Understanding Misconfigurations in ROS: An Empirical Study and Current Approaches

One of the challenges of outdoor robots is developing effective portable Human-Robot-Interaction (HRI) frameworks. Hand-held devices offer a practical solution. By equipping these devices with robot software, they can be made to interact with the outdoor robots. Android devices are ideal as they are open source and can be integrated with robots powered by the Robot Operating System (ROS), also open source. However, due to the limits of rosjava, the mechanism that links ROS with android, and the conflicting modes of operation between ROS and android, current implementations of ROS-android offer limited robot applications that do not support advanced operations such as autonomous navigation and others. This paper implements selective compartmentalization to overcome these limitations, by combining ROS with android through a number of ROS and android bridges that would facilitate the development of advanced robot applications. Through the proposed method, authors were able to develop a portable HRI framework that allowed human operators to supervise an outdoor mobile robot while it performed an autonomous task. From their mobile devices, users were able to initialize the robot, configure its motion, and monitor its progress. Also, users were able to reprogram the robot to perform new tasks (not previously planned) through a creative use of features offered in the developed HRI framework. Also, user cognitive effort was reported to be low as evident by the positive score on the NASA-TLX scale test which was corroborated with robot performance data. This paper presents the detailed development and implementation steps.

Robots are becoming more and more commonplace in many industry settings. This successful adoption can be partly attributed to (1) their increasingly affordable cost and (2) the possibility of developing intelligent, software-driven robots. Unfortunately, robotics software consumes significant amounts of energy. Moreover, robots are often battery-driven, meaning that even a small energy improvement can help reduce its energy footprint and increase its autonomy and user experience.In this paper, we study the Robot Operating System (ROS) ecosystem, the de-facto standard for developing and prototyping robotics software. We analyze 527 energy-related data points (including commits, pull-requests and issues on ROS-related repositories, ROS-related questions on StackOverflow, ROS Discourse, ROS Answers and the official ROS Wiki).Our results include a quantification of the interest of roboticists on software energy efficiency, 10 recurrent causes and 14 solutions of energy-related issues, and their implied trade-offs with respect to other quality attributes. Those contributions support roboticists and researchers towards having energy-efficient software in future robotics projects.

Robot Operating system (ROS) is collection of software frameworks for robot software development. Researchers that work with ROS will have an opportunity to use or to be exact to reuse any software framework from another researcher as long as they use a similar robot platform, or similar device that has been include in the ROS. This paper present a design for a low cost rotating Lidar that compatible with ROS. As all we know distance measurement is the basic for building an autonomous capability for robots. Rotating lidar is among one the most popular device used to acquire this kind of information. However most of them are not suitable for low budget project because of their high cost. The design presented here tries to build a low cost rotating lidar based on Lidar Lite device with the compatibility with the ROS. The design incorporate a control board based on a microcontroller.

The general objective of the research was to determine the advances related to the robotics and artificial intelligence. The specific objectives of the research are to determine the countries and organizations that successfully manufacture robots, identify the characteristics of the most representative robots and the software used in their design and operation. Methodology, in this research, 61 documents have been selected, carried out in the period 2018 - 2024; including: scientific articles, review articles and information from websites of recognized organizations. Results, the software used in the design and operation of the robots are: Robot operating systems (ros), industrial robot programming software, simulation software, robot vision software, autonomous navigation software, collaborative robot (cobot) software. Conclusions, artificial intelligence has been evolving and has managed to position itself as an important technology to improve various systems. The leading robotics producers are in Germany, Japan, and Switzerland. The organizations that successfully manufacture robots are ABB Group (Switzerland), Adept Technology Inc (United States) and Apex Automation and Robotics (Australia). And the software used in the design and operation of the robots are: Robot operating systems (ros), industrial robot programming software, simulation software, robot vision software, autonomous navigation software, collaborative robot (cobot) software.

The Robot Operating System (ROS) [229] is an open source middleware and a collection of associated software frameworks for modular (distributed) robot software. A focus of the middleware is exchange of streaming data under soft real-time conditions while maintaining a high runtime flexibility. ROS is often used in a research context where heterogeneous software components, often developed in isolation by different people, must work together across multiple computers.

