Development Of Robot Research Articles

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.

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.

Robot intelligent perception and control

Abstract. In recent years, with the rapid development of robotics, intelligent perception and control has become the core research direction in the field of robotics. This technology plays a key role in many fields such as industrial automation, medical assistance, and autonomous driving, significantly improving production efficiency and service quality, and also promoting the intelligent processes of various industries. On the basis of an in-depth analysis of robot intelligent perception and control technology, this paper systematically reviews the development of visual and non-visual perception technology and discusses the application of multi-modal perception in complex environments. The latest development of motion control and force control technology is analyzed, and its importance in fine operation is expounded. The future development direction of robot intelligent perception and control technology is proposed, and the necessity of enhancing real-time robustness and system integration is emphasized, which provides theoretical support and technical reference for promoting the continuous innovation of robot intelligent perception and control technology.

New protocol for early robot-assisted gait training after spinal surgery.

Early rehabilitation post-spinal surgery is vital for patients' recovery. Robot-assisted gait training (RAGT) shows promise but requires further study to establish a specific protocol and gauge its effects on both patients and physical therapists. This study aimed to determine the impact of a newly developed protocol for early RAGT on patients' functional enhancement and satisfaction levels after spinal surgery, as well as on the physical therapists who implemented the therapy. First, we developed the protocol in collaboration with three physiatrists and two physical therapists with extensive experience in musculoskeletal rehabilitation. The protocol was updated three times, each after three rounds of face-to-face meetings. Afterward, we conducted a cross-sectional study involving five physical therapists and 32 post-spinal surgery patients at a tertiary hospital rehabilitation center. The intervention consisted of five sessions of RAGT. Main outcome measures included the Functional Ambulation Category (FAC), the ambulation item of the Modified Barthel Index (MBI ambulation), and satisfaction surveys for both patients and physical therapists. RAGT typically started 17.91 ± 9.76 days postoperatively and was successfully applied with no remarkable adverse effects. The FAC scores increased from 2.65 ± 1.21 to 3.78 ± 0.71 (p = 0.006), and MBI ambulation increased from 7.69 ± 2.71 to 10.66 ± 2.90 (p < 0.001) between transfer and discharge. Satisfaction with the robot, RAGT, and treatment, assessed using a 5-point Likert scale, were 3.30 ± 0.79, 3.72 ± 0.85, and 3.08 ± 0.84, respectively. Satisfaction was notably the highest for alleviating fear of falling, whereas managing pain and discomfort during position changes scored the lowest. Physical therapists rated RAGT satisfaction, impact on the working environment, and treatment stability at 3.0 ± 0.65, 2.80 ± 0.67, and 3.50 ± 0.61, respectively. Early spinal surgery rehabilitation with RAGT improved patients' functionality and gait satisfaction. While physical therapists considered RAGT safe, its impact on their work environment was limited. Integrating RAGT into post-spinal surgery rehabilitation demands ongoing protocol refinement, custom robot development, and efficacy evaluations.

Programmable Lipid Bilayer Tension-Control Apparatus for Quantitative Mechanobiology.

The biological membrane is not just a platform for information processing but also a field of mechanics. The lipid bilayer that constitutes the membrane is an elastic body, generating stress upon deformation, while the membrane protein embedded therein deforms the bilayer through structural changes. Among membrane-protein interplays, various channel species act as tension-current converters for signal transduction, serving as elementary processes in mechanobiology. However, in situ studies in chaotically complex cell membranes are challenging, and characterizing the tension dependency of mechanosensitive channels remains semiquantitative owing to technical limitations. Here, we developed a programmable membrane tension-control apparatus on a lipid bilayer system. This synthetic membrane system [contact bubble bilayer (CBB)] uses pressure to drive bilayer tension changes via the Young-Laplace principle, whereas absolute bilayer tension is monitored in real-time through image analysis of the bubble geometry via the Young principle. Consequently, the mechanical nature of the system permits the implementation of closed-loop feedback control of bilayer tension (tension-clamp CBB), maintaining a constant tension for minutes and allowing stepwise tension changes within a hundred milliseconds in the tension range of 0.8 to 15 mN·m-1. We verified the system performance by examining the single-channel behavior of tension-dependent KcsA and TREK-1 potassium channels under scheduled tension time courses prescribed via visual interfaces. The result revealed steady-state activity and dynamic responses to the step tension changes, which are essential to the biophysical characterization of the channels. The apparatus explores a frontier for quantitative mechanobiology studies and promotes the development of a tension-operating experimental robot.

