Complex Robot Research Articles

The Future of Parenthood? Examining the Promise and Complexity of Pregnancy Robots in Reproductive Health.

Advancements in reproductive technology are now approaching an unprecedented frontier: the pregnancy robot, a potential artificial womb capable of carrying a fetus from fertilization to birth. This innovation, by simulating the natural uterine environment, could redefine pregnancy and parenthood, offering transformative benefits for maternal and infant health. The pregnancy robot promises safer pathways for individuals with medical risks, LGBTQ + couples, and single parents, while also reducing the risks of complications like preeclampsia and preterm birth. It builds on the foundations laid by assisted reproductive technologies (ART), aiming to make the process more accessible and inclusive. However, the introduction of such technology brings with it complex ethical and social questions, including potential impacts on maternal-child bonding, gender roles, and societal norms surrounding motherhood. Further concerns revolve around equitable access, as socioeconomic divides may restrict this technology to those with financial resources, and the risk of cultural and religious opposition. Legal, regulatory, and environmental considerations must also be addressed to responsibly integrate this technology. This article discusses the profound promise and ethical challenges of pregnancy robots, highlighting the need for thoughtful implementation and collaborative dialogue to ensure that the technology, if realized, can benefit all facets of society and pave the way for a more inclusive future in reproductive health.

Multi-constraint reinforcement learning in complex robot environments

Multi-constraint reinforcement learning in complex robot environments

REMOTE INTELLIGENT ROBOT MANIPULATOR CONTROL SUBSYSTEM

The issue of expanding the functionality of an intelligent software and hardware subsystem for capturing an object by a robot manipulator was considered. It is shown that the task of expanding the functionality of the subsystem for free-form object capture by a robot manipulator with technical vision based on the operations of building a depth map from the obtained stereo image is insufficiently developed and can be solved by integrating a remote robot cntrol subsystem connected to a local network or the Internet into the robotic complex. The subsystem was developed using a Raspberry Pi microcomputer, a Stereo Pi board, a board for connecting eight Adafruit PCA9865 servos, Raspberry PI cameras, and a camera module. The structure and electrical diagram of the subsystem, a description of the software, and the main code snippet of the web application program are presented. Based on the analysis of the research results, it is established that the proposed remote control subsystem provides an extension of the functionality of the intelligent software and hardware subsystem for capturing an object by a robot manipulator, since in addition to the functions of automatic object capture, due to remote adjustment of the accuracy and manufacturability of object capture, it provides the functions of high-precision positioning of objects relative to each other and especially the effort on the robot manipulator to perform precise operations. The reliability of the object capture is also increased due to the fact that the subsystem allows for the additional involvement of a team of competent users. The proposed system increases the degree of automation, provides the possibility of moderation, collective administration, and user feedback during robot operation.

Conceptual principles and method of creating a high-through autonomous ground robotic complex

Conceptual principles and a method of creating a high-passage autonomous ground robotic complex and a method of its construction for operation in difficult terrain and under the influence of radio-electronic warfare tools have been developed. Based on the global experience of creating high-precision autonomous robotic complexes using inertial navigation systems, the integration of magneto-inertial methods, technical vision systems with pattern recognition and binding to the terrain and artificial intelligence in the navigation system is proposed and investigated. A model of navigation system errors has been developed. Calculations of the accuracy of the components of the navigation system and the accuracy of determining the movement parameters of the robotic complex are given.

Study of the satellite pre-calming mode

Conceptual principles and a method of creating a high-passage autonomous ground robotic complex and a method of its construction for operation in difficult terrain and under the influence of radio-electronic warfare tools have been developed. Based on the global experience of creating high-precision autonomous robotic complexes using inertial navigation systems, the integration of magneto-inertial methods, technical vision systems with pattern recognition and binding to the terrain and artificial intelligence in the navigation system is proposed and investigated. A model of navigation system errors has been developed. Calculations of the accuracy of the components of the navigation system and the accuracy of determining the movement parameters of the robotic complex are given.

