The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX
Abstract
There is growing need for software tools that can accurately simulate the complex dynamics of modern robots. While a number of candidates exist, the field is fragmented. It is difficult to select the best tool for a given project, or to predict how much effort will be needed and what the ultimate simulation performance will be. Here we introduce new quantitative measures of simulation performance, focusing on the numerical challenges that are typical for robotics as opposed to multi-body dynamics and gaming. We then present extensive simulation results, obtained within a new software framework for instantiating the same model in multiple engines and running side-by-side comparisons. Overall we find that each engine performs best on the type of system it was designed and optimized for: MuJoCo wins the robotics-related tests, while the gaming engines win the gaming-related tests without a clear leader among them. The simulations are illustrated in the accompanying movie.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Rigid Body Dynamics Algorithms
Featherstone, R. (2008) · Springer eBooks · doi:10.1007/978-1-4899-7560-7 · Cited by 1,376
Corke, P. I. (1996) · IEEE Robotics & Automation Magazine · doi:10.1109/100.486658 · Cited by 842
STEWART, D. E., & TRINKLE, J. C. (1996) · International Journal for Numerical Methods in Engineering · doi:10.1002/(sici)1097-0207(19960815)39:15<2673::aid-nme972>3.0.co;2-i · Cited by 636
Anitescu, M., & Potra, F. A. (1997) · Nonlinear Dynamics · doi:10.1023/a:1008292328909 · Cited by 491
SIMBICON: simple biped locomotion control
Yin, K., Loken, K., & van de Panne, M. (2007) · ACM Transactions on Graphics · doi:10.1145/1276377.1276509 · Cited by 337
SIMBICON: simple biped locomotion control
Yin, K., Loken, K., & van de Panne, M. (2007) · ACM SIGGRAPH 2007 papers · doi:10.1145/1275808.1276509 · Cited by 328
Staggered projections for frictional contact in multibody systems
Kaufman, D. M., Sueda, S., James, D. L., & Pai, D. K. (2008) · ACM Transactions on Graphics · doi:10.1145/1409060.1409117 · Cited by 182
Todorov, E. V. (2014) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2014.6907751 · Cited by 138
Self-citationOptimization-based simulation of nonsmooth rigid multibody dynamics
Anitescu, M. (2005) · Mathematical Programming · doi:10.1007/s10107-005-0590-7 · Cited by 125
Staggered projections for frictional contact in multibody systems
Kaufman, D. M., Sueda, S., James, D. L., & Pai, D. K. (2008) · ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH Asia) · doi:10.1145/1457515.1409117 · Cited by 65
Cited by
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Rajeswaran, A., Kumar, V., Gupta, A., Vezzani, G., Schulman, J., Todorov, E., & Levine, S. (2018) · Robotics: Science and Systems XIV · doi:10.15607/rss.2018.xiv.049 · Cited by 847
Self-citationA Differentiable Physics Engine for Deep Learning in Robotics
Degrave, J., Hermans, M., Dambre, J., & wyffels, F. (2019) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2019.00006 · Cited by 182
Robot Learning From Randomized Simulations: A Review
Muratore, F., Ramos, F., Turk, G., Yu, W., Gienger, M., & Peters, J. (2022) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.799893 · Cited by 128
MuJoCo HAPTIX: A virtual reality system for hand manipulation
Kumar, V., & Todorov, E. (2015) · 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids.2015.7363441 · Cited by 102
Self-citationThe neuromechanics of animal locomotion: From biology to robotics and back
Ramdya, P., & Ijspeert, A. J. (2023) · Science Robotics · doi:10.1126/scirobotics.adg0279 · Cited by 92
Metadata
- Authors
- Erez, T., Tassa, Y., & Todorov, E.
- Venue
- 2015 IEEE International Conference on Robotics and Automation (ICRA)
- Publisher
- IEEE
- Published
- 2015-05
- Pages
- 4397-4404
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W1570792896
- Cited by
- 312
- References
- 13
- FWCI
- 24.86
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX. https://app.cochat.ai/papers/10.1109/icra.2015.7139807
- The paper
- Erez, T., Tassa, Y., & Todorov, E. (2015). Simulation tools for model-based robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX. 2015 IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/icra.2015.7139807
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