KOALA: A Modular Dual-Arm Robot for Automated Precision Pruning Equipped with Cross-Functionality Sensor Fusion

Landscape maintenance is essential for ensuring agricultural productivity, promoting sustainable land use, and preserving soil and ecosystem health. Pruning is a labor-intensive task among landscaping applications that often involves repetitive pruning operations. To address these limitations, this paper presents the development of a dual-arm holonomic robot (called the KOALA robot) for precision plant pruning. The robot utilizes a cross-functionality sensor fusion approach, combining light detection and ranging (LiDAR) sensor and depth camera data for plant recognition and isolating the data points that require pruning. The You Only Look Once v8 (YOLOv8) object detection model powers the plant detection algorithm, achieving a 98.5% pruning plant detection rate and a 95% pruning accuracy using camera, depth sensor, and LiDAR data. The fused data allows the robot to identify the target boxwood plants, assess the density of the pruning area, and optimize the pruning path. The robot operates at a pruning speed of 10–50 cm/s and has a maximum robot travel speed of 0.5 m/s, with the ability to perform up to 4 h of pruning. The robot’s base can lift 400 kg, ensuring stability and versatility for multiple applications. The findings demonstrate the robot’s potential to significantly enhance efficiency, reduce labor requirements, and improve landscape maintenance precision compared to those of traditional manual methods. This paves the way for further advancements in automating repetitive tasks within landscaping applications.

Robotic Assembly – Mobile Platform for Construction Field

"Construction sites often involve the manual transportation of heavy objects, posing risks to workers' safety and efficiency. In this paper, it was proposed a design, development, and evaluation of a service robot specifically created for carrying heavy objects in the construction field. The robot is equipped with robust locomotion capabilities, intelligent perception systems, and efficient control mechanisms to navigate through complex environments and handle various types of loads. It was presented the technical design of the robot, including its hardware components, sensing modalities, and software architecture. Furthermore, it was discussed the experimental validation of the robot's performance in real-world construction scenarios, highlighting its effectiveness in improving productivity, reducing labor costs, and enhancing workplace safety. Through this research, the aim is to demonstrate the potential of service robots as valuable assets in the construction industry, paving the way for future advancements in robotic assistance technologies. Keywords: human-robot collaboration, manipulation, autonomous systems, object transportation, mechanics."

Monitoring system for physical activity and fitness based on service robots and biomechanics

Exercise is one of the important ways for people to exercise, with characteristics such as sociality and strong participation. Especially with the improvement of the level of economic development and the improvement of the quality of life of the people, more and more people begin to attach importance to the maintenance of their own health. Physical fitness monitoring, as an effective means, is widely used in daily life, especially among the elderly. However, most of the existing monitoring methods are relatively simple, lacking pertinence, and the data collection process is relatively cumbersome and unstable, which cannot meet current needs. Therefore, it is very necessary to explore a new type of equipment that can more comprehensively and accurately monitor various physiological parameters of the human body to replace existing traditional detection technologies. Service Robots are currently the most promising intelligent hardware products. They mainly provide personalized services centered on users, sensing user behavior and implementing intelligent decision-making based on their characteristics, thereby better meeting the needs of different groups of people. This article focused on the research and development of Service Robots, and designed a comprehensive solution for Service Robots based on theories such as the Internet of Things, cloud computing, big data technology, and artificial intelligence. This article compared existing intelligent monitoring systems with fitness monitoring systems based on Service Robots, and proved that the user experience of fitness monitoring with robot participation has improved by about 4.68%. Its application scenarios were richer and its effects were more significant, enabling it to better complete tasks such as analysis and prediction of physical fitness status, real-time warning, etc., reducing the risk of people suffering from diseases, and enhancing individual protection awareness.

