Development Of Robot Research Articles

Design of a Novel Macro-Micro Integrated Brain Surgery Robot Based on Modular Parallel Mechanisms

The advancement and development of medical surgical robots have provided new technological support for brain surgery and neurosurgical procedures, improving the reliability of highly complex and precise surgeries. In turn, this urges the design and development of novel surgical robots to possess higher precision, stability, and enhanced motion capabilities. In response to this practical demand, this paper introduces a macro-micro integrated medical brain surgery robot system based on the concept of modular PMs (parallel mechanisms), which have a total of 13 active DOFs (degrees of freedom). This system divides the motion process of brain surgery into a large-scale macro-motion space and a small-scale high-precision motion space for design and planning control. The introduction of the design concept that combines multiple modular parallel sub-mechanisms has brought a significant level of decoupling characteristics to the mechanism itself. A comprehensive introduction and analysis of the surgical robot are provided, covering aspects such as design, kinematics, motion planning, and performance indicators. To address the pose allocation and coordination of motion between the macro platform and the micro platform, a pose allocation algorithm based on the decoupling and non-decoupling characteristics in various dimensions of the macro-micro platform is proposed. The designed measurement experiments have demonstrated that the repeatability in positioning accuracy of the macro and micro platform reaches the level of micron and submicron respectively. Practical experiments of motion control and simulated brain electrode implantation validate the excellent performance and stability of the entire surgical robot system. This research contributes innovative insights to the development of medical surgical robot systems, particularly in the domain of mechanism design.

Advancing Vegetable Grafting: A Comprehensive Review of Techniques, Challenges, and the Future of Automated Solutions

Vegetable grafting, a practice that combines two plant parts rootstock and scion into a single, superior plant, is an increasingly important technique in modern agriculture. By enhancing yields, stress resistance, and disease tolerance, grafting plays a crucial role in addressing challenges such as soil borne pathogens, extreme environmental conditions, and crop vulnerability to nematodes. Despite its benefits, vegetable grafting faces several challenges, including the need for compatible plant material, labour-intensive nursery production, high seed costs, and the potential for pathogen spread. Effective grafting requires meticulous selection of rootstock and scion, precise grafting techniques, and optimal post-grafting care to ensure survival and success. Looking toward the future, significant advancements in grafting technologies and nursery practices are required to overcome these challenges and improve efficiency. The development of grafting robots, capable of mechanizing the grafting process, holds promise for increasing productivity while reducing labor costs. Additionally, the establishment of specialized plug plantlet nurseries, equipped with advanced seeders, growth chambers, and acclimatization facilities, offers a pathway to enhance seedling vigour and uniformity in developing countries. Future research should also focus on refining seed-priming methods, improving seedling storage technologies, and exploring digital tools such as databases, crop models, and mobile applications to optimize grafting practices. These innovations could provide valuable insights for growers, helping them select the best rootstock-scion combinations and manage crops more efficiently. With continued research and technological advancements, vegetable grafting is poised to become a global solution, offering sustainable growth and productivity improvements in agriculture.

A systematic review on robot-assisted language learning for adults

In the 21st-century era of globalization, language proficiency is a pivotal connector across cultures, with artificial intelligence (AI) revolutionizing educational paradigms through Robot-Assisted Language Learning (RALL). This systematic review examines the role of RALL in adult second language acquisition, focusing on its pedagogical strategies and learner engagement. Unlike the previous systematic reviews that explore the multifaceted roles of robots in language learning, including as teachers, tutors, assistants, and peer learners, we identify explicit and implicit instructional strategies within RALL, highlighting the unique learning landscape of adult learners characterized by self-regulation and self-direction. We assess the latest advancements in RALL for adult learners through three research questions, compare the effectiveness of explicit versus implicit instructions, and investigate affective factors enhancing RALL performance. Our review contributes a comprehensive status analysis, in-depth exploration of interaction modes, and insights for future research directions, providing a roadmap for academic research and practical guidance for educators and robot developers. This study aims to optimize RALL strategies to better meet the needs of adult learners, fostering a more efficient and engaging language learning experience.

Evolutionary robotics as a modelling tool in evolutionary biology

The use of evolutionary robotic systems to model aspects of evolutionary biology is well-established. Yet, few studies have asked the question, “What kind of model is an evolutionary robotic system?” This paper seeks to address that question in several ways. First, it is addressed by applying a structured model description developed for physical robot models of animal sensorimotor systems, then by outlining the strengths and limitations of evolutionary robotics for modelling evolutionary biology, and, finally, by considering the deepest questions in evolution and which of them might feasibly be modelled by evolutionary robotics. The paper concludes that although evolutionary robotics faces serious limitations in exploring deeper questions in evolutionary biology, its bottom-up approach to modelling populations of evolving phenotypes and their embodied interactions holds significant value for both testing and generating hypotheses.

