Robotic Systems and Applications: Table of Contents

Robotic micromanipulation: a) actuators and their application

Bučinskas, Vytautas — 2021-06-30T00:00:00Z

Robotic Systems and Applications, Vol. 1, Issue 1, 2021, p. 2-23.
Vytautas Bučinskas, Jurga Subačiūtė-Žemaitienė, Andrius Dzedzickis, Inga Morkvėnaitė-Vilkončienė
Development of biotechnology and technologies related to small size object position and placement in working area, ensuring desired orientation and fitting during movement into prescribed positions. Paper provides an effort to classify and provide a sorted list of applications in the variety of existing robotic systems to manipulate the object of micrometric size. Extensive development of robotic systems fosters intensive request of accurate and fast drives for robots and manipulators. Paper overviews and specifies a broad spectrum of micrometric scale drives, operating under certain physical effects. These drives are analyzed according to their physical domain, movement mode, stroke or angle range, generated force, speed of movement and other essential drive parameters. The paper concludes a high potential of drives development and points direction to future their application possibilities in microrobotics.

Design of a high-payload Mecanum-wheel ground vehicle (MWGV)

Chen, Zi-Yin — 2021-06-30T00:00:00Z

Robotic Systems and Applications, Vol. 1, Issue 1, 2021, p. 24-34.
Zi-Yin Chen, Pei-Ren Liaw, Vu Linh Nguyen, Po Ting Lin
With the rapid developments of Industry 4.0 and Smart Manufacturing, customized manufacturing has been becoming greatly needed. Meanwhile, the challenge of production automation has become more bigger, especially for the automation of moving, picking, placing and manipulating objects. Many researchers have begun to work on Autonomous Ground Vehicles (AGVs). Most AGVs were utilized to carry middle or small objects, as the high-payload AGVs were rarely developed. This paper focused on the design of a High-Payload Mecanum-Wheel Ground Vehicle (MWGV), which was 1.7 m wide and 2.04 m long. The weight of the vehicle was 740 kg and it was able to carry the payload as its own weight (i.e. around 7,300 N). The safety factor of the structural strength was greater than 1.66 and the safety factor of the axial design was at least 6.24. The vehicle was designed to carry 150-kg weight with a reach of 1.375 m without falling. The design of Mecanum wheels provided great flexibility on movement with small rotational radius. Mathematical descriptions about how Mecanum wheels were controlled was also introduced in this paper. Furthermore, the mechatronics and software integrations were demonstrated. The final experimental results showed the developed MWGV was able to perform the desired movement properly.

Editor’s Letter

2021-06-30T00:00:00Z

Robotic Systems and Applications, Vol. 1, Issue 1, 2021, p. 1-1.

Positioning algorithm for AGV autonomous driving platform based on artificial neural networks

Bałazy, Patryk — 2021-08-11T00:00:00Z

Robotic Systems and Applications, Vol. 1, Issue 2, 2021, p. 41-45.
Patryk Bałazy, Paweł Gut, Paweł Knap
This paper presents an artificial intelligence algorithm responsible for the autonomy of a platform. The proposed algorithm allows the platform to move from an initial position to a set one without human intervention and with understanding and response to the dynamic environment. The implementation of such a task is possible by using a combination of a camera identifying the environment with a laser LIDAR sensor and a vision system. The signals from the sensors are analysed through convolutional neural networks. Based on AI inference, the platform makes decisions, including determining the optimal path for itself. A transfer learning method will be used to teach the neural network. This article presents the results of learning the applied neural algorithm.

