In recent research activities, autonomous vehicles and self-driving technology have gained lot of attention among scientists. The idea of autonomous vehicles can be anticipated in the 1920s when the ...design of the first radio-controlled vehicles was in progress. Autonomous vehicles are going to be the trend of the future in this modern era of automation and technology. In this paper various autonomous driving aspects, highlighting the software stack and hardware components are discussed. The software architecture covers mainly robot operating system (ROS), machine learning (ML), deep learning (DL), and OpenCV frameworks, along with the calibration of sensors and cameras. The paper also discussed about simultaneous localization and mapping (SLAM) based-path tracking, computer vision-based controller, and intelligent object avoidance. Further, point cloud, ground, radius, and raycast filters was implemented to distinguish between the real-time objects, ground, and its own parts or obstacle shadows. The paper highlights the overall hardware modules responsible for controlling the car.
•Future trend of Autonomous vehicles in modern era of automation and technology.•Simultaneous localization and mapping based-path tracking.•Computer vision-based controller, and intelligent object avoidance.•Discussion on Hardware modules responsible for controlling the car.
This article proposes a general approach to solve the hand-eye calibration problem. The system is general since it is able to calibrate any number of cameras and, moreover, is able to simultaneously ...perform the calibration of several instances of the two common hand-eye calibration use cases: eye-on-hand and eye-to-base. The calibration is solved with a nonlinear least squares method, and the reprojection error is used as a metric to guide the optimization procedure. Our approach is seamlessly integrated with the robot operating system framework and allows for the interactive positioning of sensors and labeling of data, facilitating both the data acquisition and labeling and the calibration procedures. Results show that the proposed approach is able to handle any calibration use case with a minimal initial configuration. The approach is compared with several other state-of-the-art hand-eye calibration algorithms. Results show that the proposed approach produces very accurate calibrations when compared to the state of the art.
Future challenges in manufacturing will require automation systems with robots that are increasingly autonomous, flexible, and hopefully equipped with learning capabilities. The flexibility of ...production processes can be increased by using a combination of a flexible human worker and intelligent automation systems. The adoption of middleware software such as ROS2, the second generation of the Robot Operating System, can enable robots, automation systems, and humans to work together on tasks that require greater autonomy and flexibility. This paper has a twofold objective. Firstly, it provides an extensive review of existing literature on the features and tools currently provided by ROS2 and its main fields of application, in order to highlight the enabling aspects for the implementation of modular architectures to increase autonomy in industrial operations. Secondly, it shows how this is currently potentially feasible in ROS2 by proposing a possible high-level and modular architecture to increase autonomy in industrial operations. A proof of concept is also provided, where the ROS2-based framework is used to enable a cobot equipped with an external depth camera to perform a flexible pick-and-place task.
Robot Operating System 2 DiLuoffo, Vincenzo; Michalson, William R; Sunar, Berk
International journal of advanced robotic systems,
05/2018, Volume:
15, Issue:
3
Journal Article
Peer reviewed
Open access
It is no secret that robotic systems are expanding into many human roles or are augmenting human roles. The Robot Operating System is an open-source standard for the robotic industry that enables ...locomotion, manipulation, navigation, and recognition tasks by integrating sensors, motors, and controllers into reusable modules over a distributed messaging architecture. As reliance on robotic systems increases, these systems become high value targets, for example, in autonomous vehicles where human life is at risk. As Robot Operating System has become a de facto standard for many robotic systems, the security of Robot Operating System becomes an important consideration for deployed systems. The original Robot Operating System implementations were not designed to mitigate the security risks associated with hostile actors. Robot Operating System 2, the next generation of the Robot Operating System, addresses this shortcoming, leveraging Data Distributed Services for its messaging architecture and Data Distributed Services security extension for its data protection in motion. This article provides a systematic review of Robot Operating System 2 and identifies potential risks for this new robotic system paradigm. A Robot Operating System 2 robotic system is viewed as a series of layers from the hardware that include sensors, motors, and controllers to the software layers, which include the operating system, security services, protocols, messaging, and the cognitive layer for observation, learning, and action. Since Robot Operating System 2 and security are new considerations for robotics systems as they move into mainstream, many questions emerge. For example, can some portions be secure and other portions be non-secure? Does everything need to be secure? What are the trade-offs between, security, performance, latency and throughput? What about real-time robotic systems? This article provides an overview of the Robot Operating System 2 paradigm and represents a first step toward answering these questions.
