ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems

An ever-increasing number of robotic applications is being created based on the functionalities and the communication facilities offered by the Robotic Operating System (ROS). When applications involve contact with humans, such as in some transportation tasks, a robot supervisory controller shall guarantee that in every possible circumstance safety and task requirements are satisfied. There is no framework provided by ROS to specify supervisory controllers with formal guarantees about the satisfaction of requirements. This is problematic when the complexity of the controller increases, and it is not viable to test every possible scenario during the validation stage of the robotic application. This paper presents novel work that aims at enabling supervisory controller synthesis for ROS-based applications by (a) proposing a novel mapping between concepts from supervisory control theory and ROS, (b) demonstrating that a supervisory control modeling language exists that can be used to describe plant models and to specify requirements and (c) presenting generic finite-state automata models of ROS components, regarded as plant models, which are input for the synthesis procedure. The approach is demonstrated by synthesizing the controller to coordinate state-of-the-art mobile robot navigation modules. Simulations and real-life experiments show that the generated supervisory controller guarantees the correctness of the model with respect to the requirements and that the execution time of a control loop, including the binding code between the supervisory controller and ROS, is on average short enough to be deployed in high-level control loops. The paper is accompanied by a public code repository that contains the implementation of all methods presented in the paper including simulation environments to ease the replication of the results presented.

Security for the Robot Operating System

Building customized control system for specific robot is generally acknowledged as the fundamental section of developing auto robots. To simplify the programming process and increase the reuse of codes, this research develops a general method of developing customized robot simulation and control system software with robot operating system (ROS). First, a 3D visualization model is created in URDF (unified robot description format), and is viewed in Rviz to achieve motion planning with MoveIt! software package. Second, the machine vision provided by camera driver package in ROS enables the use of tools for image process, 3D point cloud analysis to reconstruct the environment to achieve accurate target location. Third, the communication protocols provided by ROS like serial, Modbus support the communication system development. To examine the method, we designed a tomato harvesting dual-arm robot, and conducted farming experiment with it. This work demonstrates the advantages of ROS when applied in robot control system development, and offers a plain method of building such system with ROS.

The next chapter of the robotics revolution is well underway with the deployment of robots for a broad range of commercial use cases. Even in a myriad of applications and environments, there exists a common vocabulary of components that robots share-the need for a modular, scalable, and reliable architecture; sensing; planning; mobility; and autonomy. The Robot Operating System (ROS) was an integral part of the last chapter, demonstrably expediting robotics research with freely available components and a modular framework. However, ROS 1 was not designed with many necessary production-grade features and algorithms. ROS 2 and its related projects have been redesigned from the ground up to meet the challenges set forth by modern robotic systems in new and exploratory domains at all scales. In this Review, we highlight the philosophical and architectural changes of ROS 2 powering this new chapter in the robotics revolution. We also show through case studies the influence ROS 2 and its adoption has had on accelerating real robot systems to reliable deployment in an assortment of challenging environments.

Approach of resource expenditure estimation toward mechanization in the manufacturing of cell-based products.

The need for efficient automation methods has prompted the rapid development in the field of Robotics. The development of intelligent robots leads to the ability of them becoming an operator highly efficient and able to adapt to a wide range of problems. Still, despite of the several robotic solutions available, the majority of current industrial robots do not use the Robotic Operative System (ROS) and have limitations in terms of autonomously correct errors during their tasks. An important aspect to consider when developing a new robot is the selection of the methodology for recognition of the objects to be handled. In this paper, it will be presented an approach with enough flexibility to be potentially applicable to different scenarios of object recognition and handling normally found in industrial environment. The main aim is for this application to be applied to pick and place routines in robotics. Moreover it will be presented one particular case study that used the proposed approach, the European Robotics Challenges (EUROC) — a challenge aiming to develop a robot for shop floor logistics and manipulation. Our proposed approach is based on the three tiers paradigm: 1-recognition/sensing tier, 2-effector tier and 3-the control tier and was built using the ROS framework. Since ROS is becoming one of the most useful tools in robotics nowadays, the possibility of using a methodology able to be expressed in ROS allows for the development of a standard approach to pick and place operations. Another advantage of our proposed pick and place approach is the ability to have a robot safely and efficiently inserted in an unknown environment. This is possible due to the insertion of an adaptive control tier in our methodology. The proposed approach can be valuable in the field of robotics and can be potentially applied in multiple tasks and it has already allowed us to advance to the next stage of the already mention challenge.