Cyber-physical universal safety and crash detection system for autonomous robot

Pikner, Heiko — 2021-09-07T00:00:00Z

Robotic Systems and Applications, Vol. 1, Issue 2, 2021, p. 46-52.
Heiko Pikner, Mohsen Malayjerdi
Multi-purpose mobile robots with a modular layout have become a hot research topic in recent years. The safe performance of these robot’s operations is relying on the low-level cyber-physical system (CPS). In this paper, the scientific goals underscore the analysis of the computational (cyber) units for low-level real-time fault monitoring. The purpose of these units is to monitor control signals issued by other (cyber) units or sensors and if there is a safety-critical problem, then predefined actions can be triggered. The safety controller was built and tested on the TalTech iseAuto platform. Based on the results, a new multi-layer universal safety system was developed. In the first layer, all signals and messages are checked to be in a suitable range or order. The second layer detects if an accident is happening using crash sensors. The third layer includes remote control switches support. If a failure or malfunction occurs, the emergency action plan is executed to stop the vehicle safely.

Convolutional mask-wearing recognition algorithm for an interactive smart biometric platform

Bałazy, Patryk — 2021-09-13T00:00:00Z

Robotic Systems and Applications, Vol. 1, Issue 2, 2021, p. 35-40.
Patryk Bałazy, Paweł Gut, Paweł Knap
This paper presents the results of a neural convolutional system for recognizing the wearing of a mask by people entering a building. The algorithm is provided with input data thanks to cameras placed in the humanoid robot COVIDguard. The data collected by the humanoid – the temperature of people entering the facility, the location of the person, the way the protective mask was applied – are stored in the cloud, which enables the application of advanced image recognition algorithms and, consequently, the tracking of people within the range of the robot’s sensory systems by the administrator and the verification of the security level in the given premises. The paper presents the architecture of the intelligent COVIDguard platform, the structure of the sensory system and the results of the neural network learning.

Temperature difference measurement with using two RTD sensors as example of evaluating uncertainty of a vector output quantity

Idzkowski, Adam — 2021-11-05T00:00:00Z

Robotic Systems and Applications, Vol. 1, Issue 2, 2021, p. 53-58.
Adam Idzkowski, Zygmunt Warsza
The evaluation of results in the case of indirect multi-parameter measurements is presented. A theoretical basis for determining the estimates of values, the uncertainties and the correlation coefficients of indirectly obtained multi-measurand is explained in detail. The example of a difference and an average of two-temperature indirect measurement is given with the use of two RTDs. Such sensors are used in the laboratory and industrial temperature control systems. The uncertainty of measurements depends on the errors of two RTDs and the structure of signal conditioning circuit.

Construction and benchmark of an autonomous tracked mobile robot system

Ahluwalia, Vaibhav — 2022-06-30T00:00:00Z

Robotic Systems and Applications, Vol. 2, Issue 1, 2022, p. 15-28.
Vaibhav Ahluwalia, Janis Arents, Aly Oraby, Modris Greitans
Robots require a certain set of skills to perceive and analyse the environment and act accordingly. For tracked mobile robots getting good odometry data from sensory information is a challenging key prerequisite to perform in an unstructured dynamic environment, thus an essential issue in the tracked mobile robotics domain. In this article, we construct a ROS-based tracked mobile robot system taking the Jaguar V4 mobile robot as the base platform. On which several visual odometry solutions based on different cameras and methods (Intel RealSense T265, Zed camera, RTAB-Map RGBD) are integrated and benchmark comparison is performed. Analysis of new challenges faced by different methods while applied on a tracked vehicle as well as recommendations and conclusions are presented. Intel RealSense T265 solution proved to perform well in uncertain conditions which involves bounded vibrations and low lighting conditions with low latency, which result in good map generation. Further evaluations with a path planning algorithm and Intel RealSense T265 were conducted to test the effect of the robot’s motion profiles on odometry data accuracy.

Robotic micromanipulation: b) grippers for biological objects

Bučinskas, Vytautas — 2022-06-30T00:00:00Z

Robotic Systems and Applications, Vol. 2, Issue 1, 2022, p. 1-14.
Vytautas Bučinskas, Jurga Subačiūtė-Žemaitienė, Andrius Dzedzickis, Ernestas Šutinys, Inga Morkvėnaitė-Vilkončienė
Recent progress in the field of microrobotics tightly linked to an ability to grab an object firmly without the damage to the surface and structure. Process of biological object grabbing by microgrippers faces numerous limitations in the mechanical, electric and thermal domains; these limitations varies from case to case with different objects, therefore, analysis in this area was an aim of this review. This paper covers an area of micrometric size biological object manipulation and performs an analysis of used actuators and kinematic chains of the grippers in the sense of their application. Limitations and restriction of microgrippers applications analysed along available publications in numerous recent references as well as their successful implementation history. Paper provides result of analysis as compact big picture, which will be useful for researchers and designers in the area of microrobotics.

