Dr. Ralph Lange

The use of simulation in robotics is increasingly widespread for the purpose of testing, synthetic data gener- ation and skill learning. A relevant aspect of simulation for a variety of robot applications is physics-based simulation of robot-object interactions. This involves the challenge of accurately modeling and implementing different mechanical systems such as rigid and deformable bodies as well as their interactions via constraints, contact or friction. Most state-of- the-art physics engines commonly used in robotics either cannot couple deformable and rigid bodies in the same framework, lack important systems such as cloth or shells, have stability issues in complex friction-dominated setups or cannot robustly prevent penetrations. In this paper, we propose a framework for strongly coupled simulation of rigid and deformable bodies with focus on usability, stability, robustness and easy access to state-of-the-art deformation and frictional contact models. Our system uses the Finite Element Method (FEM) to model deformable solids, the Incremental Potential Contact (IPC) approach for frictional contact and a robust second order optimizer to ensure stable and penetration-free solutions to tight tolerances. It is a general purpose framework, not tied to a particular use case such as grasping or learning, it is written in C++ and comes with a Python interface. We demonstrate our system’s ability to reproduce complex real-world experiments where a mobile vacuum robot interacts with a towel on different floor types and towel geometries. Our system is able to reproduce 100% of the qualitative outcomes observed in the laboratory environment. The simulation pipeline, named Stark (the German word for strong, as in strong coupling) is made open-source.

The micro-ROS stack (micro.ros.org) integrates microcontrollers seamlessly with standard ROS 2 and brings all major ROS concepts such as nodes, publisher, subscriptions, parameters, and lifecycle onto deeply embedded systems. This enables accessing all software using the same ROS tools and APIs, regardless of the underlying computing hardware and operating system. Micro-ROS supports a broad spectrum of microcontroller families and the main open-source real-time operating systems like FreeRTOS, Zepyhr, or NuttX. It supports various microcontroller- or RTOS-specific build systems and provides ROS-CLI-based build tooling. Micro-ROS is an open-source project that has been under development at github.com/micro-ROS since 2018. It was initiated by the EU-funded innovation activity OFERA. During the the last two years, micro-ROS has been adopted by a relevant group of professional users inside the ROS community. In this chapter, we give a technical introduction to the micro-ROS stack including APIs and architecture, as well as the corresponding middleware Micro XRCE-DDS. Furthermore, tutorials for a simple application with an ESP32 microcontroller are provided together with a report on three use-cases from industrial and research applications.

The Functional Mock-up Interface (FMI) is a widely used industry standard for exchange and co-simulation of dynamic models as Functional Mock-up Units (FMU). It is supported by more than 100 modeling and simulation tools. In this chapter, we present two implementations of FMI that bridge the gap between these tools and the ROS and Gazebo community: First, the fmi_adapter package for running/simulating FMUs in ROS nodes, from https://github.com/boschresearch/fmi_adapter_ros2. Second, the gazebo-fmi package for integrating FMUs with Gazebo, from https://github.com/robotology/gazebo-fmi. After an introduction to the FMI standard, this chapter provides step-by-step, hands-on examples for both packages, followed by interface descriptions and selected implementation details. In addition to these tutorial-style sections, the chapter also provides comprehensive descriptions of two use-cases. First, it explains how the fmi_adapter enabled a convenient model-based control design workflow for a self-driving vehicle for industrial logistics. Second, it reports on the simulation of electrical actuators in Gazebo from a Modelica model.

Robotic systems are typically subject to real-time constraints. Still, the ROS ecosystem-the most popular repository of open-source robotics software-exhibits little evidence of the use of real-time theory to bound or control worst-case response times. Hurdles to adoption are the amount of expertise required to correctly use real-time scheduling mechanisms and the inherent unpredictability of typical robotics workloads, which defy static provisioning. To overcome these hurdles, ROS-Llama, an automatic latency manager for ROS2, is proposed. Crucially, use of ROS-Llama requires only little effort and knowledge of realtime concepts. Relevant properties of ROS2 and essential requirements of the robotics domain are identified, and the conceptual and practical challenges in developing such a mostly automatic tool are discussed. Experiments on a mobile robot demonstrate the viability of the approach and show that ROS-Llama reduces the maximum observed latency under load compared to the default Linux scheduler. Finally, open problems in the underlying real-time analysis and major platform limitations in Linux and ROS2 that prevent further improvements are identified.