Service robot has its challenge to adapt on new tasks based on instruction or environment. Such conditions need to reconfigure or reorganize to obtain new system capabilities. However, most common service robot, especially the one that gives services to help human to deliver food or non medical stuffs in an elderly house, suffers on its task flexibility. Unlike a human, robot system needs to be reconfigured to have a new task which may interrupt its services because of this event. To this, we need a technique to handle adaptive tasks that is flexible to change the robot tasks that do not create delay. Dynamic software product line provides a mechanism to reconfigure a system to have different capabilities based on the core assets of the system, such as software that supports and controls the hardware components in a robotic system. In this work, we make use of the dynamic software product line to create a flexible method that enables a service robot to adapt on its new tasks. In order to define the change of tasks, we model the transformation of task using a transition state which has constraints as a trigger. Other than that, the request of change may also have resulted by forcing an interrupt mechanism. To demonstrate the capability of our approach, the proof of concept using Robotic Operating System will be presented.

Astronomical observatories are complex systems requiring the integration of numerous devices into a common platform. We are presenting here the firsts steps to integrate the popular Robotic Operating System (ROS) into the control of a fully autonomous observatory. The observatory is also equipped with a decision-making procedure that can automatically react to a changing environment (like weather events). The results obtained so far have shown that the automation of a small observatory can be greatly simplified when using ROS, as well as robust, with the implementation of our decision-making algorithms.

This paper proposes an integrated control system for multi-disaster response robots based on Robot Operating System (ROS). The contributions of this paper were as follows: 1) A multi-score-based system concept was proposed in consideration of network instability issues which might frequently occur in compound disaster environments; 2) A detailed ROS based software structure was implemented to apply the proposed system to real robots; 3) Hardware cockpit and graphical user interface (GUI) for an operator were implemented; 4) through the experiment, the problem of the system based on common ROS structure, the out-of-control state, was confirmed and we verified the proposed system using the scenario.

Reuse is an important means of reducing costs and effort during the development of complex software systems. A major challenge is to find suitable components in a large library with reasonable effort. This becomes even harder in today’s development practice where a variety of artefacts such as models and documents play an equally important role as source code. Thus, different types of heterogeneous components exist and require consideration in a component search process. One flexible approach to structure (software component) libraries is faceted classification. Faceted classifications and in particular faceted browsing are nowadays widely used in online systems. This paper takes a fresh approach towards using faceted classification in heterogeneous software component libraries by transferring faceted browsing concepts from the web to software component libraries. It presents an architecture and implementation of such a library. This implementation is used to evaluate the applicability of facets in the context of an industry-driven case study.

In this paper, we have designed a autonomous vehicle which is cost effective and powered by Robotic Operating System (ROS). The vehicle is capable of maintaining a constant speed and distance for monitoring or surveillance. ROS is implemented for trajectory tracking and telemetry. A low cost compact on-board embedded system powers the vehicle. Various image processing techniques are been implemented for navigation and obstacle detection. Artificial Neural Network which helps in finding the shortest path by using the acquired data from image processing. Different controllers were implemented for movement and obstacle avoidance including PI and PID. The performance were compared and the results are also discussed in this paper.