This paper proposes deep learning-based footstep planning using Generative Adversarial Networks (GANs) for the indoor navigation of humanoid robots. The GAN-based architecture presents an efficient ...and accurate path to plan the footsteps of a humanoid robot on Robot Operating System (ROS) based architecture. During navigation, humanoid robots must understand their surroundings and be able to generate footsteps accurately. Although some algorithms that are based on sampling, such as Rapidly Exploring Random Tree (RRT*) and A*, are widely used for path planning, they fail to perform in narrow paths, especially for the footstep generation of humanoid robots. The widely growing deep learning approaches such as GANs are now producing extremely surprising results in solving real-life problems. The experiments conclude that GAN based approach performs better than conventional Dijkstra’s or A* algorithms. The accuracy of the generated footsteps from the GAN-based path planner comes out to be approximately 93%.
•This paper proposes deep learning-based footstep planning using GANs for the indoor navigation of humanoid robots.•The GAN-based architecture presents an efficient path to plan the footsteps of a humanoid robot on ROS based architecture.•During navigation, humanoid robots must understand their surroundings and be able to generate footsteps accurately.•The experiments conclude that GAN based approach performs better than conventional Dijkstra’s A* algorithms.•The accuracy of the generated footsteps from the GAN-based path planner comes out to be approximately 93%.
The Robot Operating System 2 (ROS 2) is rapidly impacting the intelligent machines sector — on space missions, large agriculture equipment, multi-robot fleets, and more. Its success derives from its ...focused design and improved capabilities targeting product-grade and modern robotic systems. Following ROS 2’s example, the mobile robotics ecosystem has been fully redesigned based on the transformed needs of modern robots and is experiencing active development not seen since its inception.
This paper comes from the desks of the key ROS Navigation maintainers to review and analyze the state of the art of robotics navigation in ROS 2. This includes new systems without parallel in ROS 1 or other similar mobile robotics frameworks. We discuss current research products and historically robust methods that provide differing behaviors and support for most every robot type. This survey consists of overviews, comparisons, and expert insights organized by the fundamental problems in the field. Some of these implementations have yet to be described in literature and many have not been benchmarked relative to others. We end by providing a glimpse into the future of the ROS 2 mobile robotics ecosystem.
•ROS 2’s Nav2 has a number of new algorithms and capabilities suitable for a large number of applications.•This survey analyzes ROS 2 algorithm’s capabilities and benchmarks performance.•Explains systems provided to build robust autonomous navigation systems in dynamic environments.
The Robot Operating System (ROS) is a popular and widely used software framework for building robotics systems. With the growth of its popularity, it has started to be used in multi-robot systems as ...well. However, the TCP connections that the platform relies on for connecting the so-called ROS nodes presents several issues regarding limited-bandwidth, delays, and jitter, when used in wireless multi-hop networks. In this paper, we present a thorough analysis of the problem and propose a new ROS node called Pound to improve the wireless communication performance by reducing delay and jitter in data exchanges, especially in multi-hop networks. Pound allows the use of multiple ROS masters (roscores), features data compression, and importantly, introduces a priority scheme that allows favoring more important flows over less important ones. We compare Pound to the state-of-the-art solutions through extensive experiments and show that it performs equally well, or better in all the test cases, including a control-over-network example.
Visible light positioning (VLP) is widely believed to be a cost-effective answer to the growing demand for service-based indoor positioning. Meanwhile, high accuracy localization is very important ...for mobile robots in various scenes including industrial, domestic and public transportation workspace. In this paper, an indoor robot VLP localization system based on Robot Operating System (ROS) is presented for the first time, aiming at promoting the application of VLP in mature robotic system. On the basis of our previous researches, we innovatively designed a VLP localization package which contains the basic operation control of the robots, the features extraction and recognition of the LED-ID, cm-level positioning, and robust dynamic tracking algorithms. This package exploited the proposed lightweight algorithm, distributed framework design, the loose coupling characteristics of the ROS, and the message communication methods among different nodes. What's more, an efficient LED-ID detection scheme is proposed to ensure the lightweight and accuracy of the positioning. A prototype system has been implemented on a Turtlebot3 Robot 11 Experiment Demonstration is available at: https://kwanwaipang.github.io/Image/ROS.mp4.. Experimental results show that the proposed system can provide robot indoor positioning accuracy within 1 cm and an average computational time of only 0.08 s.
Autonomous robots are designed to support humans in diverse ways including companionship and assistance, as technology evolves, the burden of physical tasks which were performed by humans in the past ...are getting reduced. Autonomous guidance and navigation are popular fields that use mobile robots to replace humans. These robots are widely used in space, defence, education, and industry and require navigating safely through different environments. A significant aspect of Autonomous Robot Navigation is an obstacle and pedestrian avoidance. Most of the outdoor guiding robots follow the concept of SLAM (Simultaneous Localisation and Mapping) for moving from the initial point to the goal point. Moreover, image processing plays a vital role in the detection and recognition between humans and objects. The existing methodology comprises implementing autonomous tour guide robots are based in embedded systems which has a high degree of recognition accuracy. This paper provides a comprehensive review of the existing autonomous campus and tour guiding robots. This paper is steered at providing a satellite view of these existing assemblies and the advances made with them.
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