A Domain-Specific Language for the Development of Heterogeneous Multi-robot Systems

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.

This paper presents a new approach, model theory approach, to small and medium scale transaction processing system (TPS) development. A TPS of this paper is an information system designed to process day-to-day business event data at operational level of an organization. The paper is not concerned with data base construction but with transaction processing. The model theory approach is not a software engineering approach but a systems theory approach. In the approach a model of the target system, which is called a user model, is constructed in set theory using a formal system structure of a TPS. The user model is, then, compiled into an extended Prolog (extProlog) model. The extProlog is an extension of Prolog to meet requirements for management information system development. On compilation a standardized user interface (UI) called internal UI is attached. The extProlog model with the internal UI is, then, executed under control of another standardized UI called an external UI. Implementation is an integral part of the approach. Because the UIs are designed for the formalized (abstract) structure of a TPS, they can be standardized and are provided as black box components to system development. Because a systems developer is required to only build a user model in set theory based on a model theoretic structure in the approach, it is called a model theory approach. Advantages of this approach are that it provides a theoretical structure to information systems development so that systems development can be made an engineering discipline, and facilitates rapid systems development.

Real world virtual world communication and interaction will be a cornerstone of future intelligent manufacturing ecosystems. Human robotic interaction is considered to be the basic element of factories of the future. Despite the advancement of different technologies such as wearables and Augmented Reality (AR), human-robot interaction (HRI) is still extremely challenging. Whilst progress has been made in the development of different mechanisms to support HRI, there are issues with cost, naturalistic and intuitive interaction, and communication across heterogeneous systems. To mitigate these limitations, RoSTAR is proposed. RoSTAR is a novel open-source HRI system based on the Robot Operating System (ROS) and Augmented Reality. An AR Head Mounted Display (HMD) is deployed. It enables the user to interact and communicate through a ROS powered robotic arm. A model of the robot arm is imported directly into the Unity Game engine, and any interactions with this virtual robotic arm are communicated to the ROS robotic arm. This system has the potential to be used for different process tasks, such as robotic gluing, dispensing and arc welding as part of an interoperable, low cost, portable and naturalistically interactive experience.

This paper presents a system designed to cooperatively track and share the information about moving objects using a multi-robot team. Every robot of the team is fitted with a different omnidirectional vision system running at different frame rates. The information gathered from every robot is broadcast to all the other robots and every robot fuses its own measurements with the information received from the teammates, building its own "vision of the world". The cooperation of the vision sensors enhances the capabilities of the single vision sensor. This work was implemented in the RoboCup domain, using our team of heterogeneous robot, but the approach is very general and can be used in any application where a team of robot has to track multiple objects. The system is designed to work with heterogeneous vision systems both in the camera design and in computational resources. Experiments in real game scenarios are presented.

Human Robot Interaction (HRI) is one of the biggest research field in the Robotics research world. Understanding the semantic meaning of the user instruction is very important to establish the communication between user and robot. When a user instructs to all heterogeneous service Robots with high level instructions who are working at different locations in smart house, all robots need to operate by understanding the semantic of the instruction and complete the task uniformly without considering underline software and hardware implementations. Ontology is used to extract the semantic meaning of the instructions. Each robot is assigned a specific task for specific time period for each day. User can issue commands to all robots at different time slots but the same command can be issued with different sentence by different users. We have used ontology to represents the semantic of the sentence with different commands. We have used three robots (TurtleBot, TiaGo and Husky) for our experiment in Gazebo simulator. Robot Operating System (ROS) is the middleware which is hiding more complex implementation of different functions for different robots and provide the interoperability for heterogeneous robot operations. The ROS nodes and topics can be different for different robots, therefore our implementation can solve this issue by autonomous robot registration algorithm which is working with Robot ontology.

This paper covers design and implementation of monitoring system using unmanned vehicle to monitor the spread of hazardous chemical gas. This system is applicable to wide variety of unmanned vehicles ranging from ground vehicles to aerial vehicles. It can also be implemented with multi-vehicle concept. In a simple scenario, the system uses chemical sensor to measure and monitor level of hazardous chemical gas in a specified region explored by the unmanned vehicles. Then the measurement is sent to a computer in Ground Control Station (GCS) to be visualized on 2D virtual map in real-time. In addition to data visualization, the system also provides data logging saved in a CSV file for further data processing. Users can control the vehicles remotely with a user interface in the GCS as well. This monitoring system is developed and implemented in Robot Operating System (ROS) and open source software QgroundControl (QGC). Data acquisition and communication between the vehicle and the GCS are implemented in ROS, whereas the visualization system is developed from well-known flight control user interface named QGC. Implementation of this system shows that it is successfully tested to visualize hazardous chemical gas on a 2D virtual map in real-time.

