Software engineering research on the Robot Operating System: A systematic mapping study

Albonico, Michel; Đorđević, Milica; Hamer, Engel; Malavolta, Ivano

doi:10.1016/j.jss.2022.111574

Cited by 17 publications

(5 citation statements)

References 21 publications

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“…The Robot Operating System (ROS) is an open-source tool for developing a wide variety of robotic systems grouped into mobile and fixed types. Whether the robot is one type or the other requires general software capabilities, such as communication with external devices, updated libraries and packages, and an accessible programming environment [22]. Another critical aspect of the ROS is its growing impact on professional and academic robotics since there are updated open-source packages and accessible examples online [23].…”

Section: Ros Autonomous Mobile Robotsmentioning

confidence: 99%

Path Planning for Autonomous Mobile Robot Using Intelligent Algorithms

Galarza-Falfan,

García-Guerrero,

Aguirre-Castro

et al. 2024

Technologies

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Machine learning technologies are being integrated into robotic systems faster to enhance their efficacy and adaptability in dynamic environments. The primary goal of this research was to propose a method to develop an Autonomous Mobile Robot (AMR) that integrates Simultaneous Localization and Mapping (SLAM), odometry, and artificial vision based on deep learning (DL). All are executed on a high-performance Jetson Nano embedded system, specifically emphasizing SLAM-based obstacle avoidance and path planning using the Adaptive Monte Carlo Localization (AMCL) algorithm. Two Convolutional Neural Networks (CNNs) were selected due to their proven effectiveness in image and pattern recognition tasks. The ResNet18 and YOLOv3 algorithms facilitate scene perception, enabling the robot to interpret its environment effectively. Both algorithms were implemented for real-time object detection, identifying and classifying objects within the robot’s environment. These algorithms were selected to evaluate their performance metrics, which are critical for real-time applications. A comparative analysis of the proposed DL models focused on enhancing vision systems for autonomous mobile robots. Several simulations and real-world trials were conducted to evaluate the performance and adaptability of these models in navigating complex environments. The proposed vision system with CNN ResNet18 achieved an average accuracy of 98.5%, a precision of 96.91%, a recall of 97%, and an F1-score of 98.5%. However, the YOLOv3 model achieved an average accuracy of 96%, a precision of 96.2%, a recall of 96%, and an F1-score of 95.99%. These results underscore the effectiveness of the proposed intelligent algorithms, robust embedded hardware, and sensors in robotic applications. This study proves that advanced DL algorithms work well in robots and could be used in many fields, such as transportation and assembly. As a consequence of the findings, intelligent systems could be implemented more widely in the operation and development of AMRs.

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Section: Ros Autonomous Mobile Robotsmentioning

confidence: 99%

Path Planning for Autonomous Mobile Robot Using Intelligent Algorithms

Galarza-Falfan,

García-Guerrero,

Aguirre-Castro

et al. 2024

Technologies

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“…Two different design environments were used. The first is the robot operating system (ROS) 34 which is an open-source framework that provides standard services such as hardware abstraction, low-level device control, implementation of commonly used functionality, message passing between processes, and package management. It is essential that ROS have a complete source code that is accessible to everyone.…”

Section: Wheeled Quadrotor Designmentioning

confidence: 99%

Quadrotor with wheels: design and experimental evaluation

Aizelman,

Magazinnik,

Feldman

et al. 2024

Sci Rep

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Quadrotors have found widespread use in indoor applications, including tracking and mapping. In general, to carry out such tasks effectively, a navigation solution should provide both accuracy and battery efficiency. To achieve both, we propose a cost-effective and lightweight wheeled quadrotor that combines both driving and flying capabilities. Our design allows the quadrotor to perform both functions seamlessly. We provide a detailed description of the design and construction process, highlighting its advantages. Our focus was on the Tello quadrotor, which weighs 80 grams. Our design allowed driving capability with an increased weight of only fifteen grams, resulting in less than 20% of the added weight. Furthermore, we evaluate the quadrotor’s pure inertial navigation performance and corresponding battery consumption by employing various flying and driving patterns. Our results show that when only driving the battery consumption was the lowest with 10% and some flying scenarios improve the positioning error by more than 70%.

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“…In more recent years, numerous research papers have been devoted to the evaluation of ROS2 performance related to various aspects: DDS, security, and distributed robotic systems. Without claiming to be exhaustive (a mapping of software engineering research on ROS can be found in [32]), several attempts to clarify DDS issues can be found in [33], which conducted analyses on ROS2 and several DDS providers. The authors of [34] evaluated the response time of processing chains in ROS2, and a latency analysis of ROS2 was provided in [35].…”

Section: Ros2: Origin and Performance Analysismentioning

confidence: 99%

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

Bonci,

Gaudeni,

Giannini

et al. 2023

Applied Sciences

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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.

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Software engineering research on the Robot Operating System: A systematic mapping study

Cited by 17 publications

References 21 publications

Path Planning for Autonomous Mobile Robot Using Intelligent Algorithms

Path Planning for Autonomous Mobile Robot Using Intelligent Algorithms

Quadrotor with wheels: design and experimental evaluation

Robot Operating System 2 (ROS2)-Based Frameworks for Increasing Robot Autonomy: A Survey

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