Research of the dynamical properties of mechatronic prosthesis

Tamošiūnas, Justas — 2022-12-31T00:00:00Z

Robotic Systems and Applications, Vol. 2, Issue 2, 2022, p. 29-42.
Justas Tamošiūnas, Vytautas Bučinskas
The mechatronic ankle prosthesis plays a crucial role in the recreation of natural gait biomechanics by being able to actively control time-torque parameters in different sub-phases of the walking cycle. This paper presents a methodology for improving the design process of the individual characteristics of the object of interest. A series of tests were taken to derive a correlation between an actual structure and a developed mathematical model to determine the parameters of the object under investigation. The model provides a possibility to determine time-changing force-related properties to capture a full picture of the structure for which a particular design is being chosen. The method also acts as a tool to expand traditional design criteria to get the overall view of the structural dynamics of the mechanical system.

Designing and controlling a self-balancing platform mechanism based on 3-RCC spherical parallel manipulator

Chen, Yen Jung — 2023-03-02T00:00:00Z

Robotic Systems and Applications, Vol. 3, Issue 1, 2023, p. 1-16.
Yen Jung Chen, Wei-Cheng Tung, Wei-Rui Lee, Brijesh Patel, Vytautas Bučinskas, Modris Greitans, Po Ting Lin
Motion control platforms have various applications in the manufacturing and automation industries. Different literature provides multiple issues related to the kinematics and dynamics of self-guided robots for transportation regarding platform balancing. Self-balancing platforms are utilized in many deliveries, stabilization, and transportation systems, and they are especially well suited for outdoor activities when the ground surface is not flat or structured. This paper describes developing a control technique for a self-balancing platform using the 3-RCC spherical parallel manipulator. This mechanism was designed to support an AGV (Automated Guided Vehicle) for transporting and lifting heavy weights for industrial applications. The AGV carries a robotic arm on top for different tasks. When the AGV encounters a steep slope or a rough surface, the AGV tilts, and the robotic arm’s performance is significantly affected. So, this study gives a solution to avoid these circumstances with a novel approach for the platform’s self-balancing mechanism consisting of a 3-RCC spherical parallel manipulator. Real-time stabilization and kinematics analysis methods are used to achieve the self-balancing system of the platform. When both methods are observed through different tilting angles for automation stability, Kinematic analysis performs more efficiently with less time duration when compared with the real-time stabilization method.

Improving ride comfort and road friendliness of heavy truck using semi-active suspension system

Li, Hao — 2023-03-13T00:00:00Z

Robotic Systems and Applications, Vol. 3, Issue 1, 2023, p. 17-26.
Hao Li, Vanliem Nguyen
To enhance the ride comfort and improve the road friendliness of the heavy truck, based on the dynamic model of the heavy truck, the semi-active suspension system of the vehicle is proposed and controlled based on the fuzzy logic control and Matlab/Simulink software. The efficiency of the semi-active suspension system is then evaluated based on the indexes of the root mean square acceleration of the driver’s seat, the root mean square acceleration of the cab's pitching angle, and the dynamic load coefficient of the wheel axles. The results show that with the semi-active suspension system of the heavy truck controlled by the fuzzy logic control, the acceleration responses of the heavy truck and the dynamic forces of the wheel axles are greatly reduced in comparison with the passive suspension system under various operating conditions of the loads and speeds. Especially, with the semi-active suspension system controlled by the fuzzy logic control, the root mean square accelerations of the driver’s seat and cab pitch angle; and the dynamic load coefficient at 2nd axle of the wheel are clearly reduced by 23.7 %, 27.2 %, and 20.9 % in comparison with the passive suspension system, respectively. Thus, both ride comfort and road friendliness of the heavy truck are improved by the semi-active suspension system. In addition, the vehicle load insignificantly affects ride comfort. However, it greatly affects the road damage, especially with the half load condition of the vehicle. Thus, to improve road friendliness, the full load condition of the vehicle should be used.