Industry 4.0 технологияларын оқыту мақсатында Қазақстанда техникалық мамандықтар бойынша бакалаврларды даярлау үшін робототехникалық кешенін жасау (Әбілқас Сағынов атындағы Қарағанды техникалық университеті тәжірибесі негізінде)

The training stand «FESTO Mechatronic Line» is considered, which is located in the auditorium 126 of the Department of Automation of Production Processes of the Karaganda Technical University named after A. Saginov. The stand is the object of research of several diploma projects and dissertations of students and master students of the educational program «Automation and control». This training stand is designed to train intelligent robotic and mechatronic complexes in accordance with Industry 4.0 technologies and technical solutions based on university equipment. 4 technologies of the Industry 4.0 concept have been implemented at the «FESTO Mechatronic Line» training stand. The creation of such robotic complexes will allow teaching senior students and undergraduates of universities, as well as retraining and advanced training of engineers and specialists.

Enhancing industrial robot selection through a hybrid novel approach: integrating CRITIC-VIKOR method with probabilistic uncertain linguistic q-rung orthopair fuzzy

The increasing complexity and novel features of industrial robots have made their selection for specific applications a challenging task. Decision-makers are faced with the daunting task of navigating through various attributes and specifications, often under conditions of ambiguity and uncertainty. To assist in this complex decision-making process, this paper introduces a novel decision-making framework based on probabilistic uncertain linguistic q-rung orthopair fuzzy sets (PULq-ROFS). This framework effectively combines the strengths of probabilistic uncertain linguistic term set (PULTS) and q-rung orthopair fuzzy set (q-ROFS) to provide a more robust approach for handling ambiguity and uncertainty in the robot selection process. The proposed methodology integrates a multi-attribute group decision-making (MAGDM) approach. This approach utilizes the VIseKriterijumska Optimizacija I KOmpromisno Resenje (VIKOR) method in conjunction with the criterion importance via inter-criteria correlation (CRITIC) method. The CRITIC method determines attribute weights by analyzing both the differences and contrast intensity of criteria, thereby accounting for the relative strength and conflict among them. VIKOR is then employed to aggregate individual regret and group utility, resulting in a compromise solution that guides decision-makers toward the optimal robot selection. Proposed method provide the clarity and confidence to decision makers for choice of attributes and crediting this enhancement to the framework’s transparency and its ability to incorporate a wide range of stakeholder perspectives. This framework facilitates a more inclusive decision-making process that acknowledges differing viewpoints and preferences. This proposed approach not only directs users toward optimal selections but also encourages collaboration among decision-makers, promoting a sense of shared ownership and responsibility in the selection process. This paper select the best robot by utilizing the benefits of both CRITIC and VIKOR method. The effectiveness of this integrated approach is validated through parameter and comparative analysis. The results demonstrate the potential applicability of the proposed methodology in real-world industrial robot selection scenarios, providing decision-makers with a powerful tool to navigate the complexities of modern robotic systems.

The Unmanned Robotic Complex For The Small Arms Fire Evaluation

The article presents the developed unmanned robotic complex for evaluation of small arms fire. The complex is designed for effective training of soldiers and officers in shooting at close and long distances (20 ¸ 1500 m.). The operating principle of the system is briefly described and technical characteristics are given. The complex is equipped with a hydro meteorological station for correcting shooting in accordance with the ballistic characteristics of the projectile during shooting. The shaped target is made of polymer carbon plastic material and it has a long service life. The software for unmanned control of the robotic complex has been developed. It is shown that the proposed unmanned robotic system has significant advantages over foreign analogues.

