tutorial/demo_greenhouse.world.xml

ROS 2:

ros2 launch mvsim demo_warehouse.launch.py
ros2 launch mvsim demo_depth_camera.launch.py

Move the robot with w/a/s/d (keyboard) or any standard cmd_vel publisher. In multi-robot worlds, press 1, 2, … to select the active robot.

See all demo worlds for the full list, including outdoor, road circuits, multi-storey, logistics center, articulated vehicles, and more.

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ROS 2 build status

Distro	Dev build	Binary releases	Version
Humble (u22.04)		amd64 arm64
Jazzy (u24.04)		amd64 arm64
Kilted (u24.04)		amd64 arm64
Rolling (u24.04)		amd64 arm64

EOL distros

Distro	Last stable version
ROS 1 Noetic (u20.04)
ROS 2 Iron (u22.04)

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ROSCon talk

Spanish talk with English slides and subtitles (slides):

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Citation

If you use MVSim in your research, please cite:

@article{blanco2023mvsim,
  title   = {MultiVehicle Simulator (MVSim): Lightweight dynamics simulator for multiagents and mobile robotics research},
  journal = {SoftwareX},
  volume  = {23},
  pages   = {101443},
  year    = {2023},
  doi     = {10.1016/j.softx.2023.101443},
  url     = {https://www.sciencedirect.com/science/article/pii/S2352711023001395},
  author  = {José-Luis Blanco-Claraco and Borys Tymchenko and Francisco José Mañas-Alvarez and Fernando Cañadas-Aránega and Ángel López-Gázquez and José Carlos Moreno}
}

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License

3-clause BSD License. Copyright (C) 2014-2026 Jose Luis Blanco (University of Almeria) and contributors.