Supplementation of synthetic object replicas for increasing precision of microrobot trajectory keypoints

Laizans, Modris — 2023-06-21T00:00:00Z

Robotic Systems and Applications, Vol. 3, Issue 1, 2023, p. 47-58.
Modris Laizans, Janis Arents, Oskars Vismanis, Vytautas Bučinskas, Andrius Dzedzickis, Modris Greitans
Artificial neural networks are becoming more popular with the development of artificial intelligence. These networks require large amounts of data to function effectively, especially in the field of computer vision. The quality of an object detector is primarily determined by its architecture, but the quality of the data it uses is also important. In this study, we explore the use of novel data set enhancement technique to improve the performance of the YOLOv5 object detector. Overall, we investigate three methods: first, a novel approach using synthetic object replicas to augment the existing real data set without changing the size of the data set; second - rotation augmentation data set propagating technique and their symbiosis, third, only one required class is supplemented. The solution proposed in this article improves the data set with a help of supplementation and augmentation. Lower the influence of the imbalanced data sets by data supplementation with synthetic yeast cell replicas. We also determine the average supplementation values for the data set to determine how many percent of the data set is most effective for the supplementation.

A review on path planning ai techniques for mobile robots

Deshpande, Shrinivas — 2023-06-25T00:00:00Z

Robotic Systems and Applications, Vol. 3, Issue 1, 2023, p. 27-46.
Shrinivas Deshpande, Abhishek Kumar Kashyap, Bhumeshwar K. Patle
An Industrial Robot is used in industries for transporting, assembly, manufacturing and many more applications. Industrial robots include manufacturing robots, material handling robots, robotic arm and manipulator, mobile robots, assembly robots, etc. In this paper, Mobile Robots are further being discussed. One of the tools that a Mobile Robot uses to function is all with the help of Artificial Intelligence (AI) for performing several tasks autonomously. AI works as the intelligence of the human body for robots. AI is the technology that made it possible for robots to be capable of being totally autonomous. AI marks its presence in the Manufacturing Industry with the 4th Industrial Revolution. AI has several algorithms that help in collecting and analyzing data in order to help robots to function in specific ways. These techniques include Fuzzy Logic, Genetic Algorithm, Neural Network, etc. In this paper, the role of these algorithms in Mobile Robots is discussed. Based on the review of 74 papers and articles, it is observed that there are no review papers discussing the role of nature-based and conventional algorithms used for navigation in Mobile Robots. The use of different AI techniques for specific applications has been discussed in tabular form in this paper.

Applications of collaborative robots in agile manufacturing: a review

Kakade, Siddhant — 2023-06-26T00:00:00Z

Robotic Systems and Applications, Vol. 3, Issue 1, 2023, p. 59-83.
Siddhant Kakade, Bhumeshwar Patle, Ashish Umbarkar
Collaborative robots are machines that work hand in hand with humans; or as the name suggests, collaborate with them in a specific workspace. These robots are not enclosed in confined safety zones like traditional robots, as they interact very closely with humans. Though this is the case, appropriate measures are captivated while designing these robots considering human safety. These robots are well-versed in adapting to changes and frequent upgrades. They are flexible enough to carry out complex tasks. Due to these abilities, they become a significant asset in the manufacturing field. It’s been many years now since cobots are introduced in the industry sector. So, this is the right time to review various applications of cobots in manufacturing. First, the paper starts with a brief introduction followed by an extensive literature review which was structured after reviewing 76 research papers and articles. It ends with some essential conclusions. This paper discusses the diverse applications of cobots used in the manufacturing sector and their advantages. Further, it highlights the future of cobots and how they will be a boon for a technology-driven world.

