RSLCPP -- Deterministic Simulations Using ROS 2
RSLCPP -- Deterministic Simulations Using ROS 2
This paper introduces RSLCPP (ROS Simulation Library for C++), an open-source methodology to achieve deterministic simulations in ROS 2. The authors address reproducibility issues caused by asynchronous, multi-process designs in standard ROS implementations. By ensuring consistent callback execution despite varying computation times and communication delays, RSLCPP allows existing nodes to be combined into simulation routines that yield identical results across different CPUs and architectures. The library is demonstrated on both synthetic benchmarks and real-world robotics systems, with the source code available at https://github.com/TUMFTM/rslcpp.
The authors present RSLCPP, an open-source library for ROS 2 that enables deterministic simulations by ensuring reproducible callback execution across different hardware architectures without requiring source code modifications.
Source: arXiv Robotics — research abstracts · Read original article ↗
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arXiv:2601.07052v3 Announce Type: replace Abstract: Simulation is crucial in real-world robotics, offering safe, scalable, and efficient environments for developing a variety of robotic applications. While the Robot Operating System (ROS) has been widely adopted as the backbone of these robotic applications in both academia and industry, its asynchronous, multi-process design complicates reproducibility, especially a
Open source S2
cross varying hardware platforms. Deterministic callback execution cannot be guaranteed when computation times and communication delays vary. This lack of reproducibility complicates scientific benchmarking and continuous integration, where consistent results are essential. To address this, we present a methodology to create deterministic simulations using ROS 2 nodes. Our ROS Simulation Library for C++ (RSLCPP) impl
Open source S3
ements this approach, enabling existing nodes to be combined into a simulation routine that yields reproducible results usually without requiring any source code changes. We demonstrate that our approach produces identical results across various CPUs and architectures when testing both a synthetic benchmark and a real-world robotics system. RSLCPP is open-sourced at https://github.com/TUMFTM/rslcpp.
Open source S4
Source：arXiv Robotics — research abstracts · arxiv.org