ros2_tracing: Multipurpose Low-Overhead Framework for Real-Time Tracing of ROS 2

Testing and debugging have become major obstacles for robot software development, because of high system complexity and dynamic environments. Standard, middleware-based data recording does not provide sufficient information on internal computation and performance bottlenecks. Other existing methods also target very specific problems and thus cannot be used for multipurpose analysis. Moreover, they are not suitable for real-time applications. In this paper, we present ros2_tracing, a collection of flexible tracing tools and multipurpose instrumentation for ROS 2. It allows collecting runtime execution information on real-time distributed systems, using the low-overhead LTTng tracer. Tools also integrate tracing into the invaluable ROS 2 orchestration system and other usability tools. A message latency experiment shows that the end-to-end message latency overhead, when enabling all ROS 2 instrumentation, is on average 0.0033 ms, which we believe is suitable for production real-time systems. ROS 2 execution information obtained using ros2_tracing can be combined with trace data from the operating system, enabling a wider range of precise analyses, that help understand an application execution, to find the cause of performance bottlenecks and other issues. The source code is available at: https://github.com/ros2/ros2_tracing.Comment: 8 pages, 8 figures, 3 table

Message Flow Analysis with Complex Causal Links for Distributed ROS 2 Systems

Distributed robotic systems rely heavily on the publish-subscribe communication paradigm and middleware frameworks that support it, such as the Robot Operating System (ROS), to efficiently implement modular computation graphs. The ROS 2 executor, a high-level task scheduler which handles ROS 2 messages, is a performance bottleneck. We extend ros2_tracing, a framework with instrumentation and tools for real-time tracing of ROS 2, with the analysis and visualization of the flow of messages across distributed ROS 2 systems. Our method detects one-to-many and many-to-many causal links between input and output messages, including indirect causal links through simple user-level annotations. We validate our method on both synthetic and real robotic systems, and demonstrate its low runtime overhead. Moreover, the underlying intermediate execution representation database can be further leveraged to extract additional metrics and high-level results. This can provide valuable timing and scheduling information to further study and improve the ROS 2 executor as well as optimize any ROS 2 system. The source code is available at: https://github.com/christophebedard/ros2-message-flow-analysis.Comment: 14 pages, 12 figure

Vision-Based Hybrid Controller to Release a 4-DOF Parallel Robot from a Type II Singularity

[EN] The high accuracy and dynamic performance of parallel robots (PRs) make them suitable to ensure safe operation in human¿robot interaction. However, these advantages come at the expense of a reduced workspace and the possible appearance of type II singularities. The latter is due to the loss of control of the PR and requires further analysis to keep the stiffness of the PR even after a singular configuration is reached. All or a subset of the limbs could be responsible for a type II singularity, and they can be detected by using the angle between two output twist screws (OTSs). However, this angle has not been applied in control because it requires an accurate measure of the pose of the PR. This paper proposes a new hybrid controller to release a 4-DOF PR from a type II singularity based on a real time vision system. The vision system data are used to automatically readapt the configuration of the PR by moving the limbs identified by the angle between two OTSs. This controller is intended for a knee rehabilitation PR, and the results show how this release is accomplished with smooth controlled movements where the patient¿s safety is not compromised.This research was funded by the FEDER-CICYT project with reference PID2020-119522RBI00 (ROBOTS PARALELOS DE REHABILITACION: DETECCION Y CONTROL DE SINGULARIDADES EN PRESENCIA DE ERRORES DE MANUFACTURA), Spain.Pulloquinga-Zapata, J.; Escarabajal-Sánchez, RJ.; Ferrándiz, J.; Vallés Miquel, M.; Mata Amela, V.; Urízar, M. (2021). Vision-Based Hybrid Controller to Release a 4-DOF Parallel Robot from a Type II Singularity. Sensors. 21(12):1-21. https://doi.org/10.3390/s21124080121211

Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans

The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product