Development Of Robot Technology Research Articles

Design and development of robotic technology through microcontroller system with machine learning techniques

Through the integration of AI and IoT, the digital twin transforms industrial sectors by virtually portraying physical systems. Simulation and the application of lifecycle management improve decision-making. In this paper, a virtual prototype system a digital twin framework that integrates robotic devices is proposed. Created using debugging platforms, they track every robotic activity, supported by real-time microcontroller structural design systems. Machine learning methods are the fundamental engine of the digital twin system. Because of this connection, robotic actions may be seamlessly controlled and monitored, guaranteeing effectiveness and adaptability in changing contexts. Robotics has advanced significantly with the combination of digital twin technology, machine learning, and microcontroller systems, offering improved performance and versatility in a range of applications.

Robot control system based on deep learning and RPA

Robots can help people complete repetitive and high-risk tasks, such as industrial production, medical care, environmental monitoring, etc. The control system of robots is the key to their ability to complete tasks, and studying robot control systems is of great significance. This article used Convolutional Neural Network (CNN) and Robotic Process Automation (RPA) technologies to optimize and train the robot control system and constructed a robot control system. This article conducts perception and decision-making experiments and execution experiments in the experimental section. According to the experimental results, it can be concluded that the average image recognition accuracy of the robot control system in perception and decision-making experiments was 94.62%. The average decision accuracy was 87.5%, and the average time efficiency was 176 seconds. During the execution of the experiment, the deviation of the motion trajectory shall not exceed 5 cm, and the oscillation amplitude shall not exceed 6°; the distance from the obstacle shall not exceed 20 cm, and the movement speed shall not exceed 0.6 m/s; the operating time shall not exceed 25 hours, and the number of faults shall not exceed 0.2 times per hour, all within the normal range. The robot control system based on Deep Learning (DL) and RPA has broad application prospects and research value, which would bring new opportunities and challenges to the development and application of robot technology.

Application of entertainment virtual technology based on network information resources in piano teaching

With the rapid development of digital technology, e-learning and robot technology are gradually applied in various fields. As an innovative form of traditional piano education, digital piano teaching is faced with the challenge of how to improve the learning effect and add interest. The purpose of this study is to explore the application of e-learning and virtual robot technology in digital piano teaching, so as to provide an effective teaching method and improve the learning experience and effectiveness of learners. This paper uses e-learning platform and virtual technology software to create a virtual piano learning environment. Through robotics, interaction with learners is achieved to simulate a real piano teacher. Design appropriate teaching content and assessment methods to ensure that learners can fully understand and master relevant knowledge and skills. The results show that the digital piano teaching method using e-learning and robot virtual technology can effectively improve learners' interest and participation, improve their piano playing skills and music understanding ability. Learners give positive evaluation to this new teaching method, and think that it is highly practical and innovative.

Towards sensory substitution and augmentation: Mapping visual distance to audio and tactile frequency.

Multimodal perception is the predominant means by which individuals experience and interact with the world. However, sensory dysfunction or loss can significantly impede this process. In such cases, cross-modality research offers valuable insight into how we can compensate for these sensory deficits through sensory substitution. Although sight and hearing are both used to estimate the distance to an object (e.g., by visual size and sound volume) and the perception of distance is an important element in navigation and guidance, it is not widely studied in cross-modal research. We investigate the relationship between audio and vibrotactile frequencies (in the ranges 47-2,764 Hz and 10-99 Hz, respectively) and distances uniformly distributed in the range 1-12 m. In our experiments participants mapped the distance (represented by an image of a model at that distance) to a frequency via adjusting a virtual tuning knob. The results revealed that the majority (more than 76%) of participants demonstrated a strong negative monotonic relationship between frequency and distance, across both vibrotactile (represented by a natural log function) and auditory domains (represented by an exponential function). However, a subgroup of participants showed the opposite positive linear relationship between frequency and distance. The strong cross-modal sensory correlation could contribute to the development of assistive robotic technologies and devices to augment human perception. This work provides the fundamental foundation for future assisted HRI applications where a mapping between distance and frequency is needed, for example for people with vision or hearing loss, drivers with loss of focus or response delay, doctors undertaking teleoperation surgery, and users in augmented reality (AR) or virtual reality (VR) environments.

