Search Results (35)

Manual window cleaning in high-rise urban buildings is labor-intensive, risky, and resource-inefficient. This study addresses these challenges by investigating a resource-aware mechatronic architecture through the design, development, and experimental validation of a modular Automated Window Cleaning System (AWCS). Unlike conventional open-loop solutions, the AWCS integrates mechanical scrubbing with a closed-loop fluid management system, featuring precise dispensing and vacuum-assisted recovery. The system is governed by a deterministic finite state machine implemented on an ESP32 microcontroller, enabling low-latency IoT connectivity and autonomous operation. Two implementation variants—integrated and retrofit—were validated to ensure structural adaptability. Experimental results across 30 cycles demonstrate a cleaning efficiency of ~2 min/m², a water consumption of <150 mL/m² (representing a >95% reduction compared to manual methods), and an optical cleaning efficacy of 96.9% ± 1.4%. Safety protocols were substantiated through a calculated mechanical safety factor of 6.12 for retrofit applications. This research establishes the AWCS as a sustainable, safe, and scalable solution for autonomous building maintenance, contributing to the advancement of resource-circular domestic robotics and smart home automation. Full article

Artificial intelligence (AI) is driving the evolution of autonomous agriculture towards multi-agent collaborative control, breaking through the limitations of traditional isolated automation. Although existing research has focused on hierarchical control and perception-decision-making technologies for agricultural machinery, the overall integration of these elements in building a resilient physical perception collaborative system is still insufficient. This paper systematically reviews the progress of AI-driven tractor-implement cooperative control from 2018 to 2025, focusing on four major technical pillars: (1) perception-decision-execution hierarchical architecture, (2) distributed multi-agent collaborative framework, (3) physical perception modeling and adaptive control, and (4) staged operation applications (such as collaborative harvesting). The research reveals core challenges such as real-time collaborative planning, perception robustness under environmental disturbances, and collaborative control and safety assurance under operational disturbances. To this end, three solutions are proposed: an AI framework for formalizing agronomic constraints and mechanical dynamics; a disturbance-resistant adaptive tractor-implement cooperative control strategy; and a real-time collaborative ecosystem integrating neuromorphic computing and FarmOS. Finally, a research roadmap is summarized with agronomic constraint reinforcement learning, self-reconfigurable collaboration, and biomechanical mechatronic systems as the core. By integrating the scattered progress in AI, robotics and agronomy, we provide theoretical foundation and practical guidance for scalable and sustainable autonomous farm systems. Full article

This study introduces an innovative self-regulating intelligent optimal balancing control framework for inverted pendulum-type mechatronic platforms, designed to enhance reference tracking accuracy and improve disturbance rejection capability. The control procedure is synthesized by synergistically integrating a baseline Linear Quadratic Regulator (LQR) with a fuzzy controller via a customized linear decomposition function (LDF). The LDF dissociates and transforms the LQR control law into compounded state tracking error and tracking error derivative variables that are eventually used to drive the fuzzy controller. The principal contribution of this study lies in the adaptive modulation of these compounded variables using reconfigurable tangent hyperbolic functions driven by the cubic power of the error signals. This nonlinear preprocessing of the input variables selectively amplifies large errors while attenuating small ones, thereby improving robustness and reducing oscillations. Moreover, a model-free online self-tuning law dynamically adjusts the variation rates of the hyperbolic functions through dissipative and anti-dissipative terms of the state errors, enabling autonomous reconfiguration of the nonlinear preprocessing layer. This dual-level adaptation enhances the flexibility and resilience of the controller under perturbations. The robustness of the designed controller is substantiated via tailored experimental trials conducted on the Quanser rotary pendulum platform. Comparative results show that the prescribed scheme reduces pendulum angle variance by 41.8%, arm position variance by 34.6%, and average control energy by 28.3% relative to the baseline LQR, while outperforming conventional fuzzy-LQR by similar margins. These results show that the prescribed controller significantly enhances disturbance rejection and tracking accuracy, thereby offering a numerically superior control of inverted pendulum systems. Full article