최근 로봇 소프트웨어 플랫폼의 연구는 로봇 기기들의 추상화를 통해 지능형 서비스를 제공하는데 초점을 두고 있다. 사물인터넷 환경에서 지능형 로봇 서비스를 제공하기 위해서는 이기종 센서들의 환경정보를 인지하는 상황인지 기술이 필요하다. ROS는 로봇 디바이스를 추상화하는 기술을 바탕으로 로봇을 사용한다. ROS는 로봇을 제어하기 위해 이기종 센서 자체를 추상화하는 기능을 포함하고 있으나, 일관된 수집 방법을 통한 환경 정보를 바탕으로 로봇이 인지할 수 있는 상황 정보를 제공하는 기능은 결여되어 있다. 따라서 본 논문에서는 ROS가 상황인지 기반의 로봇 서비스를 제공하는데 필요한 중계 시스템을 제안한다. 제안하는 시스템은 로봇이 인지할 수 있는 추상화된 상황정보를 제공하는 외부의 상황인지 시스템과 로봇을 제어하는 ROS를 중계하여, ROS가 상황인지 로봇 서비스를 제공할 수 있도록 도와준다. 실험에서는 제안하는 시스템을 바탕으로, 상황인지 시스템과 ROS에서 추상화된 로봇 서비스를 연동하여 로봇 서비스를 실행시키는 과정을 보인다. Recent robot software platform research focuses on providing intelligent service via abstraction of robot devices. Context-aware techniques are necessary for intelligent robot services, which are based on the perception of environmental information obtained from heterogeneous sensors in IoT environment. Robot Operating System (ROS) provides protocols to operate robot devices. ROS includes functions for abstracting heterogeneous sensors themselves in order to control the robot, however, it lacks the ability to provide context information that the robot can perceive based on environmental information through consistent collection methods. In this paper, we propose a relay system for ROS to provide context-aware robot service. The proposed system makes it possible for ROS to control and provide context-aware robot services with relay of an external context-aware system and ROS. In experiments, we demonstrate procedures that robot services abstracted from ROS and an external context-aware system works together based on the proposed system.

Robot systems are growing in importance and complexity. Ecosystems for robot software, such as the Robot Operating System (ROS), provide libraries of reusable software components that can be configured and composed into larger systems. To support compositionality, ROS uses late binding and architecture configuration via “launch files” that describe how to initialize the components in a system. However, late binding often leads to systems failing silently due to misconfiguration, for example by misrouting or dropping messages entirely.In this paper we present ROSDiscover, which statically recovers the run-time architecture of ROS systems to find such architecture misconfiguration bugs. First, ROSDiscover constructs component level architectural models (ports, parameters) from source code. Second, architecture configuration files are analyzed to compose the system from these component models and derive the connections in the system. Finally, the reconstructed architecture is checked against architectural rules described in first-order logic to identify potential misconfigurations.We present an evaluation of ROSDiscover on real world, off-the-shelf robotic systems, measuring the accuracy, effectiveness, and practicality of our approach. To that end, we collected the first data set of architecture configuration bugs in ROS from popular open-source systems and measure how effective our approach is for detecting configuration bugs in that set.

While spherical robots are an interesting design that has been studied before, but due to their relative manufacturing complexity there are few such devices commercially available. Given the increased popularity of 3D printers and laser cutters, rapid prototyping has become an integral part of engineering practice. Leveraging these advances, we have developed Spherico. Spherico is an inexpensive spherical robot that utilizes both laser cutter and 3D printing technology combined with off-the-shelve (OTS) components. Driven by a Raspberry Pi, the ROS (Robotic Operating System) is used as the underlying software architecture for controlling the robot. Using all the off-the-shelve OTS components, rapid prototyping parts and ROS, Spherico takes less than 72Hrs to build. The resulting robot is an inexpensive and robust platform for research into spherical robot control.

A review of robotic systems was carried out. The paper analyzes applied hardware and software solutions and summarizes the most common block diagrams of control systems. The analysis of approaches to control systems scaling, the use of intelligent control, the achievement of fault tolerance, and the reduction of the weight and size of control system elements belonging to various classes of robotic systems were carried out. The goal of the review is finding common approaches used in various areas of robotics to build on their basis a uniform methodology for designing scalable intelligent control systems for robots with a given level of fault tolerance on a unified component base. This part is dedicated to service robotics. The following conclusions are made on the basis of the review results: the key technology in service robotics from the point of view of scalability is the Robot Operating System (ROS); service robotics is today the main springboard for testing intelligent algorithms for the tactical and strategic control levels that are integrated into a common system based on ROS; the problem of ensuring fault tolerance in the service robotics is practically neglected, with the exception of the issue of increasing reliability by changing behavioral algorithms; in a number of areas of service robotics, in which the reduction of mass and dimensions is especially important, the robot control systems are implemented on a single computing device, in other cases a multi-level architecture implemented on Linux-based embedded computers with ROS are used.

This study utilized the Robot Operating System (ROS) to simulate various poses of humanoid robot. The distributed ROS architectures efficiently communicate with each other point to make sure the correct sequential procedures and execute full information exchange through the peer to peer topology. Humanoid robot software designed in Linux-based ROS environment to integrate the software and hardware system plant through ROS. The advanced Gazebo presents the cyber-physical behavior of humanoid robot in the reality experiments.