Reinforcement Learning-Based Simulation of Seal Engraving Robot in the Context of Artificial Intelligence

The rapid development of robotics technology has made people's lives and work more convenient and efficient. The research and simulation of robots combined with reinforcement learning intelligent algorithms have become a hotspot in various fields of robot applications. In view of this, this study is based on deep reinforcement learning convolutional neural networks, combined with point cloud models, proximal strategy optimization algorithms, and flexible action evaluation algorithms. A seal cutting robot based on deep reinforcement learning has been proposed. The final results show that the descent speed of the seal cutting robot with the root mean square difference as the performance standard is about 1% faster than the flexible action evaluation algorithm. About 2% faster than the proximal strategy optimization algorithm. It is about 4% faster than the deep deterministic strategy gradient algorithm. This indicates that the research model has certain advantages in terms of actual accuracy after cutting. The fluctuation of this model is about 10% smaller than the evaluation of flexible actions and about 60% smaller than the gradient of deep deterministic strategies. Therefore, the research model has the highest overall stability without falling into local optima. In addition, compared to the near end strategy optimization algorithm, it falls into local optima, resulting in a low coincidence degree of about 17%. The deep deterministic strategy gradient algorithm has a large fluctuation amplitude during the seal cutting process, and the overall curve is relatively slow, with a final overlap of about 70%. The overlap degree of flexible action evaluation is slightly higher by about 83%. The maximum stability of the model's overlap is best around 90%. Through experiments, it can be found that the seal cutting robot proposed in the study based on deep reinforcement learning maintains certain advantages in performance indicators in various types of tests.

3D Printing Technology: Role in Safeguarding Food Security.

The rising threats to food security include several factors, such as population growth, low agricultural investment, and poor distribution systems. Consequently, food insecurity results from a confluence of issues, including diseases, processing limitations, and distribution deficiencies. Food insecurity usually occurs in vulnerable areas where certain technologies and traditional food safety testing are not a viable solution for foodborne disease detection. In this regard, 3D printing technologies and 3D printed sensors open the platform to produce portable, accurate, and low-cost sensors that address the gaps and challenges in food security. In this paper, we discuss the perspective role of 3D printed sensors in food security in terms of food safety and food quality monitoring to provide reliable access to nutritious, affordable food. In each section, we highlight the advantages of 3D printing technology in terms of cost-effectiveness, accuracy, accessibility, and reproducibility compared to traditional manufacturing methodologies. Recent developments in robotic technologies for mechanization, such as food handling with soft grippers, are also discussed. Lastly, we delve into the applications of advanced 3D printing technologies in agricultural monitoring, particularly the future of plant wearables, environmental sensing, and overall plant health monitoring.

Modified A* algorithm for path smoothing and obstacle avoidance

With the rapid development of robotics technology, path planning is a crucial aspect of autonomous robot systems. Among them, planning paths involves using the A* algorithm, which is a common method. However, traditional A* algorithm has several limitations in path planning, such as poor real-time performance, large amount of computation per node, long computation time, low algorithmic search efficiency. Based on this, two improved approaches for the A* algorithm are proposed. The first is expanding the obstacles in the map by increasing their expansion radius. The second is the Hybrid A* algorithm, which optimizes the A* algorithm by modifying its heuristic function. Specifically, the Hybrid A* algorithm combines two heuristic functions: one based on non-holonomic constraints and the other based on dynamic programming. Experimental tests are conducted under various map expansions and branching parameters to compare the performance of these two algorithms in terms of path length, execution time, and path smoothness at corners. The results demonstrate that, with smaller branching parameters, the Hybrid A* algorithm generates shorter paths. However, in highly complex mazes, the path length of the Hybrid A* algorithm may be longer, but it exhibits smoother movements at corners.

Single-port robotic subcostal major pulmonary resection using the single-port robotic system.

The da Vinci single-port system (SPS) (Intuitive Surgical, Sunnyvale, CA, USA) was designed for single-port (SP) surgery. Although we have reported our clinical outcomes using the SPS for a simple procedure in general thoracic surgery, major pulmonary resection had been performed only in cadaveric experiments to date. This study evaluated the feasibility of SP subcostal robotic major pulmonary resection using the SPS. Here, we present our initial clinical experience of SP subcostal robotic major pulmonary resection at our institution. Twenty-five patients with lung cancer underwent SP major subcostal pulmonary resection using the SPS between March and November 2022. Patient characteristics, intraoperative and perioperative outcomes were assessed. Questionnaires were used to evaluate patient satisfaction with the cosmetic results and quality of life through face-to-face or telephone interviews on postoperative day 30. All patients underwent major pulmonary resection with complete radical resection (R0). Nineteen patients underwent lobectomy, whereas six patients underwent segmentectomy. The mean docking time and total operative time were 4.16±1.19min (range, 2.3-7.8min) and 197.6±55.33min (range, 130-313min), respectively. No patients underwent conversion to open thoracotomy. One patient required an additional assistant port due to severe pleural adhesions. SP subcostal robotic major pulmonary resection using the SPS is feasible and safe. With the continuous development of robotic technology and surgical techniques, we believe that more complex general thoracic surgeries will be performed in the future using SPS.

