Search Results (332)

Advanced two-dimensional (2D) beam steering is essential for unlocking the full potential of terahertz (THz) systems in future 6G communications and high-resolution imaging. However, achieving wide-angle, high-speed, and high-precision 2D beam control within a compact THz platform remains a significant challenge. In this work, we experimentally demonstrate an optoelectronic $2\times 2$ THz antenna array that enables flexible 2D beam steering, beam hopping, and beam scanning around the 300 GHz band. This work employs a $2\times 2$ microstrip patch antenna (MPA) array directly driven by InGaAs/InP UTC-PDs on a silicon carbide (SiC) substrate. The relative phases of the four radiating elements are precisely programmed using an optical phased array (OPA), which provides fully decoupled and low-latency phase control in the optical domain. Experimentally, we demonstrate 2D beam steering and 2D beam hopping among three representative directions at a polar angle of ${25}^{\circ }$ and azimuth angles of ${60}^{\circ }$, ${180}^{\circ }$, and ${300}^{\circ }$. Furthermore, continuous 2D beam scanning at a fixed polar angle of ${25}^{\circ }$ is achieved, enabling a full ${360}^{\circ }$ azimuth sweep within 0.43 s while maintaining high beam quality. These results confirm that the proposed UTC-PD based $2\times 2$ MPA array provides a practical and robust approach for 2D THz beam manipulation, and offers strong potential for future 6G wireless links and THz imaging applications. Full article

Inspired by the adaptive flexible motion coordination of biological systems, this study presents a bioinspired control strategy that enables robotic manipulators to achieve precise and compliant motion–force coordination for embodied intelligence and dexterous interaction in physically constrained environments. To this end, a learning-based motion–force hybrid control (LMFC) framework is proposed, which unifies learning and kinematic-level control to regulate both motion and interaction forces under incomplete or implicit kinematic information, thereby enhancing robustness and precision. The LMFC formulation recasts motion–force coordination as a time-varying quadratic programming (TVQP) problem, seamlessly incorporating multiple practical constraints—including joint limits, end-effector orientation maintenance, and obstacle avoidance—at the acceleration level, while determining control decisions at the velocity level. An RNN-based controller is further designed to integrate adaptive learning and control, enabling online estimation of uncertain kinematic parameters and mitigating joint drift. Simulation and experimental results demonstrate the effectiveness and practicality of the proposed framework, highlighting its potential for adaptive and compliant robotic control in constraint-rich environments. Full article

Robust control over the coupling and propagation of surface plasmon polaritons (SPPs) is essential for advancing various plasmonic applications. Traditional planar structures, commonly used to design SPP directional couplers, face limitations such as low extinction ratios and design complexities. These issues frequently hinder the dense integration and miniaturisation of photonic systems. Recently, exceptional points (EPs)—unique degeneracies within the parameter space of non-Hermitian systems—have garnered significant attention for enabling a range of counterintuitive phenomena in non-conservative photonic systems, including the non-trivial control of light propagation. In this work, we develop a rigorous temporal coupled-mode theory (TCMT) description of a non-Hermitian metagrating composed of alternating silicon–germanium nanostrips and use it to explore the unidirectional excitation of SPPs at EPs in the visible spectrum. Within this framework, EPs, typically associated with the coalescence of eigenvalues and eigenstates, are leveraged to manipulate light propagation in nonconservative photonic systems, facilitating the refined control of SPPs. By spatially modulating the permittivity profile at a dielectric–metal interface, we induce a passive parity–time ($\mathcal{PT}$)-symmetry, which allows for refined tuning of the SPPs’ directional propagation by optimising the structure to operate at EPs. At these EPs, a unidirectional excitation of SPPs with a directional intensity extinction ratio as high as 40 dB between the left and right excited SPP modes can be reached, with potential applications in integrated optical circuits, visible communication technologies, and optical routing, where robust and flexible control of light at the nanoscale is crucial. Full article

Underwater Vehicle-Manipulator Systems (UVMSs) play a critical role in various marine operations, where the choice of manipulator architecture significantly influences system performance. While serial robotic arms have been widely adopted in UVMS applications due to their operational flexibility, their inherent structural characteristics present certain challenges in underwater environments. These challenges primarily stem from the cumulative effects of joint mechanisms and dynamic interactions with the fluid medium. In this context, we explore an innovative UVMS solution that incorporates the Delta parallel mechanism, which offers distinct advantages through its symmetrical architecture and unilateral motor configuration, particularly in maintaining operational stability. We develop a comprehensive framework that includes mechanical design optimization, implementation of distributed control systems, and formulation of closed-form kinematic models, with comparative analysis against conventional serial robotic arms. Experimental validation demonstrates the system’s effectiveness in underwater navigation, target acquisition, and object manipulation under operator-guided control. The results reveal substantial enhancements in motion consistency and gravitational stability compared to traditional serial-arm configurations, positioning the Delta-based UVMS as a viable solution for complex underwater manipulation tasks. Furthermore, this study provides a comparative analysis of the proposed Delta-based UVMS and conventional serial-arm systems, offering valuable design insights and performance benchmarks to inform future development and optimization of underwater manipulation technologies. Full article