Multistimuli-Responsive Soft Actuators with Controllable Bionic Motions.

Soft actuators with biomimetic self-regulatory intelligence have garnered significant scientific interest due to their potential applications in robotics and advanced functional devices. We present a multistimuli-responsive actuator made from a carbon nitride/carbon nanotube (CN/CNTs) composite film. This film features a molecular switch based on reversible hydrogen bonds, whose asymmetric distribution endows the film with the ability to absorb water unevenly and convert molecular motion into macroscopic movement. By incorporating carboxylated CNTs, the film demonstrates improved mechanical properties and actuation performance. Under ambient humidity stimuli, the actuator can autonomously generate walking and tumbling motions. The CN/CNTs composite film's actuating behaviors are programmable, enabling diverse deformation modes and complex biomimetic movements. Additionally, the film exhibits excellent photothermal conversion efficiency (74.10 °C/s), allowing for temperature and light-responsive actuation, which can be remotely controlled in real time. These features have enabled the creation of soft robots capable of complex biomimetic actions such as jumping, directional movement, and transporting objects. This research broadens the potential applications of CN-based actuators and paves the way for the development of intelligent soft robots.

Robotics and Automation Roadmap: Thailand Perspectives

Robotics and automation are the key industries supporting Thailand’s strategic initiatives toward Thailand 4.0. This paper presents the development of an industry roadmap guiding the future research and development of related technologies in Thailand. The roadmap project was recently conducted during 2021–2022. The strategic targets for the future development of robotics and automation in Thailand were set to increase productivity and reduce adoption cost for the short term (2022–2023); create market opportunities for AI and industrial IoT technologies with data platform for the medium term (2024–2026); and prepare the Industry 5.0 system supporting emerging applications of digital twins and metaverse for the long term (2027–2030).

Artificial Intelligences in Industrial Robots: A Framework Based on Gardner’s Multiple Intelligences

Industrial robots, both in manufacturing and non-manufacturing sectors, are evolving rapidly, driven by advancements in artificial intelligence (AI). This paper presents a comprehensive survey of industrial robots, framed through the lens of Howard Gardner’s theory of multiple intelligences. By categorising various AI capabilities in industrial robots—such as visual recognition, decision-making, and collaborative interaction—based on Gardner’s intelligence framework, we provide a novel taxonomy that bridges human cognitive abilities and artificial systems. The survey explores the historical development of industrial robots, the current state of AI implementation, and future trends in robotics. Additionally, we discuss the implications of these advancements for industries and their workforce, as well as the ethical considerations surrounding the growing autonomy of AI systems. This paper aims to serve as a reference point for researchers and professionals seeking to understand the intersection of cognitive science and industrial AI, highlighting the potential and challenges of integrating AI into robotic systems.

Intelligent assistive obstacle avoidance device based on SLAM and wearable technology

Abstract. This paper presents a conceptual design for an intelligent assistive device that combines visual simultaneous localisation and mapping (SLAM) with wearable technology. The device has been developed through the integration of two innovative fields: visual SLAM and wearable technology. The objective is to develop a device that is both user-friendly and safe. The design addresses the issue of safety for visually impaired individuals when they are outside the home. The objective is to provide a dependable, real-time, and resilient solution that can be utilised in intricate indoor and outdoor settings. The system is designed to provide reliable, real-time, and highly effective solutions in variable environments. The main components of the proposed system include visual SLAM, intelligent wearable devices (as carriers), and a comfortable and straightforward user feedback system (through haptic, auditory, or visual signals to provide feedback to the wearer), while simultaneously considering the safety and comfort of the device. This is due to the consideration of the prolonged and frequent periods of use by visually impaired individuals. This paper considers the latest advances in SLAM algorithms, improvements in wearable sensors and the latest developments in robotics for assisting visually impaired people. It also discusses the potential of these technologies in the future development of assistive devices. The aim is to provide a feasible, comfortable and safe solution that will enhance the safety and autonomy of visually impaired people when they are outside.