The Application of CoppeliaSim EDU in Robot Course Teaching

CoppeliaSim EDU, as a powerful tool for robot teaching, is changing the traditional teaching mode. This software provides a comprehensive robot simulation environment where users can explore different scenarios, models, and programming interfaces to gain a deeper understanding of robot technology. Its advantage lies in reducing the cost and potential security risks of physical robots, making robot education more widespread and secure. In actual teaching, teachers can use CoppeliaSim EDU for course design, guide students to carry out robot programming and simulation experiments, and improve teaching effectiveness. Through case analysis, it can be found that using CoppeliaSim EDU can better stimulate students' interest in learning, improve their practical ability and innovative thinking. In the future, with the continuous development of robotics technology, the application prospects of CoppeliaSim EDU will be even broader, bringing more possibilities for robot education.

A novel parallel ant colony optimization algorithm for mobile robot path planning.

With the continuous development of mobile robot technology, its application fields are becoming increasingly widespread, and path planning is one of the most important topics in the field of mobile robot research. This paper focused on the study of the path planning problem for mobile robots in a complex environment based on the ant colony optimization (ACO) algorithm. In order to solve the problems of local optimum, susceptibility to deadlocks, and low search efficiency in the traditional ACO algorithm, a novel parallel ACO (PACO) algorithm was proposed. The algorithm constructed a rank-based pheromone updating method to balance exploration space and convergence speed and introduced a hybrid strategy of continuing to work and killing directly to address the problem of deadlocks. Furthermore, in order to efficiently realize the path planning in complex environments, the algorithm first found a better location for decomposing the original problem into two subproblems and then solved them using a parallel programming method-single program multiple data (SPMD)-in MATLAB. In different grid map environments, simulation experiments were carried out. The experimental results showed that on grid maps with scales of 20 $ \times $ 20, 30 $ \times $ 30, and 40 $ \times $ 40 compared to nonparallel ACO algorithms, the proposed PACO algorithm had less loss of solution accuracy but reduced the average total time by 50.71, 46.83 and 46.03%, respectively, demonstrating good solution performance.

Development of robot technology to contribute to 1F decommissioning (4)

Development of robot technology to contribute to 1F decommissioning (4)

Development of robot technology to contribute to 1F decommissioning (1)

Development of robot technology to contribute to 1F decommissioning (1)

Development of robot technology to contribute to 1F decommissioning (2)

Development of robot technology to contribute to 1F decommissioning (2)

Reconsidering the Meaning of ‘Visual Literacy’ in the Age of AI : Applications to Liberal Arts Education and Possible Extensions

Literacy is an important driving force when it comes to attaining a critical eye for the real world, as well as for analyzing problems in the past and making predictions for the future. Since literacy is evolving in a new paradigm for human lifestyles and abilities, in no small part thanks to the rapid development of AI(Artificial Intelligence) and robot technology, this study begins with a review of the change in the meaning of literacy. Next, we consider the meaning of ‘visual literacy’, in an era when AI reads and analyzes information such as images and texts, as well as visual recognition, voice recognition, and decision-making through algorithms, and creates art in a new way. The ultimate purpose of this study is to argue for the need to change the meaning of ‘visual literacy’ as a driving force for visual communication based on imagination in terms of technological utilization, critical thinking, and ethical social problem solving. Therefore, the content of this study emphasizes both a utopian and dystopian aesthetic vision, as well as critical thinking, in terms of potential and expandability of AI, rethinking the meaning of ‘visual literacy’ at the ethical level with human autonomous judgment and a sense of responsibility. The results of this study demonstrate the need for us to apply ‘visual literacy’ in a way that combines imagination and critical thinking, as well as our need to develop a new way of visual cognition necessary for the acquisition and use of digital technology in terms of the role of liberal arts education in universities. Through this study, I argue that the application of ‘visual literacy’ to foster democratic citizenship qualities can help us expand new possibilities for the role of liberal arts education in the era of AI by giving us the authority to understand and utilize digital media based on imagination for image and text information processing technology and visual communication.