Feedback hybrid force and position control of an upper limb exoskeleton to support human movement

Nguyen, Thang Cao — 2023-11-19T00:00:00Z

Robotic Systems and Applications, Vol. 3, Issue 2, 2023, p. 84-97.
Thang Cao Nguyen, Anh Dong Nguyen, Manukid Parnichkun, My Thi Tra Phan
In the paper, a feedback hybrid control including a force feedback control and a position control is proposed to control a four degree of freedom (4-dof) upper limb exoskeleton for supporting human movement at the shoulder, elbow and wrist joints. The novelty of the paper is that it has been able to control all the interaction forces at all links in the exoskeleton robot by using the proposed control. The desired interaction forces at the links and desired position are compared with the measured interaction forces and position, respectively. Then the torque at the shoulder, the torque elbow and the torque wrist joints are controlled to compensate the force error and the position error. The gains of the proposed controller are optimized by using the Balancing Composite Motion Optimization (BCMO). The simulation and control of the 4-dof upper limb exoskeleton using the proposed control is carried out in the paper to show that the interaction forces and the position of the exoskeleton track their desired values.

A review on positioning techniques of mobile robots

Semborski, Jakub — 2024-02-17T00:00:00Z

Robotic Systems and Applications, Vol. 4, Issue 1, 2024, p. 30-43.
Jakub Semborski, Adam Idzkowski
In this article, we have reviewed the available positioning, localization and navigation techniques for mobile robots. Different localization techniques based on diverse technologies are compared with one another, along with diverse algorithms and techniques for analyzing this information. The article highlights algorithms based on odometry, triangulation, visual analysis, and marker detection. The analysis included global, local, and personal location. One acquires knowledge on which method is suitable for indoor use and which for outdoor use, as well as the appropriate environmental conditions for each. The accuracy of the individual methods was compared with that of integrated systems consisting of several methods. For practical knowledge, it is possible to determine whether a particular method is cost-effective for a particular solution and to compare the expenses involved.

Integration of robotics and automation in supply chain: a comprehensive review

Mohan Banur, Om — 2024-02-21T00:00:00Z

Robotic Systems and Applications, Vol. 4, Issue 1, 2024, p. 1-19.
Om Mohan Banur, B. K. Patle, Sachin Pawar
Robotics and automation have developed as key technologies for supply chain management as a result of the increased demand for quicker and more effective supply chains. Robotics and automation improve supply chain management by lowering long-haul expenses, boosting work and usage strength, reducing errors, declining repetitive stock checks, updating orchestrating, taking care of times, and assembling induction to the problematic and hazardous places. Robotics aids in design, creation, etc. Automation helps to do tasks that are often done by people through the use of self-operating physical machines, computer software, and other technology. Despite being widely accepted as a tool to aid in decision-making, supply chain management (SCM) has very seldom used AI and ML. This article investigates several AI and ML sub-fields that are best suited for resolving real-world SCM-related issues in order to fully realize the potential benefits of AI and Ml for SCM. In doing so, this article examines the track record of successful AI and ML applications to supply chain management and highlights the most fruitful SCM domains to apply AI and ML. And also find out the how robotics and automations helps in warehouse management. The most recent developments in robotics and automation for supply chain management are thoroughly reviewed in this paper. We first give a general overview of the difficulties that supply chain management faces before going over the many ways that robotics and automation are used at various points along the supply chain. Additionally, we go over the advantages of robots and automation in supply chain management, including higher efficiency, accuracy, lower costs, and improved safety. Lastly, we discuss some of the present drawbacks and difficulties associated with robots and automation in supply chain management and suggest some possible directions for further investigation.