Modeling and precise tracking control of spatial bending pneumatic soft actuators

In recent years, a variety of pneumatic soft actuators (PSAs) have been proposed due to the development of soft robots in biomimetic robots, medical devices, etc. At the same time, the modeling and control of PSAs remains an open question. In this paper, a spatial bending pneumatic soft actuator (SBPSA) modeling method based on the Prandtl–Ishlinskii (PI) model is proposed, and the inverse model is designed to compensate for hysteresis nonlinearity. Furthermore, an adaptive feedback controller combined with a hysteresis compensator is proposed for the precise control and tracking of SBPSAs. Finally, an experimental platform is built, and experimental results demonstrate the effectiveness of the proposed method for precise tracking.

Research Progress on Pole-Climbing Robots: A Review

Background: Pole-climbing robots are a type of application robot commonly used for quality inspection, cleaning, and maintenance of utility poles, high voltage lines, bridge cables, transmission pipelines, and other important facilities with a certain height. The working conditions are often harsh and dangerous, making manual participation unsafe. The pole-climbing robot can provide a platform for maintenance and cleaning work. Remote control operation of the pole-climbing robot is achieved through communication and control technology. It has been created to improve efficiency and reduce personnel accidents greatly. At the same time, the continuous development of science and technology has led to the expansion of robot design concepts. It has also brought about great changes and growth in the development of pole-climbing robots. Objective: The purpose of this paper is to report the latest progress in the research of pole-climbing robots from bionic and non-bionic perspectives and to provide a research reference for researchers in this field. Method: By analyzing academic theses and published patents, this paper presents a new classification of pole-climbing robots from the perspective of bionic and non-bionic. By summarizing the literature, the structural characteristics of various pole-climbing robots and their differences and applications are summarized. Results: The performance of the pole-climbing robots is analyzed from the viewpoint of structural characteristics and action execution methods. In turn, the characteristics of various types of pole-climbing robots are summarized. Finally, based on the above discussion, the future problems and development directions of pole-climbing robots are predicted. Conclusion: The pole-climbing robots can be divided into two categories, bionic and non-bionic, based on the analysis of design features. Both bionic and non-bionic pole-climbing robots have good development and applications in their respective directions. Also, bionic and non-bionic pole-climbing robots have different detailed classifications based on material, structure, and other perspectives. They have different advantages and disadvantages in terms of the performance of pole-climbing action execution. It provides a research reference for future researchers in this field.

Robotics and artificial intelligence in unconventional reservoirs: Enhancing efficiency and reducing environmental impact.

Shale, tight gas, and coal bed methane reservoirs are unconventional reservoirs that have geometrically complicated geological formations with low permeability, rendering their extraction operations difficult, expensive, and environmentally sensitive. On the other hand, recent developments in Robotics and Artificial Intelligence continue to transform how exploration, production, and maintenance activities are carried out in these reservoirs. This review paper encompasses how Robotics and AI technologies are applied to these unconventional reservoirs, improving operation efficiency, increasing the recovery rate and minimizing environmental damage. It updates on the latest status of autonomous drilling, AI-driven reservoir characterization and robotic fracturing. The paper also discusses future opportunities: emerging technologies, integration of AI with predictive analytics, and innovations toward sustainability. These are the challenges that come with possible solutions discussed in the paper: high costs, technical integration, and data quality. The review thereby presents the thought that robotics and AI will take a transformative role in the unconventional reservoir sector during the next few years, both in economic performance and environmental sustainability.

Framework for Integrating Large Language Models with a Robotic Health Attendant for Adaptive Task Execution in Patient Care

The development of intelligent medical service robots for patient care presents significant challenges, particularly in integrating diverse knowledge sources and enabling robots to autonomously perform tasks in dynamic and unpredictable healthcare environments. This study introduces a novel framework that combines large language models with healthcare-specific knowledge and robotic operations to enhance autonomous task execution for a Robotic Health Attendant. Utilizing OpenAI’s ChatGPT, the system processes structured information about patient care protocols and unstructured human inputs to generate context-aware robot actions. A prototype system was tested in a simulated patient room where the robot successfully performed both simple individual actions and complex tasks involving the execution of multiple actions, based on real-time dialogues with the language model and predefined task specifications. The results demonstrate the potential of language models to reduce the reliance on hardcoded logic and provide healthcare professionals with the ability to interact with robotic systems through natural language.