The paper presents a framework for interactive control of multi robots using mixed reality interfaces. The proposed approach can operate with both single and multi-robot systems, including interaction with industrial manipulators, mobile robots, and unmanned aerial vehicles (UAV). The human–robot interface allows both interactive and physical interaction with the robot. Particular attention is paid to a visualisation of the robots' intent during control. The presented framework has Robotic Operation System (ROS) as a core that can be connected to any robot and mixed reality interface. This allows us to make framework scalable and connect several different mixed reality devices and multiple heterogeneous robots. In the implementation part we connected our framework with Microsoft HoloLens, collaborative robot KUKA IIWA, mobile platform Plato, UAV designed on the basis of dji f450. The proposed framework was tested experimentally with real experimental setups mentioned above. The results showed the capabilities of the mixed reality system for interactive control of different robots' type.

Multi robot systems are defined as a collection of two or more robots that are capable of working autonomously while coordinating with each other. Three challenges emerge while designing any multi robot system. The robots have to coordinate their path planning or trajectory planning in order to avoid collision during the course of navigation, while collaborating tasks with other robots to achieve a specific end goal for the system. The other challenge, which is the focus of this paper, is the security of the entire multi robot system. Since robots have to coordinate with each other, any one of them being malicious due to any kind of security threat, can lead to a chain reaction that may compromise the entire system. Such security threats can be fatal if not dealt with immediately. This paper proposes the use of a Hybridized Blockchain Model (HBM) to identify such security threats and take necessary actions in real time so that the system does not encounter any catastrophic failure. The proposed security architecture uses ROS (Robot operating system) to decentralize the information collected by robot clients and HBM to monitor the clients and take necessary real time actions.

In this paper, we present the development of the Multiple Robotic Fish cooperation System (MRFS), which is built on the basis of a series of radio-controlled, multi-link biomimetic fish-like robots designed in our lab. The motivation of this work is that the capability of one single fish robot is often limited while there are many complex missions which should be accomplished by effective cooperation of multiple fish robots. MRFS, as a novel test bed for multiple robotic fish cooperation, can be applied to different types of complex tasks. More importantly, MRFS provides a platform to test and verify the algorithms and strategies for cooperation of multiple underwater mobile robots. We use a disk-pushing task as an example to demonstrate the performance of MRFS.

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.

The primary essence of storyboarding, reducing complexity in uncertain environments and creating an early visualization of complex system, makes it one of innovative requirement elicitation techniques. Based on the initial sketchy requirements, an abstract level storyboard may be created depicting user interactions with distinct scenes and scenarios for web-based User Interfaces (UI). Multiple rounds of elicitations and storyboards creations will develop initial sketchy storyboard into a refined depiction of user needs. The advent of Model-Driven Software Engineering (MDSE) and Model-Driven Architecture (MDA), as against code centric approaches, presents an abstract view of software products in the shape of models as primary artifacts for automated design development and implementation. In this article, the concepts of Storyboarding and Metamodeling are merged to introduce a Storyboard Metamodel regarding Web-based UI. This leads to automatically develop an evolutionary prototype of a given system from initial requirements. The application of proposed meta-model is demonstrated through a web application case study. The results prove that the proposed meta-model is capable of generating both simple as well as complex storyboards that can be transformed to evolutionary prototype of a given system.

With the rapid advancement of unmanned aerial vehicle (UAV) technologies, drone swarms have been increasingly adopted in applications ranging from agriculture and logistics to defense and performance arts. However, conventional swarm control architectures, predominantly centralized, remain limited in scalability, adaptability, and robustness under dynamic conditions. To address these limitations, this study presents a bio-inspired formation control framework that integrates decentralized coordination and autonomous role assignment. The proposed system incorporates a reference–follower mechanism, enabling drones to dynamically select reference units based on spatial proximity, thereby enhancing inter-drone interaction and formation stability. Furthermore, a hybrid communication architecture based on Robot Operating System (ROS) and Message Queuing Telemetry Transport (MQTT) protocols is developed to overcome the constraints of traditional ROS communication frameworks and improve scalability. Finally, simulation and real-world flight experiments validate the proposed approach, demonstrating significant improvements in formation flexibility, communication efficiency, and adaptive leader switching compared to conventional leader–follower and virtual structure models.