Complex system science has recently shifted its focus to include modeling, simulation, and behavior control. An effective simulation software built on robot operating system (ROS) is used in robotics development to facilitate the smooth transition between the simulation environment and the hardware testing of control behavior. In this paper, we demonstrate how the simultaneous localization and mapping (SLAM) algorithm can be used to allow a robot to navigate autonomously. The Gazebo is used to simulate the robot, and Rviz is used to visualize the simulated data. The G-mapping package is used to create maps using collected data from a variety of sensors, including laser and odometry. To test and implement autonomous navigation, a Turtlebot was used in a Gazebo-generated simulated environment. In our opinion, additional study on ROS using these important tools might lead to a greater adoption of robotics tests performed, further evaluation automation, and efficient robotic systems.

The control system of a high-DOF human-interaction robot requires the high-frequency simultaneous control of multiple joints, which needs the capability to handle computation-massive tasks with low latancies. Aiming at the force control of 2-DOF fluid-actuated manipulator, I'm going to introduce a distributed infrastructure design with good flexibility and scalability, while maintaining a high-quality real-time performance. In this thesis, a motor control library, arranged on a core-isolated real-time machine, is developed to provide control implementers with functional APIs and input/output mapping of low-level data structures from SOEM (Simple Open EtherCAT Master) interfacing the direct-drive motors and peripheral sensors via EtherCAT bus communication. While on a remote machine, the ROS (Robot Operating System) is deployed to deal with high-level non-realtime applications, including algorithm processing, data visualization and status analysis. At the same time, a user-friendly Python proxy with a couple of control APIs are offered as an auxiliary medium besides the ROS native interfaces. To synchronize the user-facing data on both sides, a robust ROS interface is developed using the Shared Memory technique which is an IPC (Inter-Process Conmmunication) mechanism supported by Linux POSIX standards. The teleoperation experiment demonstrates that the robot system can operate the closed-loop control consistently at 2 kHz, while limiting the loaded latency below 100 us. In addition, the collision detection test shows both dexterity and maneuverability under unknown environments.

Programming modern Robots' missions and behavior has become a very challenging task. The always increasing level of autonomy of such platforms requires the integration of multi-domain software applications to implement artificial intelligence, cognition, and human-robot/robot-robot interaction applications. In addition, to satisfy both functional and nonfunctional requirements such as reliability and energy efficiency, robotic SW applications have to be properly developed to take advantage of heterogeneous (Edge-Fog-Cloud) architectures. In this context, containerization and orchestration are becoming a standard practice as they allow for better information flow among different network levels as well as increased modularity in the use of software components. Nevertheless, the adoption of such a practice along the design flow, from simulation to the deployment of complex robotic applications by addressing the de-facto development standards (i.e., robotic operating system - ROS - compliancy for robotic applications) is still an open problem. We present a design methodology based on Docker and Kubernetes that enables containerization and orchestration of ROS-based robotic SW applications for heterogeneous and hierarchical HW architectures. The design methodology allows for (i) integration and verification of multi-domain components since early in the design flow, (ii) task-to-container mapping techniques to guarantee minimum overhead in terms of performance and memory footprint, and (iii) multi-domain verification of functional and non-functional constraints before deployment. We present the results obtained in a real case of study, in which the design methodology has been applied to program the mission of a Robotnik RB-Kairos mobile robot in an industrial agile production chain. The source code of the mobile robot is publicly available on GitHub.

In clinics, customized archwires are demanded for lingual orthodontic treatment. However, only very experienced orthodontists can handle the manual appliance preparation. This pattern not only occupies lots of the orthodontist's labor time, but also can not ensure the accuracy of the appliances. Therefore, a robotic system was developed for automatic and accurate orthodontic archwire bending in our study. First, a method for customized archwire parameterization was developed. Second, an adaptive sampling-based bending planner with collision checker in time-varying environment was designed. Finally, a bending control strategy was used to eliminate the springback effect of the archwires and bending point shift during the bending process. A self-developed simulation platform based on Robot Operating System with MoveIt was used for preliminary validation of the proposed method. Physical experiments for multi-functional orthodontic bends on the robotic system were conducted as well. The results have shown that the developed robotic system using the proposed planning and control method was able to accomplish the automatic and accurate orthodontic archwire bending.