Ethical Reflections on the Application of Medical Robots in Healthcare

With the development and utilization of medical robots, more and more members of the public have begun to pay attention to the risks of practicing medical robots and have expressed concerns about their application. In order to deeply study the ethical risks of medical robots applied in health care, this study chooses the literature research method to reflect on the moral and ethical issues involved in medical robots. The study found that current medical robots have many application scenarios, such as: surgery, rehabilitation care, assisted work and telemedicine. These application scenarios of medical robots may bring ethical risks such as attribution of medical responsibility, doctor-patient relationship, and data algorithms. Intensively, the study points out that inadequate laws, immature values, and technological deficiencies are the most significant factors leading to the aforementioned risks. Thus, adequate attention should be paid to the medical career, the intelligent technology of robots should be improved, and the relevant laws and regulations should be actively improved. This study realistically reflects the current situation and risks of medical robot application, and through in-depth reflection, provides inspiration for robots to better serve the medical cause.

The Future of Robotics: Integrating Biological Components in Biohybrid Robotics for Enhanced Functionality and Adaptability

Biohybrid robotics, an emerging interdisciplinary field, combines biological tissues with synthetic robotic systems to create machines that exhibit enhanced functionality, adaptability, and efficiency. By integrating living cells, muscles, or other biological components with engineered structures, biohybrid robots are designed to mimic natural processes and behaviors, offering the potential for significant advancements in soft robotics, medical devices, and autonomous systems. This paper explores the latest developments in biohybrid robotics, focusing on the design principles, challenges in integrating biological and synthetic components, and the potential applications in fields such as healthcare, environmental monitoring, and bioengineering. By leveraging the inherent advantages of biological tissues—such as self-healing, energy efficiency, and adaptive responsiveness—biohybrid robots could outperform conventional robotic systems in tasks that require flexibility, precision, and interaction with dynamic environments. This research also examines the ethical and technical challenges associated with the field, including the sustainability of biological materials and the long-term stability of these systems. The potential for biohybrid robotics to revolutionize industries by blending biological intelligence with synthetic durability underscores the significance of this rapidly evolving technology. Biohybrid robotics not only holds promise for creating more versatile and efficient machines but also represents a major step toward bridging the gap between biology and engineering. By harnessing the unique properties of biological systems, such as their ability to grow, repair, and adapt to changing environments, biohybrid robots can offer solutions to challenges that traditional robotics struggle to address. For example, in the medical field, these robots could assist in developing more effective prosthetics, bio-inspired implants, and even robotic systems that work inside the body to perform tasks with a level of precision and biocompatibility previously unattainable. This research delves into the potential for future advancements in areas such as environmental sustainability, where biohybrid robots could be used for tasks like pollution detection and waste management. Their biological components would enable them to interact with natural ecosystems in more seamless and non-disruptive ways. However, this integration of living tissues with technology also raises important ethical considerations regarding the use of biological materials and the extent to which we can manipulate living organisms for technological purposes. Addressing these challenges will be critical to the successful development and deployment of biohybrid robotics in real-world applications.

A Biomimetic Nociceptor Based on a Vertical Multigate, Multichannel Neuromorphic Transistor.

Nociceptors, crucial sensory receptors within biological systems, are essential for survival in diverse and potentially hazardous environments. Efforts to replicate nociceptors through advanced electronic devices, such as memristors and neuromorphic transistors, have achieved limited success, capturing basic nociceptive functions while more advanced characteristics like various forms of central sensitization and analgesic effect remain out of reach. Here, we introduce a vertical multigate, multichannel electrolyte-gated transistor (Vm-EGT), designed to mimic nociceptors. Utilizing the hybrid mechanism combining electric-double-layer (EDL) with ion intercalation/deintercalation in EGTs, our approach successfully replicates peripheral sensitization and desensitization characteristics of nociceptors. The intricate multigate and multichannel design of the Vm-EGT enables the emulation of more advanced nociceptive functionalities, including central sensitization and analgesic effect. Furthermore, we demonstrate that by exploiting the inherent current-voltage relationship, the Vm-EGT can simulate these advanced nociceptive features and seamlessly transition between them. Integrating a Vm-EGT with a thermistor and a heating plate, we have developed an artificial thermal nociceptor that closely mirrors the sensory attributes of its biological counterpart. Our approach significantly advances the emulation of nociceptors, providing a basis for the development of sophisticated artificial sensory systems and intelligent robotics.

Design of a Bionic Spider Robot with a Two-Degrees-of-Freedom Leg Structure and Body Frame

Spiders have unique biological characteristics and excellent maneuverability, making them an ideal model for bionic robot design. However, traditional bionic spider robot designs usually have multiple degrees of freedom and confront many challenges. These challenges include complex control requirements, higher energy consumption, larger size and weight, higher risk of failure, and higher cost. This study proposes a leg design with two degrees of freedom to reduce its control and manufacturing costs. It can better control leg movement and improve leg force through a multi-link mechanism and a dual-motor system. In addition, the triangular gait and hexagonal body structure align the weight of the body with the support point, thereby enhancing stability. This study offers a comprehensive and organized approach to bio-inspired robot design, providing a valuable reference for future bionic robot development.