Cooperative dual-actor proximal policy optimization algorithm for multi-robot complex control task

This paper introduces a novel multi-agent Deep Reinforcement Learning (DRL) framework named the Cooperative Dual-Actor Proximal Policy Optimization (CDA-PPO) algorithm, designed to address complex humanoid robot cooperative learning control tasks. Effective cooperation among multiple humanoid robots, particularly in scenarios involving complex walking gait control and external disturbances in dynamic environments, is a critical challenge. This is especially pertinent for tasks requiring precise coordination and control, such as joint object transportation. In various real-life scenarios, humanoid robots might need to cooperate to carry large objects in many scenarios. This capability is crucial for logistics, manufacturing, intelligent transportation, and search-and-rescue missions applications. Humanoid robots have gained significant popularity, and their use in these cooperative tasks is becoming more common. To address this challenge, we propose CDA-PPO, which introduces a learning-based communication platform between agents and employs two distinct policy networks for each agent. This dual-policy approach enhances the robots’ ability to adapt to complex interactions and maintain stability while performing intricate tasks. We demonstrate the efficacy of CDA-PPO in a cooperative object-transportation scenario, where two humanoid robots collaborate to carry a table. The experimental results show that CDA-PPO significantly outperforms traditional methods, such as Independent PPO (IPPO), Multi-Agent PPO (MAPPO), and Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3), in terms of training efficiency, stability, reward acquisition, and humanoid robot cooperative balance control with effective coordination between robots. The findings underscore the potential of CDA-PPO to advance the field of cooperative multi-agent control problems, proposing the way for future research in complex robotics applications.

Сравнительная оценка показателей изокинетического тестирования нижних конечностей студенток 18–20 лет, занимающихся TRX-фитнесом и обычной физической культурой

The purpose of this article was to, by means of isokinetic testing, evaluate the strength parameters of the lower limbs in 18–20-year-old female students doing TRX training and standard exercises. Materials and methods. The research involved 40 female students of South Ural State University aged between 18 and 20 years, who were divided into the experimental (n = 20) and control (n = 20) groups. The former was doing TRX training, while the latter performed standard physical exercises on the university’s curriculum. The experiment was conducted at the Sports Science Research Centre of South Ural State University. Strength parameters were evaluated using a robotic medical diagnostic complex Biodex System 4Pro (Biodex Medical System, Inc., USA) at the start of exercise classes in the autumn of 2020 and after 1.5 years of classes in the spring of 2022. Results. In the course of the experiment, female students who had been doing TRX training for 1.5 years showed statistically significantly better results than the control group in the following parameters during knee flexion and extension: peak torque, peak torque per body weight, time to peak torque, coefficient of variation, mean power and mean peak torque (26 cases of statistically significant changes in the parameters out of 48 assessed cases were recorded). This indicates that lower limb muscles in female students doing this type of training became much stronger. Therefore, training with the use of TRX suspension straps can be considered an effective way to develop strength capabilities of the lower limbs in humans.

Efficient Robot Manipulation via Reinforcement Learning with Dynamic Movement Primitives-Based Policy

Reinforcement learning (RL) that autonomously explores optimal control policies has become a crucial direction for developing intelligent robots while Dynamic Movement Primitives (DMPs) serve as a powerful tool for efficiently expressing robot trajectories. This article explores an efficient integration of RL and DMP to enhance the learning efficiency and control performance of reinforcement learning in robot manipulation tasks by focusing on the forms of control actions and their smoothness. A novel approach, DDPG-DMP, is proposed to address the efficiency and feasibility issues in the current RL approaches that employ DMP to generate control actions. The proposed method naturally integrates a DMP-based policy into the actor–critic framework of the traditional RL approach Deep Deterministic Policy Gradient (DDPG) and derives the corresponding update formulas to learn the networks that properly decide the parameters of DMPs. A novel inverse controller is further introduced to adaptively learn the translation from observed states into various robot control signals through DMPs, eliminating the requirement for human prior knowledge. Evaluated on five robot arm control benchmark tasks, DDPG-DMP demonstrates significant advantages in control performance, learning efficiency, and smoothness of robot actions compared to related baselines, highlighting its potential in complex robot control applications.