This study develops a robust pneumatic control system for soft robots that require multi-cavity coordination. It proposes an FPGA-based hybrid valve pneumatic system (HVPS) with networked control and multi-mode pressure regulation to enhance performance in complex tasks. The system integrates a hybrid valve unit (a negative-pressure proportional valve + solenoid valves) to support four pressure regulation modes, implements an FPGA-based PWM/DAC control for scalability, and utilizes EtherCAT (Ethernet for Control Automation Technology) for real-time networked synchronization. The experimental results demonstrate that the HVPS can achieve variable-frequency PWM (VF-PPRM) and variable-duty-ratio PWM (VDR-PPRM), controlling a Multi-Layer Soft Sponge Robot (ML-SSR) to perform better crawling behaviors at frequencies ranging from 0.2 Hz to 0.33 Hz and duty ratios ranging from 30% to 50%. ML-SSRs could perform manipulation and synchronization following behavior using a closed-loop proportional regulation module (CPRM) and networked connection, with the mean square errors (MSEs) of 0.85 around the X-axis and 1.03 around the Y-axis. This work uniquely integrates FPGA-based hybrid valve control with EtherCAT networking, introduces multi-mode pressure regulation within a single pneumatic unit, and offers a scalable architecture for soft robotic systems, thereby enhancing the flexibility and performance of pneumatic control. Full article

Industrial Robots (IRs) are typically employed as flexible machines to perform many types of repetitive and intensive tasks within fenced safe areas, ensuring high productivity and cost efficiency. However, their rigid programming approaches often pose challenges during cell commissioning and reset, hindering the implementation of self-reconfigurable systems. In addition, several production lines still need the presence of skilled operators to conduct assisted assembly operations and inspections. This motivates the growing interest in the development of innovative solutions for supporting safe and efficient human–robot collaborative applications. The manual guidance of the IR end-effector is a representative functionality of such collaboration, as it simplifies heavy-part manipulation and allows intuitive robot teaching and programming. The present study reports a sensor-based approach for enabling manual guidance operations with high-payload IRs and discusses its practical implementation on a production cell with an extended workspace. The setup features a KUKA robot mounted on a custom linear track actuated via Beckhoff technology to enable flexible assembly and machining operations. The developed logic and its software configuration, split into multiple control units to allow the manual guiding of both the 6-axis IR and the linear track unit, are described in detail. Finally, an experimental demonstration involving two users with different levels of expertise was conducted to evaluate the approach during target teaching on a physical cell. The results showed that the proposed manual guidance method significantly reduced task completion time by more than 55% compared with the conventional teach pendant, demonstrating the effectiveness and practical advantages of the developed framework. Full article

Power line sag monitoring is critical for ensuring transmission system reliability and optimizing grid capacity utilization. Traditional sag detection methods rely on hyperbolic cosine models that assume ideal catenary behavior under uniform loading conditions. However, these models impose restrictive assumptions about weight distribution and suspension conditions that limit accuracy under real-world scenarios involving wind loading, ice accumulation, and non-uniform environmental forces. This study introduces a novel Bézier curve-based mathematical framework for transmission line sag detection and monitoring. Unlike traditional hyperbolic cosine approaches, the proposed methodology eliminates idealized assumptions and provides enhanced flexibility for modeling actual conductor behavior under variable environmental conditions. The Bézier curve approach offers enhanced precision and computational efficiency through intuitive control point manipulation, making it well suited for Dynamic Line Rating (DLR) applications. Experimental validation was performed using a controlled laboratory setup with a 1:100 scaled transmission line model. Results demonstrate improvement in sag measurement accuracy, achieving an average error of 1.1% compared to 6.15% with traditional hyperbolic cosine methods—representing an 82% improvement in measurement precision. Statistical analysis over 30 independent experiments confirms measurement consistency with a 95% confidence interval of [0.93%, 1.27%]. The framework also demonstrates a 1.5 to 2 times increase in computational efficiency improvement over conventional template matching approaches. This mathematical framework establishes a robust foundation for advanced transmission line monitoring systems, with demonstrated advantages for power grid applications where traditional catenary models fail due to non-ideal environmental conditions. The enhanced accuracy and efficiency support improved Dynamic Line Rating implementations and grid modernization efforts. Full article

