DART (Dynamic Animation and Robotics Toolkit) is an open-source, research-focused physics engine for robotics, animation, and machine learning. It provides transparent kinematics, dynamics, collision, and constraint-solving foundations for users who need more than a black-box simulator. DART uses generalized coordinates for articulated rigid body systems and Featherstone's Articulated Body Algorithm for accurate, stable motion dynamics.

• Research-grade dynamics — Featherstone algorithms, generalized coordinates, and direct access to dynamics quantities
• Easy to start — Python and C++ packages through common package managers, plus reproducible source builds with pixi
• Extensible foundations — Math, collision, constraints, model loading, benchmarks, and tests that support new algorithms and baseline comparisons
• Unified model loading — Load URDF, SDF, MJCF, and SKEL models through a single API
• Scalable compute roadmap — Cross-platform CPU support today, with roadmap work for multi-core, SIMD, and accelerator backends
• Battle-tested ecosystem — Powers Gazebo, research labs, and production systems worldwide, with best-effort support for production use

Python

import dartpy as dart

world = dart.World()

# Load a robot from URDF
urdf = dart.io.UrdfParser()
robot = urdf.parseSkeleton("dart://sample/urdf/KR5/KR5 sixx R650.urdf")
world.addSkeleton(robot)

# Simulate 100 steps
for _ in range(100):
    world.step()
    print(f"Positions: {robot.getPositions()}")

C++

#include <dart/dart.hpp>

int main() {
  auto world = dart::simulation::World::create();

  // Load a robot from URDF
  auto robot = dart::io::urdf::readSkeleton("path/to/robot.urdf");
  world->addSkeleton(robot);

  // Simulate 100 steps
  for (int i = 0; i < 100; ++i) {
    world->step();
    std::cout << "Positions: " << robot->getPositions().transpose() << "\n";
  }
  return 0;
}

All distributions →

• Static Docs: English | 한국어
• AI Docs (interactive Q&A; experimental): DeepWiki | NotebookLM (Google account required)

• Developer Onboarding Guide — Architecture, components, and workflows
• Contributing Guide — Style guide and contribution process
• Project Direction — Research-focused north star and priorities
• Living Plans — Active and proposed roadmap items
• Background Theory — Dynamics, contact solving, and mathematical foundations
• Gazebo Integration — gz-physics integration workflow
• Release Roadmap — Compatibility, deprecations, and future plans

• main — Active development targeting DART 7
• release-6.16 — Maintenance branch for DART 6 (critical fixes only)

If you use DART in an academic publication, please consider citing this JOSS Paper:

@article{Lee2018,
  doi = {10.21105/joss.00500},
  url = {https://doi.org/10.21105/joss.00500},
  year = {2018},
  publisher = {The Open Journal},
  volume = {3},
  number = {22},
  pages = {500},
  author = {Jeongseok Lee and Michael X. Grey and Sehoon Ha and Tobias Kunz and Sumit Jain and Yuting Ye and Siddhartha S. Srinivasa and Mike Stilman and C. Karen Liu},
  title = {DART: Dynamic Animation and Robotics Toolkit},
  journal = {Journal of Open Source Software}
}

DART is licensed under the BSD 2-Clause License.