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| Simbody | |
|---|---|
| Name | Simbody |
| Developer | Stanford University; Simbios; OpenSim |
| Released | 2008 |
| Programming language | C++ |
| Operating system | Linux; macOS; Windows |
| Genre | Multibody dynamics; biomechanical simulation |
| License | Apache License |
Simbody is an open-source multibody physics library designed for high-fidelity simulation of articulated bodies, muscles, and constraints. It provides a numerically robust engine used in biomechanics, robotics, and computer animation research at institutions such as Stanford University and projects like OpenSim. Simbody emphasizes accuracy, conservation properties, and extensibility for engineers and scientists working with dynamic systems.
Simbody is a software toolkit for solving the equations of motion for constrained multibody systems, supporting rigid bodies, mobilizers, forces, and kinematic constraints. It targets researchers and developers associated with organizations such as NIH, NASA, and DARPA who require precise dynamic simulation for projects comparable to work at MIT, Caltech, and ETH Zurich. The library integrates numerical methods influenced by classical studies from figures like Euler, Lagrange, and Gauss, and is implemented in C++ to interoperate with toolchains used at institutions including University of Cambridge and Imperial College London.
Development began in the mid-2000s within the Simbios center at Stanford University as part of federally funded efforts to model human movement in silico for biomedical research. Early collaborators included researchers affiliated with University of Pennsylvania, University of Florida, and University of Michigan. Contributions and maintenance have involved engineers who previously worked on projects at NASA Ames Research Center and laboratories inspired by methodologies developed at Carnegie Mellon University and Georgia Tech. The project evolved alongside related software such as OpenSim and drew on published algorithms from conferences like IEEE Conference on Robotics and Automation and ASME Dynamics symposia.
The architecture separates a high-level system model from low-level numerical integrators and solvers, following design patterns used at organizations like Google and Microsoft for modular software. Core components include the System and State abstractions, a MultibodyTree for bodies and joints, Force elements for springs and actuators, and Constraint solvers influenced by methods popularized in research at ETH Zurich and Max Planck Institute for Intelligent Systems. Numerical solvers borrow strategies similar to those discussed in literature from Society for Industrial and Applied Mathematics and algorithms comparable to solvers used by Intel and AMD in high-performance computing contexts.
Simbody supports holonomic and non-holonomic constraints, stabilized implicit time-stepping, analytical derivatives, and inverse dynamics routines used by researchers at Columbia University and University of California, Berkeley. It includes support for kinematic loops, contact modeling with compliant and rigid contact formulations akin to approaches evaluated at Oak Ridge National Laboratory and Lawrence Livermore National Laboratory, and muscle-actuated models informed by studies from Rehabilitation Research groups funded by NIH. The API exposes mechanisms for integrating with visualization frameworks used at University of Utah and real-time systems developed at Carnegie Mellon University.
Simbody is applied in diverse projects: musculoskeletal simulations for rehabilitation research pursued by groups at Stanford University and Harvard University; robot dynamics and control prototyping similar to work at Boston Dynamics and Honda Research Institute; biomechanical analyses in sports science labs like those at Australian Institute of Sport and Loughborough University; and character animation pipelines influenced by studios such as Industrial Light & Magic and Weta Digital. It underpins studies on prosthetic device design connected to efforts at Mayo Clinic and Cleveland Clinic, and is embedded in educational platforms used at Massachusetts Institute of Technology and University of Toronto.
Benchmarks demonstrate Simbody's efficiency on problems with many degrees of freedom, comparing favorably to alternative engines evaluated in papers presented at IEEE International Conference on Robotics and Automation and International Conference on Computer Vision. Performance analyses leverage multicore CPUs and vectorization techniques similar to optimizations used by NVIDIA and Intel for scientific codes. Comparative studies run on clusters like those at XSEDE and supercomputing centers such as Argonne National Laboratory illustrate trade-offs between implicit integrators and explicit methods reported by researchers at Princeton University and Cornell University.
Simbody is distributed under the Apache License to encourage reuse by academic groups, startups, and larger organizations including entities comparable to Siemens and Schneider Electric. Source code, prebuilt binaries, and bindings for languages used at institutions such as Imperial College London and University of Oxford are available through common code hosting workflows similar to those used by GitHub and GitLab. Community contributions are coordinated with governance patterns seen in projects like TensorFlow and The Linux Foundation.
Category:Computational physics software