Researching low frequency vibration of automobile-robot

Jia, Yujie — 2024-06-06T00:00:00Z

Robotic Systems and Applications, Vol. 4, Issue 1, 2024, p. 20-29.
Yujie Jia, Vanliem Nguyen
Automobile-robot (self-driving automobile) is being researched and developed vigorously. When the automobile-robot is moving on the road surface, the low frequency vibration excitation not only influences the ride comfort of the automobile-robot but also strongly affects the durability of the vehicle’s structures. To research the automobile-robot’s vibration in the low frequency region, a dynamic model of the vehicle is established to calculate the vibration equations in the time region. Based on the theory of the Laplace transfer function, the automobile-robot’s vibration equations in the time region are transformed and converted to the vibration equations in the frequency region. Then, the effect of the design parameters and operation parameters on the characteristic of the automobile-robot’s acceleration-frequency is simulated and analyzed to evaluate the ride comfort as well as the durability of the automobile-robot’s structures in the frequency region. The research results show that the design parameters of the stiffness, mass, and road wavelength remarkably affect the characteristic of the automobile-robot’s acceleration-frequency. To reduce the resonant amplitude of the acceleration-frequency in the vertical and pitching direction of the automobile-robot, the stiffness parameters of the automobile-robot's and tires should be reduced while the mass of the automobile-robot’s body should be increased. Additionally, the road’s roughness also needs to be decreased or the road’s quality needs to be enhanced to reduce the resonant amplitude of the automobile-robot’s acceleration-frequency.

Robotics and AI in museums – the future of the present

de Mello, Janaina Cardoso — 2024-12-31T00:00:00Z

Robotic Systems and Applications, Vol. 4, Issue 2, 2024, p. 44-58.
Janaina Cardoso de Mello, Gyamarco Pereira Nascimento Secci, Pedro Henrique Ribeiro
The contemporary concerns regarding the provision of Basic Education in the Humanities, capable of preparing students for cognitive exercise as critical citizens and professionals who meet the demands of the 21st century, underpin the inquiry that guided this project: “How can the Teaching of History and Cultural Heritage in Basic Education operate significantly in the face of new demands in the relationship between human societies and digital technologies?” It is understood that enabling technologies 4.0 also encompass Artificial Intelligence (AI) and Robotics (used in industry, but also in education), and their incorporation into teaching and learning for new generations is important. The BNCC (2017) emphasizes the importance of using material objects to assist teachers and students in questioning the meaning of things in the world, stimulating the production of historical knowledge in the school environment. Understanding this practice as an action in which teachers and students can play the role of agents in the teaching and learning process, both assuming a “historical attitude” towards the proposed contents. Therefore, the aim was to present the results of the research and technological developments carried out during the “SayHist – AI and Robotics in Museums of Sergipe” project, between 2022 and 2023, aiming to create a mini robot connected to an application capable of presenting exhibitions from two museums in Sergipe (Museum of Sergipe History – MUHSE) through audio and video, with speakers and a micro-projector.

A recent lower limb exoskeleton robot for gait rehabilitation: a review

Rakhmatillaev, Javlonbek — 2024-12-31T00:00:00Z

Robotic Systems and Applications, Vol. 4, Issue 2, 2024, p. 68-87.
Javlonbek Rakhmatillaev, Vytautas Bucinskas, Zafar Juraev, Nodirbek Kimsanboev, Umidjon Takabaev
Human rehabilitation improved significantly after traumas, surgery, or accidental cross-link events with human health. During the last six decades, exoskeletons have played a significant role in human activities related to body training and post-trauma or surgery treatment, especially in gait rehabilitation. The main goal of rehabilitation training is to restore patients’ physical abilities to average by improving and monitoring their posture and gaining weight. In this paper, a classification of various types of exoskeletons is provided, a comparison between the different lower limb exoskeletons for gait rehabilitation presents, the gait anatomy, mechanical design, and control strategy for the prototype of lower limb exoskeleton studies, and the end, some concluding remarks are stated that may be useful for future work. The paper concludes with conclusions and a significant reference list.