Experience of using robot-assisted (da Vinci) operations in the treatment of common endometriosis

Background. Currently, genital endometriosis is considered as one of the most severe conditions in women of reproductive age, which has detrimental consequences for social, professional and psychological functioning. It ranks third in the structure of gynecological diseases after inflammatory diseases of the female reproductive system and uterine fibroids. Because of this, it acquires a more pronounced social significance and ceases to be only a medical problem. Aim. To study the results of surgical treatment of patients with severe forms of genital endometriosis using the da Vinci surgical robotic complex.Materials and methods. A retrospective analysis of the treatment results of 51 patients operated on at the N.I. Pirogov National Medical and Surgical Center for the period from January 2015 to July 2024, who underwent robot-assisted (da Vinci) operations for deep endometriosis involving neighboring organs. The duration of surgery and hospital stay, the amount of blood loss, the frequency of intra- and postoperative complications, the clinical course of the disease in the long-term postoperative period, the frequency of detection of residual infiltration in the postoperative period, and the implementation of reproductive plans were analyzed.Results. The duration of the surgical intervention was 220.8 ± 21.87 minutes. The postoperative bed-day was 6.9 ± 1.5 bed days. The average blood loss was 160.2 ± 67.58 ml. There were no intraoperative complications. Postoperative complications accounted for 7.8 %. Residual infiltration occurred in 11.7 % of cases. 94.1 % of the patients had no clinical symptoms of endometriosis in the long-term postoperative period. The pregnancy rate was 31.9 %.Conclusion. Surgical treatment of deep endometriosis using da Vinci surgical robotic complex in the amount of radical removal of endometrioid infiltrate has a positive effect on both the clinical course of the disease and the reproductive potential of a woman. Real-time fluorescence navigation has demonstrated additional imaging capabilities in robotic surgery for deep endometriosis, potentially increasing the radicalism of surgical treatment of infiltrating endometriosis and may lead to a reduction in recurrence rates.

On the Optimal Distribution of Traction Forces in Cable Propulsors of Mobile Robots

The analysis of methods of distribution of traction forces in various propellers of mobile robotic complexes and transport vehicles is carried out. The problem of synthesizing a method for controlling the distribution of the total traction load between interconnected electric drives of mobile robot propellers, discretely interacting with the support surface, is considered. An underwater mobile robot is simulated with several "walking-like" anchor-cable propellers, which ensure the movement of the underwater mobile robot by pulling the body to the supports located on the bottom. A mathematical model of the rectilinear motion of a mobile robotic device with walking-type propellers has been compiled. A mathematical description of the electric drive of the propulsion of such a mobile robot is proposed, taking into account its kinetic transfer function. It is shown that the total traction effort realized by a mobile robot is the source of the moment of resistance in the electric drive of each mover. In this regard, coefficients characterizing the distribution of traction force have been introduced into the differential equation of electric drives. A feature of the functions of these coefficients is their dependence on the distance traveled, speed and strength of resistance to movement. To optimize the distribution of the total power load between the thrusters, a target functional has been compiled. It is shown that as such a target functional, a requirement for a minimum of total heat losses in an interconnected electric drive of propellers can be formulated. To find the minimum of the accepted functional, the Euler-Poisson equations are compiled. As an additional limitation, the condition of physical feasibility is introduced. The results of solving such an optimization problem are presented on the simplest calculation scheme of two DC electric drives, between which the load is distributed along the rectilinear movement of a solid. As a result of solving the formulated optimization problem, the dependences of control actions for electric drives (voltage for DC electric drives), graphs of changes in the target function providing optimal distribution of traction forces between them are obtained, and the optimality of such distribution is proven.