The origin of life initiated an evolutionary continuum yielding biologically optimized systems capable of operating under extreme environmental constraints. Biomimetics, defined as the systematic abstraction and transfer of biological principles into engineering domains, has become a strategic design paradigm for addressing the multifactorial challenges of space systems. This study introduces two core contributions to formally establish the discipline of Aerospace Bionic Robotics (ABR): First, it elucidates the relevance of biologically derived functionalities such as autonomy, adaptability, and multifunctionality to enhance the efficiency of space robotic platforms operating in microgravity environments. Second, it proposed the BEAM-D (Biomimetic Engineering and Aerospace Mechatronics Design), a standard for the development of Aerospace Bionic Robotics. By integrating biological abstraction levels (morphological, functional, and behavioral) with engineering protocols including ISO, VDI, and NASA’s TRL, BEAM-D enables a structured design pathway encompassing subsystem specification, cyber–physical integration, in situ testing, and full-scale mission deployment. It is implemented through a modular BEAM-DX framework and reinforced by iterative BIOX design steps. This study thus establishes formalized bio-inspired design tools for advanced orbital and planetary robotic systems capable of sustained autonomous operations in deep space exploration scenarios. Full article

The field of haircutting robots is poised for a significant transformation, driven by advancements in artificial intelligence, mechatronics, and humanoid robotics. This perspective paper examines the emerging market for haircutting robots, propelled by decreasing hardware costs and a growing demand for automated grooming services. We review foundational technologies, including advanced hair modeling, real-time motion planning, and haptic feedback, and analyze their application in both teleoperated and fully autonomous systems. Key technical requirements and challenges in safety certification are discussed in detail. Furthermore, we explore how cutting-edge technologies like direct-drive systems, large language models, virtual reality, and big data collection can empower these robots to offer a human-like, personalized, and efficient experience. We propose a business model centered on supervised autonomy, which enables early commercialization and sets a path toward future scalability. This perspective paper provides a theoretical and technical framework for the future deployment and commercialization of haircutting robots, highlighting their potential to create a new sector in the automation industry. Full article

Several types of self-balancing vehicles have been successfully developed and commercialized in the past two decades, both as manned vehicles and as autonomous mobile robots. At the same time, due to their characteristic instability and underactuation, a large body of research has been devoted to their control. However, despite this practical and theoretical interest, the current publicly available literature does not cover their systematic design and development. In particular, overall processes that lead to a finished vehicle starting from a set of requirements and specifications have not been examined in the literature. Within this context, this paper contributes a comprehensive mechatronic, dynamics-based procedure for the design of this class of vehicles; to promote clarity of exposition, the procedure is systematically presented using Model-Based Systems Engineering tools and principles. In particular, the proposed design method is developed and formalized starting from an original description of the vehicle, which is treated as a complex system composed of several interconnected multi-domain components that exchange power and logical flows through suitable interfaces. A key focus of this work is the analysis of these exchanges, with the goal of defining a minimal set of quantities that should be necessarily considered to properly design the vehicle. As a salient result, the design process is organized in a logical sequence of steps, each having well-defined inputs and outputs. The procedure is also graphically outlined using standardized formalisms. The design method is shown to cover all the mechanical, electrical, actuation, measurement and control components of the system, and to allow the unified treatment of a large variety of different vehicle variants. The procedure is then applied to a specific case study, with the goal of developing the detailed design of a full-scale vehicle. The main strengths of the proposed approach are then widely highlighted and discussed. Full article

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is reshaping curricula from K–12 to postgraduate levels. This paper analyzes instructional models including project-based learning, laboratory work, capstone design courses, and robotics competitions, highlighting their effectiveness in developing both technical and creative competencies. Widely adopted platforms such as the Robot Operating System (ROS) are briefly discussed in the context of their educational value and real-world alignment. Through case studies, institutional insights, and synthesis of academic and industry practices, this review underscores the vital role of robotics education in fostering innovation, systems thinking, and workforce readiness. The paper concludes by identifying the key challenges and future directions to guide researchers, educators, industry stakeholders, and policymakers in advancing robotics as both technological and educational frontiers. Full article