Object localization of channel robot using laser triangulation

Zulkifal, Muhammad — 2024-12-31T00:00:00Z

Robotic Systems and Applications, Vol. 4, Issue 2, 2024, p. 59-67.
Muhammad Zulkifal, Vytautas Bučinskas, Andrius Dzedzickis, Vygantas Ušinskis
Trajectory tracking and Object Localization in robots are developing rapidly, but the tasks are becoming increasingly complex and significantly increasing the range of tasks for robotic systems. Cognitive tasks in domestic, industrial or traffic conditions require not only the recognition of objects but also their evaluation by classifying them without direct recognition. One of such spheres are tunnels that are physically difficult for humans to reach and require diagnostics. In such an environment, it is difficult to globally define the direction and goal, so it is necessary to interpret the locally obtained information. To solve such a problem, sensor fusion is widely applied, but sensors of different physical natures do not allow to obtain the necessary information directly, so there is a great need to use AI to interpret and control the received information and generate the robot's trajectory [1]. Local navigation systems require a wide range of sensors [4]. Various cameras and time-of-flight LiDAR lasers are widely used. For the aforementioned reasons, an economical local trajectory generation and tracking system is being developed, one of the most important components for object recognition is the laser triangulation method. The essence of this method is that the camera reacts to the projection of the laser light in front of it and interprets the obstacle depending on its distortion. In this way, the camera's resources are more concentrated, and at the same time, a simple RGB camera is enough for this method. Also, this method is perfect in the dark, when the laser light is more pronounced. In this paper, the laser triangulation method will be reviewed in detail, evaluating its advantages and disadvantages.

Research on mechanical part recognition method based on improved mask R-CNN instance segmentation

Xiao, Kui — 2025-01-23T00:00:00Z

Robotic Systems and Applications, Vol. 5, Issue 1, 2025, p. 1-11.
Kui Xiao, Lei Wang, Haoran Xu, Pengchao Zhang, Heng Zhang
Aiming at the problem of poor part recognition due to mutual occlusion between parts and the influence of different postures in the assembly scene, we propose an improved Mask R-CNN-based part recognition method for complex scenes. Firstly, the ResNet101 network is used to enhance the feature extraction capability of the network and improve the part recognition effect; secondly, the normalization layer of the backbone network is replaced to reduce the effect of batch size on the feature extraction of the model; lastly, the feature pyramid network structure is improved to enhance the transfer efficiency between the high and low layers of the network, and to enhance the capability of the feature capture; through the experiments on the homemade dataset, the average detection accuracy of this method is 4.7 % higher than that of the original Mask R-CNN. Through the experiments on the homemade dataset, it is found that compared with the original Mask R-CNN, the average detection accuracy of the method is improved by 4.7 %.The optimized network model proposed in this paper can improve the accuracy of part recognition, realize the accurate detection of parts in the complex environment such as stacking, occlusion and so on, and provide a solution for the recognition of parts in the complex environment.

Optimum kinematic – dynamic performance of the reconfigurable delta robot through genetic algorithm optimization

Hasanlu, M. — 2025-06-02T00:00:00Z

Robotic Systems and Applications, Vol. 5, Issue 1, 2025, p. 28-49.
M. Hasanlu, M. Siavashi
Delta robots play a critical role in high-speed industrial applications due to their parallel kinematic structure, which provides superior precision, agility, and efficiency. This study presents a reconfigurable Delta robot with a novel structural adaptation mechanism, allowing geometric modifications to optimize its kinematic and dynamic performance. The research systematically derives the robot’s kinematic and dynamic equations, examines the impact of altering the structure of its chains, and applies genetic algorithm optimization to enhance its overall functionality. The influence of varying arm lengths, chain structures, and joint configurations is analyzed to determine their effects on workspace, actuator torque requirements, and operational stability. The findings indicate that optimized chain configurations improve workspace utilization by up to 15 %, reduce actuator torque by 12 %, and enhance end-effector speed by 8 %. By integrating structural adaptability and optimization techniques, this study demonstrates that the reconfigurable Delta robot achieves a superior balance between precision, speed, and energy efficiency. These advancements make it a promising solution for next-generation high-speed robotic applications in industries such as packaging, assembly, and medical automation.