DETERMINATION OF OPTIMAL CONDITIONS FOR HERMETIC WELDING OF THIN FOILS WHEN USED IN MEMBRANE-TYPE STRUCTURES

Purpose. Development of optimal technology for welding thin-walled shells mode of 12Х18Н10Т steel (δ=0.15 mm), working at alternating loads. Research methods. Research methods. For welding automatic argon-arc welding (AAAW) equipment was used for of orbital welding, which includes a MW 2600 current source (FRONIUS) with software control unit and welding head of closed type MW40. Research warks showed that this type of welding is not enough for such small thicknesses concentration of the welding arc, which does not allow stable forming of the bath and obtaining solid uniform seam. A special robotic complex was used for microplasma welding STARWELD 190H, which includes: a power source for the regular arc INV 50; source main arc power supply INV 190; SIEMENS Simatic S 7-300 control unit; robot CR3-535M (MITSUBISHI); manipulator and HPH 80 plasmatron. Welding quality control was carried out by visual inspection and metallographic examination. Taking into account the conditions of operation of the parts, according to the technical conditions of the drawing, it was also provided pneumohydraulic control method. Obtained results. Visual inspection the outer surface of the welds showed the absence of defects in the form of pores, cracks, shells, no fusions, undercuts, etc. The geometric dimensions of the weld met the requirements of the standard documentation valid at the enterprise. Metallographic studies of the boxes membranes, welded by microplasma welding, gave a positive result. Defects of metallurgical character were not found in the welds. Practical value. The optimal method of welding that can be applied is determined for the manufacture of thin-walled membrane structures, from the point of view of manufacturability and economy expediency It has been established that microplasma welding allows obtaining a hermetically tight seam, when the thickness of parts to be welded is about 0.15 mm. The performance of welded membrane boxes is confirmed in the barostatic valve of an aircraft engine. It is established that micro plasma welding can be used in the manufacture of thin-walled shells made of 12X18H10T steel (δ=0.15 mm), which work at variable loads. The technological process of welding is introduced into the series production.

Multimodal flexible electronic skin with adjustable module size for robot collision detection

Purpose This paper aims to present a modular multimodal flexible electronic skin that can be used for robot collision detection in human–robot interactions. This type of electronic skin will meet the requirements of performance indicators such as sensing mode, sensing domain coverage and dynamic data update rate in human–robot interactions. Design/methodology/approach The electronic skin uses a modular architecture, and the sensing module is designed to be adjustable in size so that it can be easily deployed on complex robot surfaces, increasing area coverage, reducing power consumption, and improving data update rates. Findings The authors evaluated electronic skin through experiments using a UR5 robot. Electronic skin has high static scene perception differentiation and dynamic scene perception abilities. Moreover, the robot realizes a high-speed collision response based on the electronic skin proposed in this study. Originality/value The proposed electronic skin provides crucial technical support for advancing robotic technologies, and holds promising prospects for industrial applications.

DESIGN FEATURES OF THE MANIPULATOR-MOTOR FOR MULTI-PURPOSE ROBOTIC PLATFORMS

It has been established that the use of multi-purpose robotic platforms (MPRP), as one of the types of ground robotic complexes, is an important factor that allows preserving the life and health of servicemen on the battlefield. It was found that the movement of MPRP, and as a result, the performance of assigned tasks, is often limited (loss of stability and passability) as a result of difficult terrain areas, or as a result of destruction caused by enemy fire. The well-known approaches that allow to ensure the multi-functionality of individual parts of the MPRP to improve their stability and passability were analyzed and it was established that they do not realize in their design features the use of multi-functional manipulators, which, if necessary, can perform the functions of a stepping or wheel drive. A new approach is proposed, which consists in the application of multi-functional manipulators (manipulators-movers) on the MPRP, which, in the event of extreme movement conditions, can, in addition to the manipulator function (grab, transfer of objects), perform the function of a walking or wheeled mover (ensuring movement over areas of the terrain). The results of designing and modeling in the Solid Works software environment are presented. An analysis of the design features of the manipulator-mover for MPRP was carried out and it was established that the multi- functionality of the manipulator-mover is implemented by introducing new elements and connections, in particular, in the manipulator mode, with minimal mass-dimensional parameters, an increase in the available space is achieved with the possibility of endless rotational movements of the captured object in any direction, and in the driver mode, when four manipulators-drivers are located on top of the MPRP in pairs, symmetrically on both sides, the functions of stepping or wheel drivers are provided.