Development of Dual-Arm Human Companion Robots That Can Dance.

As gestures play an important role in human communication, there have been a number of service robots equipped with a pair of human-like arms for gesture-based human-robot interactions. However, the arms of most human companion robots are limited to slow and simple gestures due to the low maximum velocity of the arm actuators. In this work, we present the JF-2 robot, a mobile home service robot equipped with a pair of torque-controlled anthropomorphic arms. Thanks to the low inertia design of the arm, responsive Quasi-Direct Drive (QDD) actuators, and active compliant control of the joints, the robot can replicate fast human dance motions while being safe in the environment. In addition to the JF-2 robot, we also present the JF-mini robot, a scaled-down, low-cost version of the JF-2 robot mainly targeted for commercial use at kindergarten and childcare facilities. The suggested system is validated by performing three experiments, a safety test, teaching children how to dance along to the music, and bringing a requested item to a human subject.

Video Review Can Measure Surgical Robotic Skill Development in a Resident Robotic Hernia Curriculum: A Retrospective Cohort Study

Background: Hernia repairs are one of the most common general surgery procedures and an essential part of training for general surgery residents. The widespread incorporation of robotic hernia repairs warrants the development of a procedure-specific robotic curriculum to assist novice surgeons in improving technical skills. Objective: To evaluate a robotic hernia simulation-based curriculum for general surgery residents using video review. Methods: Retrospective cohort study of PGY-3 general surgery residents from the University of Chicago from 2019 to 2021. The residents completed inguinal hernia repair (IHR) and ventral hernia repair (VHR) drills as part of a robotic simulation curriculum. The drills were recorded and graded according to the modified objective structured assessment of technical skills (OSATS) and time to completion. The drills were completed by 3 attending surgeons to establish gold-standard benchmarks. Results: In total, 20 residents started the curriculum, 19 completed all IHR drills and 17 completed all VHR drills. Attending surgeon total OSATS scores and time to completion were significantly better than the trainees on the first attempt (P &lt; 0.05). When comparing 1st to 4th attempt, resident OSATS scores improved significantly for IHR (15.5 vs 23.3; P &lt; 0.001) and VHR (16.8 vs 23.3; P &lt; 0.001). Time also improved over 4 attempts (IHR: 28.5 vs 20.5 minutes; P &lt; 0.001 and VHR: 29.6 vs 21.2 minutes; P &lt; 0.001). Residents achieved attending-level OSATS scores by their fourth attempt for VHR, but not for IHR. Residents did not achieve attending-level times for either hernia drills. Conclusions: The robotic hernia curriculum improved resident performance on hernia repair drills and was well-received by the residents.

Recent progress in soft robots: principles, designs, and applications

Abstract With advancements in the manufacturing industry persisting, soft robots have experienced rapid development, progressively emerging as a pivotal focus in the future trajectory of robotic technology. As a new type of robot technology, soft robots have significant differences from traditional robots in terms of principles, driving methods, design control, and other aspects. Here, we sort out and summarize the latest developments in soft robotics. Firstly, typical principles and driving methods were introduced, including rope drive, variable stiffness drive (gas negative pressure, intelligent fluids, etc), electromagnetic drive, and so on. Secondly, the main materials and characteristics of soft robots are analyzed, including hydrogels, shape memory alloys, photosensitive materials, electromagnetic rheological elastomer, biodegradable materials, etc. Then, typical soft robot structures and processing methods were introduced, including fluid static skeleton structures, muscle fluid static skeleton structures, and others. Finally, the problems of soft robots are analyzed, and the future development direction and importance are summarized. This paper highlights the recent progress in smart functional materials, typical biomimetic structures, and assembly methods applicable to soft robots, which is expected to assist the development and advancement of the next generation of soft robots.