David Apolinar Guerra-Zubiaga

The robotic exploration of space began only five decades ago, and yet in the intervening years, a wide and diverse ecosystem of robotic explorers has been developed for this purpose. Such devices have greatly benefited from miniaturization trends and the increased availability of high-quality commercial off-the-shelf (COTS) components. This review outlines the specific taxonomic distinction between planetary surface rovers and other robotic space exploration vehicles, such as orbiters and landers. Additionally, arguments are made to standardize the classification of planetary rovers by mass into categories similar to those used for orbital satellites. Discussions about recent noteworthy trends toward the miniaturization of planetary rovers are also included, as well as a compilation of previous planetary rovers. This analysis compiles relevant metrics such as the mass, the distance traveled, and the locomotion or actuation technique for previous planetary rovers. Additional details are also examined about archetypal rovers that were chosen as representatives of specific small-scale rover classes. Finally, potential future trends for miniature planetary surface rovers are examined by way of comparison to similar miniaturized orbital robotic explorers known as CubeSats. Based on the existing relationship between CubeSats and their Earth-based simulation equivalents, CanSats, the importance of a potential Earth-based analog for miniature rovers is identified. This research establishes such a device, coining the new term ‘CanBot’ to refer to pathfinding systems that are deployed terrestrially to help develop future planetary surface exploration robots. Establishing this explicit genre of robotic vehicle is intended to provide a unified means for categorizing and encouraging the development of future small-scale rovers.

The integration of digital twin software solutions with industrial collaborative robotics applications has gained significant attention due to its potential to enhance operational efficiency in various industries. The authors of this paper provide a comprehensive review of the literature, analyzing the benefits, challenges, and opportunities associated with this unification. The research methodology incorporates both quantitative and qualitative analyses of relevant scholarly articles, case studies, and industry reports. The study identifies research gaps and challenges, including data management, security, scalability, interoperability, and transitioning simulations to digital twins. To address these gaps, the authors explore published frameworks for effectively integrating digital twin software solutions with industrial collaborative robotics applications. An important challenge is to define some tools to develop a digital twin. This paper explores the tools implemented by other researchers to develop a digital twin. The findings of this research contribute to a deeper understanding of the combination of digital twins and collaborative robots, paving the way for improved operational efficiency and informed decision-making.

This review article comprehensively delves into the rapidly evolving field of domain adaptation in computer and robotic vision. It offers a detailed technical analysis of the opportunities and challenges associated with this topic. Domain adaptation methods play a pivotal role in facilitating seamless knowledge transfer and enhancing the generalization capabilities of computer and robotic vision systems. Our methodology involves systematic data collection and preparation, followed by the application of diverse assessment metrics to evaluate the efficacy of domain adaptation strategies. This study assesses the effectiveness and versatility of conventional, deep learning-based, and hybrid domain adaptation techniques within the domains of computer and robotic vision. Through a cross-domain analysis, we scrutinize the performance of these approaches in different contexts, shedding light on their strengths and limitations. The findings gleaned from our evaluation of specific domains and models offer valuable insights for practical applications while reinforcing the validity of the proposed methodologies.

The manufacturing industry recognizes drilling operations as a significant portion of production, often accounting for a substantial part of overall costs. In the transformative wave of Industry 4.0, new technologies have emerged, presenting remarkable opportunities to enhance machining processes. Thus,this study integrates digital twins (DT) technology to refine drilling operations. Within this framework, a robot actively executed drilling tasks, with the DT closely monitoring and regulating the drilling speed. This research further established a connectivity bridge that facilitates synchronizing the virtual system with the operational process. The article presents a Design of Experiments (DOE) in a virtual simulation space to analyze the impact of various parameters. This approach aimed to pinpoint the robot joints wielding the most significant influence on the comprehensive drilling operations sequence. The findings underscored that the J4 joint of the FANUC robot model M-16iB/20 stood out as a critical contributor to the process, influencing it by an impressive margin of 16%. This research demonstrates a promising avenue for harnessing digital twin technology to streamline and optimize manufacturing production, setting a precedent for future explorations in the field.

This paper reports on the development of a novel soft robotic system for remote ultrasound applications. Direct contact of the ultrasound probe with the patient's body represents a safety risk and therefore control of the probe's positioning and applied force is a crucial task. The proposed robot uses a passive control system that provides safe interaction between the robot and the patient by leveraging soft robotics technology. The soft robot's structure can be considered as a nonlinear spring which can be designed to exert a safe force within the robot's workspace to guarantee the safety of human–robot interaction. The literature suggests that effective ultrasound imaging of both the heart and abdomen requires six degrees-of-freedom. These degrees-of-freedom consist of three translational motions, which are achieved using a novel hybrid soft cable-driven parallel robot, and three wrist motions, which is based on a universal joint design. The experimental results show that the robot can achieve all these six degrees-of-freedom, and its blocking force can be engineered to generate a uniform force within the workspace.

Robotics and automation have been a growing area within K–12 educational institutions for the past decade. Across secondary educational institutions, students are introduced to robotics in classes, after-school clubs, and competition leagues through various educational platforms, vendors, and kits. Robotics was initially implemented in schools to help drive more interest in STEM through hands-on application of mechanical, electrical, structural, and computer engineering concepts. Recently, the trend of K–12 robotics has become very niche, focusing more on mobile robotics or robotics competitions. Because of this trend, students have limited exposure to emerging technological advances, such as those found in Industry 4.0. Exciting technological areas, such as digital twins, are not covered in curricula, and this lack of exposure negatively influences the direction of student interest in the “T” and “E” of STEM, with many students never pursuing computer science, technology, or robotics in higher education. The primary goal of this research is to provide a methodology to expose secondary students to Industry 4.0 technologies by leveraging accessible technologies, such as Unity and the Robot Operating System (ROS), to develop a low-cost, high-fidelity digital twin of a pick-and-place robot in a smart warehouse operation. This digital twin prototype will help students to learn about Industry 4.0 trends, such as next-generation automation systems, digital twins, digital manufacturing, intelligent automation, and additive manufacturing, using ROS–Unity integration and hardware accessible to secondary schools to simulate a pick-and-place robotic application. By harnessing the accessibility of Unity and ROS to create a low-cost digital twin prototype for a secondary school, this research has a secondary goal of improving the pipeline of students interested in pursuing STEM-related learning in higher education, thereby ensuring a future STEM workforce that can research, design, develop, operate, and maintain the systems and technologies of Industry 4.0.

With technological developments on the rise, the manufacturing industry acknowledges that it is not only important to integrate instruments, controls, and robots, but that it is also essential to connect these elements to people in order to achieve future automation. Whether in an operating room where a surgeon uses machines to save lives, or in an earthquake disaster zone where an

Industrial Internet of Things (IIOT) is currently developing as an important manufacturing paradigm with active contemporary research exploring its trends in enhancing Industry 4.0 on a global scope. Manufacturing encompasses a broad umbrella of technologies with this work focusing specifically on process control implementation through IIOT along Industry 4.0 trends. With the vast