Dynamic programming techniques have proven much more flexible than calculus of variations and other techniques in performing redundancy resolution through global optimization of performance indices. When the state and input spaces are discrete, and the time horizon is finite, they can easily accommodate generic constraints and objective functions and find Pareto-optimal sets. Several implementations have been proposed in previous works, but either they do not ensure the achievement of the globally optimal solution, or they have not been demonstrated on robots of practical relevance. In this communication, recent advances in dynamic programming redundancy resolution, so far only demonstrated on simple planar robots, are extended to be used with generic kinematic structures. This is done by expanding the Robot Operating System (ROS) and proposing a novel architecture meeting the requirements of maintainability, re-usability, modularity and flexibility that are usually required to robotic software libraries. The proposed ROS extension integrates seamlessly with the other software components of the ROS ecosystem, so as to encourage the reuse of the available visualization and analysis tools. The new architecture is demonstrated on a 7-DOF robot with a six-dimensional task, and topological analyses are carried out on both its state space and resulting joint-space solution.

There are many ways to build the software for a Middle Size League (MSL) robot. A common problem in developing software for any long-term project including MSL is enabling future developers to maintain and continue further research on the project. A solution to this problem is to use an already existing software development framework. In recent years, the Robot Operating System (ROS) has become the ’de facto’ standard framework for robotics software development. This paper will explore the advantages found in using ROS as the framework to build a software for a robot The three main advantages that were found in using ROS are data sharing, hardware abstraction, and program concurrency. These advantages allowed the team to build modular software that is more maintainable. Furthermore, there was minimum computation cost found in using ROS. Lastly, the locomotion system was tested. When given a linear movement command, the locomotion system has an average actual distance error of 8.84 cm with a standard deviation of 6.70 cm. It is also found that the average computed error is 3.54 cm with a standard deviation of 1.49 cm.

Customization of manipulator configurations using modularity and reconfigurability aspects is receiving much attention. Modules presented so far in literature deals with the conventional and standard configurations. This paper presents the 3D printable, light-weight and unconventional modules: MOIRs' Mark-2, to develop any custom `n'-Degrees-of-Freedom (DoF) serial manipulator even with the non-parallel and non-perpendicular jointed configuration. These unconventional designs of modular configurations seek an easy adaptable solution for both modular assembly and software interfaces for automatic modeling and control. A strategy of assembling the modules, automatic and unified modeling of the modular and reconfigurable manipulators with unconventional parameters is proposed in this paper using the proposed 4 modular units. A reconfigurable software architecture is presented for the automatic generation of kinematic and dynamic models and configuration files, through which, a designer can design, validate using visualization, plan and execute the motion of the developed configuration as required. The framework developed is based upon an open source platform called as Robot Operating System (ROS), which acts as a digital twin for the modular configurations. For the experimental demonstration, a 3D printed modular library is developed and an unconventional configuration is assembled, using the proposed modules followed by automatic modeling and control, for a single cell of the vertical farm setup.

In this paper we present a terrain-aided particle filter to localize a freely drifting underwater vehicle. The vehicle is a bottom imaging Lagrangian float used for habitat classification, monitoring and fish abundance. During operation the vehicle captures down looking images at a controlled altitude above the bottom. Direct navigation information is often, but not always, recorded with a ultra short baseline (USBL) acoustic system. The presented methodology provides an alternate method for georeferencing when USBL is unavailable. The implemented particle filter utilizes a background bathymetry map and visual odometry as a motion mode. The particle filter is implemented using the Robot Operating System (ROS) and Orocos Bayesian Filtering Library (BFL). The Grid Map package is used to store and retrieve the bathymetryic data. Results using data collected on field deployments in the Hawaiian islands in 2018 show the method is able to effectively utilize the terrain information and produce drift trajectories which closely match the recorded USBL data. Utilizing the method allows the float system to be deployed with minimal ship-side support while still maintaining the georeferencing critical to the end use of the collected images.

We present tx2_fcnn_node – a Robot Operating System (ROS) compatible tool that is aimed at seamless integration of various monocular depth reconstruction neural networks to the robotic software based on ROS (which is a de-facto standard in the area of robotics). Our tool simplifies the process of deploying, evaluating, and comparing depth reconstruction neural networks both on real robots and in simulation. We complement our software with a set of the precompiled neural networks which can be used off the shelf, with some of them being able to demonstrate near real-time performance when running onboard compact embedded platforms, e.g. Nvidia Jetson TX2, that are often used nowadays both in academia and industry.