MotrixSim Embodied Intelligence Simulation PlatformEvolution Beyond Physics
Utilize high-performance and high-precision simulation technology to promote seamless integration between virtual and real worlds, enhancing design, testing, and optimization efficiency in multiple industries.
Why Choose MotrixSim
The key to solving the Sim2Real problem lies in making physical simulation algorithms more aligned with the real world. MotrixSim addresses this by leveraging a proprietary high-performance physics engine, optimized across several critical areas to minimize the gap between simulation and reality.
Physics Algorithms Better Reflect the Real World
Newton’s Cradle Simulation
Gravity Gyro Simulation
Massive Static Contact Evaluation
Algorithm Remains Robust Under Large Time Steps
Stable Simulation Even At 10ms Time Step
A stable algorithm under large time steps enables the simulation to proceed with fewer calculations per second by increasing the time interval. This not only accelerates simulation speed but also reduces computational load, which is particularly beneficial for real-time and large-scale simulation performance.
Seamlessly Connecting Simulation to Deployment
Towards Seamless Sim2Real Transfer
Leveraging a series of enhancements in our proprietary physics engine, we successfully trained the Unitree Go1 in MotrixSim and deployed it directly to real machine for validation. Notably, no post-processing was applied in this locomotion task, achieving a preliminary stage of seamless transfer from virtual environments to the physical world. This result suggests that addressing the Sim2Real challenge heavily depends on continuous advancement in physical simulation algorithms.
Why Choose MotrixSim
The key to solving the Sim2Real problem lies in making physical simulation algorithms more aligned with the real world. MotrixSim addresses this by leveraging a proprietary high-performance physics engine, optimized across several critical areas to minimize the gap between simulation and reality.
Physics Algorithms Better Reflect the Real World
Newton’s Cradle Simulation
Newton’s Cradle is a device consisting of a series of equal-mass spheres suspended in a straight line. When one sphere is pulled back and released, it strikes the others, causing a sphere on the opposite end to swing outward—while conserving the total energy of the system. Correctly simulating Newton’s Cradle requires highly accurate energy conservation algorithms along with fine-tuned collision detection and response mechanisms.
Gravity Gyro Simulation
The precession and nutation simulation of a gravity gyro can evaluate the accuracy of a physics engine in contact point handling and angular momentum modeling. MotrixSim shows behavior highly consistent with theoretical predictions, while MuJoCo exhibits irregular displacement in the simulation. This precise reproduction of dynamics provides a reliable basis for Sim2Real system identification and optimization, significantly reducing tuning effort and iteration cycles during deployment.
Massive Static Contact Evaluation
A shelf scene with a large number of densely packed and statically contacting items can be used to evaluate the stability and accuracy of physics engines in dense contact modeling. MotrixSim shows stable performance in handling massive object contacts, while MuJoCo exhibits severe object jittering in this scenario. The high-precision simulation capability for large-scale static contact scenes provides reliable support for real-world applications such as warehouse logistics.
Algorithm Remains Robust Under Large Time Steps
Stable Simulation Even At 10ms Time Step
A stable algorithm under large time steps enables the simulation to proceed with fewer calculations per second by increasing the time interval. This not only accelerates simulation speed but also reduces computational load, which is particularly beneficial for real-time and large-scale simulation performance.
Seamlessly Connecting Simulation to Deployment
Towards Seamless Sim2Real Transfer
Leveraging a series of enhancements in our proprietary physics engine, we successfully trained the Unitree Go1 in MotrixSim and deployed it directly to real machine for validation. Notably, no post-processing was applied in this locomotion task, achieving a preliminary stage of seamless transfer from virtual environments to the physical world. This result suggests that addressing the Sim2Real challenge heavily depends on continuous advancement in physical simulation algorithms.
Key Features
MotrixSim provides high-performance and high-precision simulation technology, supporting generalized coordinates and multi-body physics modeling, and adopting implicit solvers to achieve more accurate drive models and superior dynamic stability.
Physics Simulation
Supports full rigid body dynamics simulation with inertia, friction, and high-precision collision detection for realistic real-time interactions in complex environments.
High-Performance Computing
The CPU version is built with Rust, delivering high performance and memory safety for stable and reliable simulation results.
Next-Generation Solver
The multibody dynamics solver uses improved constraint modeling and implicit integration for stable, efficient real-time simulation of high-DOF systems.
Generalized Coordinate Modeling
Utilizes generalized coordinate-based multibody system modeling, supporting complex topological structures with built-in joint constraints. Works well for systems like robots, arms, and vehicle suspensions.
Python API
Features a Python API that supports model creation, simulation control, and data interaction for rapid prototyping and development.
Robotics Support
Optimized robotics simulation with full compatibility for URDF/MJCF files, ideal for robotics algorithm development and scenario setup.
Getting Started with MotrixSim
Getting to Know MotrixSim
Explore the MotrixSim embodied intelligence simulation platform and watch typical cases that demonstrate its high precision, accuracy, and superior performance. MotrixSim has also collaborated with well-known robotic arm and robot manufacturers to create real-world application cases, providing you with practical references.
SDK Sample Project
MotrixSim provides examples to help users quickly get started, understand the core workflow of embodied intelligence simulation, and support algorithm validation and AI application research.
Documentation
Explore our documentation and let simulation drive innovation.
User Manual
API Documentation