In advanced spectroscopy, the classical symmetric optical frequency comb is limited in temporal flexibility and selection freedom, which constrains the efficiency and stability of quantum manipulation. To overcome this limitation, we propose a method to realize precise energy-level manipulation using a femtosecond non-temporally symmetric optical frequency comb in the semiclassical three-level system. Numerical calculations show that the fall time of the pulse is the key parameter to realize the precise manipulation, and a shorter fall time contributes to the efficient accumulation of population. By optimizing the pulse parameters, 99.15% accumulation of population in the target state can be successfully achieved and stably maintained using an asymmetric slowly turned-on and rapidly turned-off (STRT) pulse train. Our demonstration of the non-temporally symmetric optical frequency comb provides a promising approach to efficient quantum-state preparation using spectral modulation. Full article

This paper proposes a novel design method for multifunctional modular metasurfaces based on cascaded multilayer modules. Strong electromagnetic coupling between cascaded modules and balanced interface impedance achieved through optimized resonator configurations enable broadband operation. By pairwise cascading of the three modules to maximize utilization and achieve maximum channel count, the system realizes comprehensive electromagnetic wavefront manipulation across 4 broadband frequency ranges, demonstrating diverse functionalities including orbital angular momentum beam generation, polarization conversion, beam splitting, and radar cross-section reduction with 7 operational channels: two reciprocal co-polarized transmission channels at 14–20.7 GHz, individual reflection channels in +z and −z spaces at 32–38 GHz, two reciprocal cross-polarized transmission channels at 11.9–13.2 GHz, and a reflection channel in −z space at 20–28 GHz, spanning both transmission and reflection modes. The proposed cascading method is accomplished through direct attachment assembly, avoiding air coupling while enabling rapid installation and fast functional switching, providing flexibility for multifunctional electromagnetic wave control applications. Full article

The cyber–physical integrated power distribution system is poised to become the predominant trend in the development of future power systems. Although the highly intelligent panoramic link information system in substations facilitates the efficient, cost-effective, and secure operation of the power system, it is also exposed to dual threats from both internal and external factors. Under intentional cyber information attacks, the operational data and equipment response capabilities of the panoramic link information system within smart substations can be illicitly manipulated, thereby disrupting dispatcher response decision-making and resulting in substantial losses. To tackle this challenge, this paper delves into the research on automatic verification and active defense mechanisms for the cyber–physical power distribution system under panoramic link attacks in smart substations. Initially, to mitigate internal risks stemming from the uncertainty of new energy output information, this paper utilizes a CGAN-IK-means model to generate representative scenarios. For scenarios involving external intentional cyber information attacks, this paper devises a fixed–flexible adjustment resource response strategy, making up for the shortfall in equipment response capabilities under information attacks through flexibility resource regulation. The proposed strategy is assessed based on two metrics, voltage level and load shedding volume, and computational efficiency is optimized through an enhanced firefly algorithm. Ultimately, the efficacy and viability of the proposed method are verified and demonstrated using a modified IEEE standard test system. Full article

Conventional vibrational systems associated with proprioception are mostly equipped with a single standard frequency and amplitude. This feature often fails to show kinesthetic illusion on different subjects, as different individuals respond to different frequencies and amplitudes. Additionally, different muscle groups may also require the flexibility of frequencies and amplitudes. We developed a custom vibrational system that is equipped with flexible frequency and amplitude, adapted to a custom graphical user interface (GUI). Based on the user’s criteria, the proposed vibrational system enables a wide range of frequencies and amplitudes that can be swept under a single platform. In addition, the system uses small linear actuators that are wearable and attach to the subject without the need for restrictive straps. The vibrational system was used to model trunk proprioceptive impairment associated with low back pain. Low back pain is the leading cause of disability worldwide. It is mostly associated with impaired postural control of the trunk. For postural control, the somatosensory system transmits proprioceptive (position sense) information from the sensors in the skin, joints, muscles, and tendons. Proprioceptive studies on trunk muscles have been conducted where the application of vibration at a set amplitude and frequency across all participants resulted in altered proprioception and a kinesthetic illusion, but not in all individuals. To assess the feasibility of the system, we manipulated the trunk proprioception of five subjects, demonstrating that the vibrational system is capable of modulating trunk proprioception and the value of customizing parameters of the system to obtain maximal deficits from individual subjects. Full article