Learning Curve for Robotic Colorectal Surgery.

With the increasing adoption of robotic surgery in clinical practice, institutions intending to adopt this technology should understand the learning curve in order to develop strategies to help its surgeons and operating theater teams overcome it in a safe manner without compromising on patient care. Various statistical methods exist for the analysis of learning curves, of which a cumulative sum (CUSUM) analysis is more commonly described in the literature. Variables used for analysis can be classified into measures of the surgical process (e.g., operative time and pathological quality) and measures of patient outcome (e.g., postoperative complications). Heterogeneity exists in how performance thresholds are defined during the interpretation of learning curves. Factors that influence the learning curve include prior surgical experience in colorectal surgery, being in a mature robotic surgical unit, case mix and case complexity, robotic surgical simulation, spending time as a bedside first assistant, and being in a structured training program with proctorship.

Effectiveness of the Walkbot system in patients with infantile cerebral palsy

BACKGROUND: Estimating the effectiveness of robotic mechanotherapy is crucial in the rehabilitation of children with cerebral palsy. AIM: To evaluate the effectiveness of the Walkbot robotic complex (Walkbot, Korea) in children with cerebral palsy. MATERIALS AND METHODS: The study included 35 patients with infantile cerebral palsy who received courses of rehabilitation therapy based on the state autonomous institution “City Children’s Polyclinic No. 7.” A comparative analysis of the functional motor outcomes between two groups of children with cerebral palsy was performed. Group 1 was treated with locomotor therapy on the Walkbot, whereas group 2 was not prescribed with the apparatus. RESULTS: The effect of using the Walkbot mechanotherapeutic complex on functional motor outcomes in patients with infantile cerebral palsy was evaluated. Better dynamics of the level of motor skills development on the GMFM-66 scale was noted in group 1 (by 6.8% in group 1 and 4.1% in group 2; p=0.006). The Hauser index (p=0.05) indicated an improvement in locomotor function, which increased the level of independence in everyday life according to the FIM scale (p=0.044), compared to the data of children in the control group. Attaining the effect depends on the number of procedures and total number of rehabilitation courses. CONCLUSION: Children with cerebral palsy who received the Walkbot therapy have better motor outcomes, primarily relating to locomotor function.

Methodology for assessing the effectiveness of innovations, robotization and automation in the automotive industry

The current trend in the automotive industry confirms that innovation and process automation are increasingly helping the industry’s development and economic growth. In addition to the digitalisation of society, new technologies are also being actively developed. The economic development of a country is inextricably linked to the development of process innovation, process automation and robotisation. In this paper, the theoretical background of innovation approaches in the automotive industry and performance evaluation methodologies have been discussed. Industrial robots and robotic technological complexes, which are universally used in industry, have existed for about 50 years and at the present moment of time replace humans and displace them from the sphere of production to the sphere of services and control. To ensure balanced economic development, the Government of the Republic of Kazakhstan closely monitors the main economic sectors and endeavours to support domestic manufacturers in every possible way. The automobile industry is no exception. The purpose of this article is to conduct a brief theoretical review of the state of the automobile industry, as well as to study foreign experience. We have studied the methodology of economic efficiency assessment. The study showed that innovation, robotisation and automation undoubtedly lead to the economic development of both regions and the country as a whole.

Visual-Tactile Perception Based Control Strategy for Complex Robot Peg-in-Hole Process via Topological and Geometric Reasoning

Visual-Tactile Perception Based Control Strategy for Complex Robot Peg-in-Hole Process via Topological and Geometric Reasoning