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CENIC: Convex Error-controlled Numerical Integration for Contact

arXiv2 min read

arXiv:2511.08771v2 Announce Type: replace Abstract: State-of-the-art robotics simulators operate in discrete time. This requires users to choose a time step, which is both critical and challenging: large steps can produce non-physical artifacts, while small steps force the simulation to run slowly. Continuous-time error-controlled integration avoids such issues by automatically adjusting the time step to achieve a desired accuracy. But existing error-controlled integrators struggle with the stiff dynamics of contact, and cannot meet the speed and scalability requirements of modern robotics workflows. We introduce CENIC, a new variable-step integrator that brings together recent advances in convex time-stepping and error-controlled integration, inheriting benefits from both continuous integration and discrete time-stepping. CENIC runs at fast real-time rates comparable to discrete-time robotics simulators like MuJoCo, Drake and Isaac Sim, while also providing guarantees on accuracy and convergence.

Abstract:State-of-the-art robotics simulators operate in discrete time. This requires users to choose a time step, which is both critical and challenging: large steps can produce non-physical artifacts, while small steps force the simulation to run slowly. Continuous-time error-controlled integration avoids such issues by automatically adjusting the time step to achieve a desired accuracy. But existing error-controlled integrators struggle with the stiff dynamics of contact, and cannot meet the speed and scalability requirements of modern robotics workflows. We introduce CENIC, a new variable-step integrator that brings together recent advances in convex time-stepping and error-controlled integration, inheriting benefits from both continuous integration and discrete time-stepping. CENIC runs at fast real-time rates comparable to discrete-time robotics simulators like MuJoCo, Drake and Isaac Sim, while also providing guarantees on accuracy and convergence.

20 pages with 20 figures. Submitted to IEEE Transactions on Robotics (T-RO). The supplemental video is available publicly at this https URL

Robotics (cs.RO); Computational Engineering, Finance, and Science (cs.CE); Computational Physics (physics.comp-ph)

arXiv:2511.08771 [cs.RO]

(or arXiv:2511.08771v2 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2511.08771 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 250 words