Reform of Robotics Engineering Practice Teaching in Applied Undergraduate Colleges and Universities Based on OBE Education

The modern society has put forward higher level requirements for the development of robotics technology, which also puts forward new challenges to the teaching practice of robotics engineering majors in applied undergraduate colleges and universities. In this paper, guided by the concept of OBE education, we discuss the reform strategies for the practical teaching of robotics engineering majors in applied undergraduate colleges and universities from the three aspects of project-driven learning, focusing on diversified assessment, and being practice-oriented. Through the implementation of these reform measures, students' practical ability, teamwork ability and problem-solving ability can be better cultivated, and their application level in the field of robotics engineering can be enhanced.

Ethical Issues and Response Strategies of Intelligent Robot Technology

In response to the ethical issues arising from the development of intelligent robot technology, this paper first analyzes the ethical issues that have arisen in the development of intelligent robot technology from three aspects: the impact on the definition of human subjectivity, the impact on human creativity, and the impact on human privacy. Then, from the technical, institutional, and moral perspectives, targeted strategies are proposed to address ethical issues related to intelligent robot technology.

A technical evaluation of robots in hazardous professions

In recent years, the rapid development of robot technology has gradually led to the reality that humans are replaced by robots in dangerous occupations. However, in contrast to robots in other fields, robots in hazardous professions have a wide variety and complexity due to the low repeatability and high uncertainty of tasks, so they have specialized functions and no relative standard form. As a result, the eligibility criteria for evaluating this type of robot remain unclear. This paper focuses on two criteria that can be used to evaluate such robots and determine whether existing robots in hazardous professions meet these criteria. In order to find solutions to the issues, many papers related to rescue robots is reviewed, and important information is extracted and reintegrated to obtain the final results. In this paper, capability and practical acceptability are two evaluation criteria of robots in hazardous obtained. At the same time, it is judged that most of the existing robots meet both of the standards, but they expose a great number of defects when facing a more complex environment. This paper also provides several suggestions that might address the existing limitations.

A novel 3D vision-based robotic welding path extraction method for complex intersection curves

With the rapid development of robot technology, robotic welding technology has gradually been applied in the complex co-main intersection pipeline welding field. However, due to the existence of clamping errors and processing dimensional errors in intersecting pipes of the same specification, the actual welding path deviates from the taught path and cannot meet the accuracy requirements of robot welding, which further hinders the development and application of robotic welding in this field. To solve these problems, we propose a 3D vision-based robotic welding path extraction method for complex intersecting curves without programming and teaching. We begin by selecting the complex co-main intersection pipeline as the research object and building a robotic welding system based on 3D vision. Through mathematical analysis of the complex intersecting pipe model and an analysis of the internal coordinate transformation relationship within the welding system, we establish a mathematical model of the complex intersection curves at any clamping position in the manipulator coordinate system. On this basis, We propose a multi-view point cloud stitching method using Eye-in-Hand calibration and the ICP algorithm to obtain a complete co-main intersection pipeline point cloud. Subsequently, we propose a mathematical model parameter-solving algorithm based on the co-main intersection pipeline point cloud. Finally, the obtained actual parameters of the workpiece are combined with the established mathematical model to extract the welding path of the robot’s current position. Experimental results demonstrate that the proposed method can automatically extract welding seams for complex intersection curves without the need for programming and teaching.

Latest Developments in Robotic Percutaneous Coronary Interventions

Since the first robotic-assisted percutaneous coronary intervention procedure (R-PCI) was performed in 2004, there has been a steady evolution in robotic technology, combined with a growth in the number of robotic installations worldwide and operator experience. This review summarises the latest developments in R-PCI with a focus on developments in robotic technology, procedural complexity, tele-stenting and training methods, which have all contributed to the global expansion in R-PCI.

A study on the application of artificial intelligence in the design of intelligent medical robots

Abstract With the development of artificial intelligence and robotics technology, the combination of artificial intelligence and medical device research and development has been promoted, which is an important product of the development of artificial intelligence. In this paper, the general structure of the intelligent medical robot is designed by combining artificial intelligence technology and robotics-related technology. Then, the binocular vision function of the robot was realized by visually acquiring the image of the target object, 3D reconstruction of the target object, and combining the SIFT image recognition algorithm and target tracking algorithm. Then, a new speech recognition algorithm was constructed to realize the human-robot interaction function with the medical robot based on the deep learning Transforme network after the construction of the human acoustic model. Finally, the designed intelligent medical robot was tested, and its overall performance was evaluated. The results show that the recognition errors of the intelligent medical robot on the features of the items are all within 0.05, the recognition errors on the features of the human body are within 0.2, and the speed of the target tracking is between 6km/h and 16km/h. The average recognition accuracy of the medical robot for voice commands is about 0.9, the recognition time is about 0.7s, the normal working rate of each function is more than 0.99, and the test speed is within 2s.