This research aims to actively suppress vibrations at the end-effector of a flexible manipulator. When configured in a locked state, the system behaves as a two-link manipulator subjected to disturbances on the first link. To analyze its behavior, Finite Element Analysis (FEA) is employed to extract the natural frequencies (eigenvalues) and corresponding mode shapes (eigenvectors) of a two-link, two-joint flexible manipulator (2L2JM). The obtained eigenvectors are transformed into uncoupled state-space equations using balanced realization and the Match-DC-Gain model reduction algorithm. An H-infinity controller is then designed and applied to both the full-order and reduced-order models of the manipulator. The objective of this study is to validate an analytical framework through FEA, demonstrating its applicability to complex manipulators with multiple joints and flexible links. Given that the full state-space representation typically results in high-dimensional matrices, model reduction enables effective vibration control with a minimal number of states. The derivation of the 2L2JM state space, its model reduction, and a subsequent control strategy have not been previously addressed in this manner. Simulation results showcasing vibration suppression of a cantilever beam are presented and benchmarked against two alternative modeling approaches. Full article

Aphids remain exceptional models for symbiosis research due to their unique experimental advantages that extend beyond documenting symbiont-mediated phenotypes. Nine commonly occurring facultative bacterial symbionts provide well-characterized benefits, including defense against parasitoids, pathogens, and thermal stress. Yet the system’s greatest value lies in enabling diverse research applications across biological disciplines through experimental tractability combined with ecological realism. Researchers can create controlled experimental lines through symbiont manipulation, maintain clonal host populations indefinitely, and cultivate symbionts independently. This experimental power is complemented by extensive knowledge of symbiont dynamics in natural populations, including temporal and geographic distribution patterns—features generally unavailable in other insect-microbe systems. These advantages facilitate investigation of key processes in symbiosis, including transmission dynamics, mechanisms, strain-level functional diversity, multi-partner infections, and transitions from facultative to co-obligate relationships. Integration across biological scales—from genomics to field ecology—enables research on symbiont community assembly, ecological networks, coevolutionary arms races, and agricultural applications. This combination of experimental flexibility, comprehensive natural history knowledge, and applied relevance positions aphids as invaluable for advancing symbiosis theory while addressing practical challenges in agriculture and invasion biology. Full article

The art of folding paper, named “origami”, has transformed from serving religious and cultural purposes to various educational and entertainment purposes in the modern world. Significantly, the fundamental folds and creases in origami, which enable the creation of 3D structures from a simple flat sheet with unique crease patterns, serve as a great inspiration in engineering applications such as deployable mechanisms for space exploration, self-folding structures for exoskeletons and surgical procedures, micro-grippers, energy absorption, and programmable robotic morphologies. Therefore, this paper will provide a systematic review of the state-of-the-art origami-inspired structures that have been adopted and exploited in robotics design and operation, called origami-inspired robots (OIRs). The advantages of the flexibility and adaptability of these folding mechanisms enable robots to achieve agile mobility and shape-shifting capabilities that are suited to diverse tasks. Furthermore, the inherent compliance structure, meaning that stiffness can be tuned from rigid to soft with different folding states, allows these robots to perform versatile functions, ranging from soft interactions to robust manipulation and a high-DOF system. In addition, the potential to simplify the fabrication and assembly processes, together with its integration into a wide range of actuation systems, further broadens its capabilities. However, these mechanisms increase the complexity in theoretical analysis and modelling, as well as posing a challenge in control algorithms when the robot’s DOF and reconfigurations are significantly increased. By leveraging the principles of folding and integrating actuation and design strategies, these robots can adapt their shapes, stiffness, and functionality to meet the demands of diverse tasks and environments, offering significant advantages over traditional rigid robots. Full article

As the industrial automation landscape advances, the integration of sophisticated perception and manipulation technologies into robotic systems has become crucial for enhancing operational efficiency and precision. This paper presents a significant enhancement to a robotic system by incorporating the Mask R-CNN deep learning algorithm and the Intel^® RealSense™ D435 camera with the UFactory xArm 5 robotic arm. The Mask R-CNN algorithm, known for its powerful object detection and segmentation capabilities, combined with the depth-sensing features of the D435, enables the robotic system to perform complex tasks with high accuracy. This integration facilitates the detection, manipulation, and precise placement of single objects, achieving 98% detection accuracy, 98% gripping accuracy, and 100% transport accuracy, resulting in a peak manipulation accuracy of 99%. Experimental evaluations demonstrate a 20% improvement in manipulation success rates with the incorporation of depth data, reflecting significant enhancements in operational flexibility and efficiency. Additionally, the system was evaluated under adversarial conditions where structured noise was introduced to test its stability, leading to only a minor reduction in performance. Furthermore, this study delves into cybersecurity concerns pertinent to robotic systems, addressing vulnerabilities such as physical attacks, network breaches, and operating system exploits. The study also addresses specific threats, including sabotage and service disruptions, and emphasizes the importance of implementing comprehensive cybersecurity measures to protect advanced robotic systems in manufacturing environments. To ensure truly robust, secure, and reliable robotic operations in industrial environments, this paper highlights the critical role of international cybersecurity standards and safety standards for the physical protection of industrial robot applications and their human operators. Full article