Fuzzy adaptive back stepping control of wheeled mobile robot

Hasanlu, M. — 2025-06-28T00:00:00Z

Robotic Systems and Applications, Vol. 5, Issue 1, 2025, p. 12-27.
M. Hasanlu, M. Siavashi
Wheeled mobile robots (WMR) are unmanned vehicles and practical robots for industry and human life. The low-cost manufacturing, simple assembling, high-speed, lightweight design, and high observability and controllability of the WMRs have attracted the attention of engineering disciplines such as mechanical and electrical science. This paper focuses on the control of wheeled mobile robots through fuzzy adaptive back stepping (ABS). The mathematical model of WMR is divided into two types, including kinematic and dynamic analyses. Actually, this research analyzes the theoretical math model using hybrid methods such as fuzzy logic and adaptive back stepping (BS) to control WMR in both noisy and noiseless conditions along its path. On the other hand, this hybrid controller, because of its more robust performance, can track WMR on its targets. Because of this, WMR's ability to move around makes it choose fuzzy and adaptive back stepping (FABS) methods, which use model-based and time-dependent features, respectively. As a result, the signal inputs fuzzy membership functions, and then the fuzzy approach outputs a new signal that goes to the back-step adaptive controller to finalize the control effort to navigate WMR with the lowest error during its destinations.

An integrative review of control strategies in robotics

Rakhmatillaev, Javlonbek — 2025-07-10T00:00:00Z

Robotic Systems and Applications, Vol. 5, Issue 2, 2025, p. 50-74.
Javlonbek Rakhmatillaev, Vytautas Bucinskas, Nozimjon Kabulov
This paper presents an integrative review of control strategies in robotics, covering classical control methods (linear quadratic regulator, proportional-integral-derivative), modern methods (adaptive, sliding mode, model predictive, and H-infinity), intelligent control methods (neural network, fuzzy logic, and machine learning), and hybrid control methods (integration of classical, modern, and intelligent control methods) to identify the advantages, limitations and gaps for future. A brief comparison of control methods between the types of control strategies is conducted with respect to robustness, stability, and complexity of implementation on 3 different levels of evaluation criteria: high, average, and low; advantages; limitations; and robotic applications, including examples. This paper discusses the theoretical and practical advancements and the classification of control strategies according to controller types (linear, nonlinear, and learning-based), approaches (model-based and model-free), and classifications (centralized, decentralized, and modal control). The review highlights the strengths, limitations, and potential research directions in bridging classical, modern, intelligent, and hybrid control paradigms to achieve safe, efficient, and adaptive robotic behavior in complex, uncertain environments. We discuss the future direction: autonomy, human-robot collaboration, and enhanced learning and challenges: cost, reliability, safety of control strategies, concluding with recommendations for future research.

Maintenance, repair, and overhaul of robotic systems

Vieira, Guilherme E. — 2025-12-29T00:00:00Z

Robotic Systems and Applications, Vol. 5, Issue 2, 2025, p. 75-89.
Guilherme E. Vieira, Jeffrey W. Herrmann
This paper not only explores the fundamental aspects of but also brings new ideas for maintenance, repair, and overhaul (MRO) operations of robotic systems (RS). This synthesis is based on the limited scholarly research in this area and on information gathered from comprehensive web searches and analysis of corporate websites so that the results reflect the current views of RS developers and operators. The paper describes several crucial areas concerning RS MRO: maintenance of robotic systems, challenges and best practices for RS MRO, predictive maintenance variables and key performance indicators, data analytics, software solutions for RS MRO, and logistics/supply chain approach that should be considered. These insights provide not only a comprehensive understanding of the current state of RS MRO but also describe trends and suggestions for the future of RS MRO, emphasizing the novelty of the proposed research conducted. Key trends that organizations will need to address include the use of artificial intelligence (AI) models and the increasing importance of RS MRO logistics and supply chain management.