This article presents a series of innovative systems developed through student laboratory projects, comprising two autonomous vehicles, a quadrupedal walking robot, an active ankle-foot orthosis, a ball-on-beam balancing mechanism, a ball-on-plate system, and a manipulator arm, all actuated by pneumatic artificial muscles (PAMs). Due to their flexibility, low weight, and compliance, fluidic muscles demonstrate substantial potential for integration into various mechatronic systems, robotic platforms, and manipulators. Their capacity to generate smooth and adaptive motion is particularly advantageous in applications requiring natural and human-like movements, such as rehabilitation technologies and assistive devices. Despite the inherent challenges associated with nonlinear behavior in PAM-actuated control systems, their biologically inspired design remains promising for a wide range of future applications. Potential domains include industrial automation, the automotive and aerospace sectors, as well as sports equipment, medical assistive devices, entertainment systems, and animatronics. The integration of self-constructed laboratory systems powered by PAMs into control systems education provides a comprehensive pedagogical framework that merges theoretical instruction with practical implementation. This methodology enhances the skillset of future engineers by deepening their understanding of core technical principles and equipping them to address emerging challenges in engineering practice. Full article

Rice is the predominant grain crop in China, with its consumption showing a steady annual increase. Due to the diminishing labor force, China’s rice cultivation industry faces significant challenges and has an urgent requirement for automated rice transplanters. This study developed an agricultural navigation system integrating mechatronic-hydraulic control with navigation technologies to automate the rice transplanter’s driving and operational processes. The designed automation devices enable precise control over functions such as steering and working clutch. A path planning methodology was proposed to generate straight-line reference paths by giving target points and to determine the headland turning pattern based on the working width and turning radius of the rice transplanter. Additionally, an operational control strategy based on the finite state machine (FSM) was developed, enabling effective switching of the rice transplanter’s operational states through the designation of key points. The test results showed that the maximum lateral error of the rice transplanter along straight-line paths was 4.83 cm on the cement pavement and 6.30 cm in the field, with the maximum error in determining key points being 7.22 cm in the field. These results indicate that the agricultural navigation system developed in this study can achieve the automation of rice transplanters and provide certain inspiration for the research of autonomous agricultural vehicles. Full article

This paper focuses on the mathematical and numerical modeling of a non-classical macro fiber composite (MFC) piezoelectric transducer, MFC-P2, integrated with an aluminum cantilever beam for energy harvesting applications. It seeks to harness the transverse vibration energy in the environment to power small electronic devices, such as wireless sensors, where conventional power sources are inconvenient. The P2-type macro fiber composites (MFC-P2) are specifically designed for transverse energy harvesting applications. They offer high electric source capacitance and improved electric charge generation due to the strain developed perpendicularly to the voltage produced. The system is modeled analytically using Euler–Bernoulli beam theory and piezoelectric constitutive equations, capturing the electromechanical coupling in the d31 mode. Numerical simulations are conducted using COMSOL Multiphysics 6.29 to reduce the complexity of the mathematical model and analyze the effects of material properties, geometric configurations, and excitation conditions. The theoretical model is based on the transverse vibrations of a cantilevered beam using Euler–Bernoulli theory. The natural frequencies and mode shapes for the first four are determined. Depending on these, the resonance frequency, voltage, and power outputs are evaluated across a 12 kΩ resistive load. The results demonstrate that the energy harvester effectively operates near its fundamental resonant frequency of 10.78 Hz, achieving the highest output voltage of approximately 0.1952 V and a maximum power output of 0.0031 mW. The generated power is sufficient to drive ultra-low-power devices, validating the viability of MFC-based cantilever structures for autonomous energy harvesting systems. The application of piezoelectric phenomena and obtaining electrical energy from mechanical vibrations can be powerful solutions in such systems. The application of piezoelectric phenomena to convert mechanical vibrations into electrical energy presents a promising solution for self-powered mechatronic systems, enabling energy autonomy in embedded sensors, as well as being used for structural health monitoring applications. Full article

Given increasingly complex threats, adapting surveillance approaches to meet the necessary security levels is essential. The aim of this paper is to develop a surveillance architecture based on autonomous mechatronic systems (mobile robots and drones) designed to secure areas of strategic interest, covering a predefined space while providing enhanced security at minimal costs. Designing such a system is challenging due to the need for continuous monitoring, raising issues around autonomy, as well as the design of the navigation and command and control systems. This paper presents key surveillance systems, demonstrating their efficiency and further development potential. This paper discusses the steps taken to enable a team of autonomous mobile robots to monitor a known indoor location by using a specialized positioning system. Steps are taken to deploy, implement, and configure the said indoor global positioning system (GPS). Among those steps, a study is performed by attaching one of the mobile beacons to a linear axis and moving said axis to known points. This position is read by both the axis and the positioning system, and the results are compared. Full article

