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Errors in Cyber-Physical Systems present a major problem given the current state of technological complexity. Self-diagnosis can contribute to address it, being the standpoint of the present paper. Hence, an application of exploratory Machine Learning models to assess the functioning of robot software in order to identify anomalies that lead to low performance is proposed. More precisely, Hybrid Unsupervised Exploratory Plots (HUEPs) are extended through density-based clustering techniques, that are applied together with unsupervised exploratory projection models. As a result, intuitive and informative visualizations of software performance are obtained, supporting the monitoring and anomaly detection tasks. The proposed clustering extension of HUEPs is thoroughly validated on a massive and up-to-date open dataset, obtaining promising results. [ABSTRACT FROM AUTHOR]

In recent years, ROS (Robot Operating System) packages have become increasingly popular as a type of software artifact that can be effectively reused in robotic software development. Indeed, finding suitable ROS packages that closely match the software's functional requirements from the vast number of available packages is a nontrivial task using current search methods. The traditional search methods for ROS packages often involve inputting keywords related to robotic tasks into general-purpose search engines (e.g., Google) or code hosting platforms (e.g., GitHub) to obtain approximate results of all potentially suitable ROS packages. However, the accuracy of these search methods remains relatively low because the task-related keywords may not precisely match the functionalities offered by the ROS packages. To improve the search accuracy of ROS packages, this paper presents a novel semantic-based search approach that relies on the semantic-level ROS Package Knowledge Graph (RPKG) to automatically retrieve the most suitable ROS packages. Firstly, to construct the RPKG, we employ multi-dimensional feature extraction techniques to extract semantic concepts, including code file name, category, hardware device, characteristics, and function, from the dataset of ROS package text descriptions. The semantic features extracted from this process result in a substantial number of entities (32,294) and relationships (54,698). Subsequently, we create a robot domain-specific small corpus and further fine-tune a pre-trained language model, BERT-ROS, to generate embeddings that effectively represent the semantics of the extracted features. These embeddings play a crucial role in facilitating semantic-level understanding and comparisons during the ROS package search process within the RPKG. Secondly, we introduce a novel semantic matching-based search algorithm that incorporates the weighted similarities of multiple features from user search queries, which searches out more accurate ROS packages than the traditional keyword search method. To validate the enhanced accuracy of ROS package searching, we conduct comparative case studies between our semantic-based search approach and four baseline search approaches: ROS Index, GitHub, Google, and ChatGPT. The experiment results demonstrate that our approach achieves higher accuracy in terms of ROS package searching, outperforming the other approaches by at least 21% from 5 levels, including top1, top5, top10, top15, and top20. [ABSTRACT FROM AUTHOR]

Nowadays, robots are widely applied in life as well as industrial production, medicine, rescue, learning, and entertainment. There are many kinds of robots using different modern technologies such as manipulators, movement, and biomimetic robots; each type is applied according to its own role. Robots are also applied in training, especially in STEM training implemented with mobile robots. In this paper, we proposed models to design mobile robot combined with Android OS Tablet with a user interaction screen, voice control model, and AIDL IPC interactive model for remote control. We research the mobile robot using RockChip AI Processor RK3399Pro, which focuses on understanding the structure and operating mechanism of the AI Processor that RockChip robot uses, along with researching Android with IPC AIDL architecture and Automatic Voice Recognition technology to control robot to turn left, turn right, move forward, backward, and stop the movement by voice with three languages: Korean, English, and Vietnamese. We experimented on 1850 recording audio files including 1013 female voices and 837 male voices with 'latest_short,' 'latest_long,' and 'command_and_search' models. The results obtained a fairly high average confidence of 95% for English and Vietnamese languages and 87% for Korean. From results of this study, it will serve as a foundation for the research and development of a system to support students in learning by interacting with mobile robots through voice with multi-language. STEM education in the form of gamification of the curriculum, especially for extensive research on training programs can be applied in mobile robots with more flexibility. [ABSTRACT FROM AUTHOR]

In a Robot Operating System (ROS) application, robot software is often distributed across multiple networked components, forming the ROS network, where every component acts as server and/or a client, and publishing and/ or receiving robot data simultaneously. For indoor robots, a local ROS network, through a Wi-Fi hotspot, is sufficient. But for outdoor robots, a remote ROS network is needed to connect the ROS application to the cloud. Although a number of cloud-based solutions support this, implementing them is challenging, as they need to be configured to facilitate ROS's unique, multidirectional, and simultaneous flow of robot data. This article presents Port Forwarding as an alternative approach, which offers a private, secured, and a direct ROS-to-ROS, eliminating the need for a dedicated middleware and its configuration and setup complexities. But Port Forwarding has its own challenges; chiefly, the beforehand knowledge of Internet addresses of all networked components and the need to update port forwarding settings when these addresses change, which they often do. This article addresses this issue (and others) and presents a detailed procedure for setting Port Forwarding for ROS applications, highlighting configuration, and troubleshooting steps. Also, the article compares between Port Forwarding and cloud-based solutions, in terms of setup, performance, and others. Results show that robot performance under Port Forwarding is on par with cloud-based solutions, but it required a fraction of setup time. The authors developed a set of shell scripts that monitor the Internet addresses of all networked components and auto-update Port Forwarding settings when they change, solving this issue. With this, Port Forwarding could be considered a viable option for ROS system networks, on par with cloud-based solutions. [ABSTRACT FROM AUTHOR]

A beam-to-column connection design and results of engineer calculations using Autodesk's Robot Structural analysis are shown in the article. Two types of connections, bolted and welded, were calculated. The tensile resistance amounted to 912.74 kN, bending resistance to 100.87 kN⋅m and effective design capacity of the bolt amounted to 27.69 kN. Normal stress in the weld amounted to σ⊥max = τ⊥max 72.72 MPa, in the vertical weld to σ⊥ = τ⊥ = 63.34 MPa and tangent stress amounted to τ|| = 4.37 MPa. The results allowed us to implement minor changes such as increasing the distance between the bolt and the edge and decreasing the size of the fillet welds. The design is fully compliant with the EN 1993-1-8 norm. Using Robot Structural Analysis substantially increased the pace of calculations giving precise and clear outcomes. [ABSTRACT FROM AUTHOR]

A component is a reusable and replaceable software module accessed through its interface. Component-based development is expected to shorten the development period, reduce maintenance costs, and improve program reusability and the interoperability of components. This paper proposes a new robot software component platform in order to support the entire process of robot software development. It consists of specifications of a component model, component authoring tool, component composer, and component execution engine. To show its feasibility, this paper presents the analysis results of the component's communication overhead, a comparison with other robotic software platforms, and applications in commercial robots. [ABSTRACT FROM AUTHOR]

Robots are an integral part of today's industrial scenario. As a result, simulation has evolved as a major tool in the programming and the design of robots. Simulation in this sense includes actually having a computer draw conclusions about the workings of a system. These conclusions are derived from the knowledge already possessed about the system in question. It is, in effect, a knowledge based process that utilizes the information stored about a particular system in the database to predict its response to the various situations. Robot software is the collection of computer programs and related information that is developed, marketed, manufactured and sustained for industrial robots. Consequently, the software for industrial robots is best seen from three points of view: operation; application; and manufacturing. [ABSTRACT FROM PUBLISHER]