Towards a Unified Framework for Software-Hardware Integration in Evolutionary Robotics

The discrepancy between simulated and hardware experiments, the reality gap, is a challenge in evolutionary robotics. While strategies have been proposed to address this gap in fixed-body robots, they are not viable when dealing with populations and generations where the body is in constant change. The continual evolution of body designs necessitates the manufacturing of new robotic structures, a process that can be time-consuming if carried out manually. Moreover, the increased manufacturing time not only prolongs hardware experimental durations but also disrupts the synergy between hardware and simulated experiments. Failure to effectively manage these challenges could impede the implementation of evolutionary robotics in real-life environments. The Autonomous Robot Evolution project presents a framework to tackle these challenges through a case study. This paper describes the main three contributions of this work: Firstly, it analyses the different reality gap experienced by each different robot or the heterogenous reality gap. Secondly, it emphasizes the importance of automation in robot manufacturing. And thirdly, it highlights the necessity of a framework to orchestrate the synergy between simulated and hardware experiments. In the long term, integrating these contributions into evolutionary robotics is envisioned to enable the continuous production of robots in real-world environments.

The Architecture of Immortality Through Neuroengineering

From mobile health and wearables to implantable medical devices and neuroprosthetics, the integration of machines into human biology and cognition is expanding. This paper explores the technological advancements that are pushing the human–machine boundaries further, raising profound questions about identity and existence in digital realms. The development of robots, androids, and AI–human hybrids promises to augment human capabilities beyond current limits. However, alongside these advancements, significant limitations arise: biological, technical, ethical, and legal. This paper further discusses the existential implications of these technological strides. It addresses the philosophical dimensions of mortality, forgiveness, and the significance of death in a world where technological immortality may be within reach. By addressing these questions, the paper seeks to provide a comprehensive analysis of the potential for these advancements to reshape our understanding of existence and the quest for immortality.

Soft robots and soft bodies: biological insights into the structure and function of fluidic soft robots.

Over the last two decades, robotics engineering has witnessed rapid growth in the exploration and development of soft robots. Soft robots are made of deformable materials with mechanical properties or other features that resemble biological structures. These robots are often inspired by living organisms or mimic their locomotion, such as crawling and swimming. This paper aims to assist researchers in robotics and engineering to design soft robots incorporating or inspired by biological systems with a more informed perspective on biological models and functions. We address the characteristics of fluidic soft robots inspired by or mimicking biological examples, establish a method to categorize soft robots from a functional biological perspective, and provide a wider range of organisms to inspire the development of soft robotics. The actuation mechanisms in bioinspired and biomimetic soft robotics would benefit from a clearer understanding of the underlying principles, organization, and function of biological structures.

Human–robot interaction: predicting research agenda by long short-term memory

The article addresses the identification and prediction of research topics in human–robot interaction (HRI), fundamental in Industry 4.0 (I4.0) and future Industry 5.0 (I5.0). In the absence of research agendas in the scientific literature, the study proposes a multilayered model to create a precise agenda to guide the scientific community in new developments in collaborative robotics and HRI technologies. The methodology is divided into four stages, which make up the three layers of the model. In the first two stages, scientific articles on HRI for the period 2020–2021 were collected and analyzed using data mining techniques together with VantagePoint and Gephi software to identify keywords and their relationships. These initial stages form layer 1 of the model, where the main scientific themes are recognized. In the third stage, article titles and abstracts are cleaned and processed using natural language processing (NLP) techniques, generating word embeddings models that highlight relevant HRI-related terms, forming layer 2. The fourth and final stage uses Recurrent Neural Networks (RNN) with long short-term memory (LSTM) architecture to predict future topics, consolidating the previously identified terms and forming layer 3 of the model. The results show that in layer 1 HRI has intensive application in various sectors through advanced computational algorithms, with trust as a key feature. In layer 2, terms such as vision, sensors, communication, collaboration and anthropomorphic aspects are fundamental, while layer 3 anticipates future topics such as design, performance, method and controllers, essential to improve robot interaction. The study concludes that the methodology is effective in defining a robust and relevant research agenda. By identifying future trends and needs, this work fills a gap in the scientific literature, providing a valuable tool for the research community in the field of HRI.