The integration of AI and robotics in healthcare raises concerns, and additional issues regarding autonomous systems are anticipated. Effective communication is crucial for robots to be seen as “caring”, necessitating advanced mechatronic design and natural language processing (NLP). This paper examines the potential of humanoid robots to autonomously replicate compassionate care. The study employs computational simulations using mathematical and agent-based modeling to analyze human–robot interactions (HRIs) surpassing Tetsuya Tanioka’s TRETON. It incorporates stochastic elements (through neuromorphic computing) and quantum-inspired concepts (through the lens of Martha Rogers’ theory), running simulations over 100 iterations to analyze complex behaviors. Multisensory simulations (visual and audio) demonstrate the significance of “dynamic communication”, (relational) “entanglement”, and (healthcare system and robot’s function) “superpositioning” in HRIs. Quantum and neuromorphic computing may enable humanoid robots to empathetically respond to human emotions, based on Jean Watson’s ten caritas processes for creating transpersonal states. Autonomous AI humanoid robots will redefine the norms of “caring”. Establishing “pluralistic agreements” through open discussions among stakeholders worldwide is necessary to align innovations with the values of compassionate care within a “posthumanist” framework, where the compassionate care provided by Level 4 robots meets human expectations. Achieving compassionate care with autonomous AI humanoid robots involves translating nursing, communication, computer science, and engineering concepts into robotic care representations while considering ethical discourses through collaborative efforts. Nurses should lead the design and implementation of AI and robots guided by “technological knowing” in Rozzano Locsin’s TCCN theory. Full article

Grasping and object manipulation have been considered key domains of Cyber-Physical Systems (CPS) since the beginning of automation, as they are the most common interactions between systems, or a system and its environment. As the demand for automation is spreading to increasingly complex fields of industry, smart tools with sensors and internal decision-making become necessities. CPS, such as robots and smart autonomous machinery, have been introduced in the meat industry in recent decades; however, the natural diversity of animals, potential anatomical disorders and soft, slippery animal tissues require the use of a wide range of sensors, software and intelligent tools. This paper presents the development of a smart robotic gripper for deployment in the meat industry. A comprehensive review of the available robotic grippers employed in the sector is presented along with the relevant recent research projects. Based on the identified needs, a new mechatronic design and early development process of the smart gripper is described. The integrated force sensing method based on strain measurement and magnetic encoders is described, including the adjacent laboratory and on-site tests. Furthermore, a combined slip detection system is presented, which relies on an optical flow-based image processing algorithm using the video feed of a built-in endoscopic camera. Basic user tests and application assessments are presented. Full article

This review focuses on the complex connections between machine learning, mechatronics, and stretch forming, offering valuable insights that can lay the groundwork for future research. It provides an overview of the origins and fundamentals of these fields, emphasizes notable progress, and explores the influence of these fields on society and industry. Also highlighted is the progress of robotics research and particularities in the field of sheet metal forming and its various applications. This review paper focuses on presenting the latest technological advancements and the integrations of these fields from their beginnings to the present days, providing insights into future research directions. Full article

In recent years, social assistive robots have gained significant acceptance in healthcare settings, particularly for tasks such as patient care and monitoring. This paper offers a comprehensive overview of the expressive humanoid robot, Qhali, with a focus on its industrial design, essential components, and validation in a controlled environment. The industrial design phase encompasses research, ideation, design, manufacturing, and implementation. Subsequently, the mechatronic system is detailed, covering sensing, actuation, control, energy, and software interface. Qhali’s capabilities include autonomous execution of routines for mental health promotion and psychological testing. The software platform enables therapist-directed interventions, allowing the robot to convey emotional gestures through joint and head movements and simulate various facial expressions for more engaging interactions. Finally, with the robot fully operational, an initial behavioral experiment was conducted to validate Qhali’s capability to deliver telepsychological interventions. The findings from this preliminary study indicate that participants reported enhancements in their emotional well-being, along with positive outcomes in their perception of the psychological intervention conducted with the humanoid robot. Full article