Robotic swarm has been a hot topic in recent years. In robotic swarms, a team of network enabled bots are dispatched to some areas to fulfill certain tasks, such as military actions and chemical substance tracking. However, how to monitor, control, and coordinate swarms in a real-time manner such th

This proposal is about a study we recently published in the IEEE Transaction of Software Engineering journal [4]. Context: Collaborative software engineering (CoSE) deals with methods, processes and tools for enhancing collaboration, communication, and co-ordination (3C) among team members [5]. CoSE can be employed to conceive different kinds of artifacts during the development and evolution of software systems. For instance, when focusing on software design, multiple stakeholders with different expertise and responsibility collaborate on the system design. Model-Driven Software Engineering (MDSE) provides suitable techniques and tools for specifying, manipulating, and analyzing modeling artifacts including metamodels, models, and transformations [1]. Collaborative MDSE consists of methods or techniques in which multiple stakeholders manage, collaborate, and are aware of each others' work on a set of shared models. A collaborative MDSE approach is composed of three main complementary dimensions: (i) a model management infrastructure for managing the life cycle of the models, (ii) a set of collaboration means for allowing involved stakeholders to work on the modelling artifacts collaboratively, and (iii) a set of communication means for allowing involved stakeholders to exchange, share, and communicate information within the team. Collaborative MDSE is attracting several research efforts from different research areas (e.g., model-driven engineering, global software engineering, etc.), resulting in a variegated scientific body of knowledge on the topic. Objective: In this study we aim at identifying, classifying, and understanding existing collaborative MDSE approaches. More specifically, our goal is to assess (i) the key characteristics of collaborative MDSE approaches (e.g., model editing environments, model versioning mechanisms, model repositories, support for communication and decision making), (ii) their faced challenges and limitations, and (iii) the interest of researchers in collaborative MDSE approaches over time and their focus on the three dimensions of collaborative MDSE. Method: In order to achieve this, we designed and conducted a systematic mapping study [6] on collaborative MDSE. Starting from over 3,000 potentially relevant studies, we applied a rigorous selection procedure [3] resulting in 106 selected papers, further clustered into 48 primary studies, along a time span of nineteen years. A suitable classification framework has been empirically defined and rigorously applied for extracting key information from each selected study. We collated, summarized, and analyzed extracted data by applying scientifically sound data synthesis techniques. Results: In addition to a number of specific insights, our analysis revealed the following key findings: (i) there is a growing scientific interest on collaborative MDSE in the last years; (ii) multi-view modeling, validation support, reuse, and branching are more rarely covered with respect to other aspects about collaborative MDSE; (iii) different primary studies focus differently on individual dimensions of collaborative MDSE (i.e., model management, collaboration, and communication); (iv) most approaches are language-specific, with a prominence of UML-based approaches; (v) few approaches support the interplay between synchronous and asynchronous collaboration. Conclusion: This study gives a solid foundation for a thorough identification and comparison of existing and future approaches for collaborative MDSE [2]. Those results can be used by both researchers and practitioners for identifying existing research/technical gaps to attack, better scoping their own contributions to the field, or better understanding or refining existing ones.

The application of autonomous mobile robots in robotic security platforms is\nbecoming a promising field of innovation due to their adaptive capability of\nresponding to potential disturbances perceived through a wide range of sensors.\nResearchers have proposed systems that either focus on utilizing a single\nmobile robot or a system of cooperative multiple robots. However, very few of\nthe proposed works, particularly in the field of multi-robot systems, are\ncompletely dependent on LiDAR sensors for achieving various tasks. This is\nessential when other sensors on a robot fail to provide peak performance in\nparticular conditions, such as a camera operating in the absence of light. This\npaper proposes a multi-robot system that is developed using ROS (Robot\nOperating System) for intruder detection in a single-range-sensor-per-robot\nscenario with centralized processing of detections from all robots by our\ncentral bot MIDNet (Multiple Intruder Detection Network). This work is aimed at\nproviding an autonomous multi-robot security solution for a warehouse in the\nabsence of human personnel.\n