Search Results (816)

The paper presents a shared control strategy that allows a human operator to physically guide the end-effector of a robotic manipulator to perform different tasks, possibly in interaction with the environment. To switch among different operational modes referring to a finite state machine algorithm, ElectroMyoGraphic (EMG) signals from the user’s arm are used to detect muscular contractions and to interact with a variable admittance control strategy. Specifically, a Support Vector Machine (SVM) classifier processes the raw EMG data to identify three classes of contractions that trigger the activation of different sets of admittance control parameters corresponding to the envisaged operational modes. The proposed architecture has been experimentally validated using a Kinova Jaco² manipulator, equipped with force/torque sensor at the end-effector, and with a limited group of users wearing Delsys Trigno Avanti EMG sensors on the dominant upper limb, demonstrating promising results. Full article

Nephronophthisis (NPH) is the leading genetic cause of end-stage renal disease in children and young adults, but no effective disease-modifying therapies are currently available. Here, we identify glucagon-like peptide-1 (GLP-1) signaling as a novel therapeutic target for NPH through a systematic drug repurposing screen in zebrafish. By simultaneously depleting nphp1 and nphp4, we developed a robust zebrafish model that reproduces key features of human NPH, including glomerular cyst formation. Our screen revealed that dipeptidyl peptidase-4 (DPP4) inhibitors (Omarigliptin and Linagliptin) and GLP-1 receptor agonists (Semaglutide) significantly reduce cystogenesis in a dose-dependent manner. Genetic analysis demonstrated that GLP-1 receptor signaling is important for maintaining pronephros integrity, with gcgra and gcgrb (GLP-1 receptor genes) playing a particularly important role. Transcriptomic profiling identified adenosine receptor A2ab (adora2ab) as a key downstream effector of GLP-1 signaling, which regulates ciliary morphology and prevents cyst formation. Notably, nphp1/nphp4 double mutant zebrafish exhibited the upregulation of gcgra as a compensatory mechanism, which might explain their resistance to cystogenesis. This compensation was disrupted by the targeted depletion of GLP-1 receptors or the inhibition of adenylate cyclase, resulting in enhanced cyst formation, specifically in the mutant background. Our findings establish a signaling cascade from GLP-1 receptors to adora2ab in terms of regulating ciliary organization and preventing cystogenesis, offering new therapeutic opportunities for NPH through the repurposing of FDA-approved medications with established safety profiles. Full article

In Aerial Manipulation, the motion of the robotic arm can cause unwanted movements of the flying base affecting the trajectory tracking capability. A possible solution to reduce these disturbances is to use a free revolute joint between the flying base and the manipulator, thus reducing the torque applied to the base from the manipulator. In this paper, a novel approach to solve the inverse kinematics of an aerial manipulator with a free revolute joint is presented. The approach exploits the Generalized Jacobian to deal with the presence of a mobile base, and the dynamics of the system is considered to predict the motion of the non-actuated joint; external forces acting on the system are also included. The method is implemented in MATLAB for a planar case considering the parameters of a real manipulator attached to a real octocopter. The tracking of a trajectory with the end-effector and a load picking task are simulated for a non-redundant and for a redundant manipulator. Simulation results demonstrate the capability of this approach in following the desired trajectories and reducing rotation and horizontal translation of the base. Full article

This paper studies the dynamic parameters identification problem of load and linkages of a serial robot in the presence of model uncertainty. The dynamic parameters of load and linkages of a serial robot have been identified through a combination procedure, which is useful for different platforms of serial robot systems. The purpose of this paper is to propose a dynamic parameter identification method for a serial robot based on a dual quaternion. Using the information of the force and torque of the load obtained by the six-dimensional force sensor installed on the end-effector of the robot, the dynamics parameter identification matrix of the load is derived, which also uses the information of motion speed and acceleration of the end-effector. On the other hand, the analysis of the dynamic relationship between adjacent linkages and the joints is based on dual quaternion algebra, and the identification matrix for the dynamic parameters and the difference values of associated linkages are derived, as well. The combination procedure of the method is flexible in the application of dynamic parameters identification for a serial robot using a dual quaternion. Furthermore, the proposed DQ (dual quaternion)-based method in this paper has the advantage of lower cost compared with the RBFNN (radial basis function neural network)-based method. The effectiveness of the proposed dynamic parameter identification method for a serial robot has been verified by relevant experiments. Full article

This research addresses the enhancement of operational efficiency in apple-picking robots through the design of a bimanual spatial configuration enabling obstacle avoidance in contemporary orchard environments. A parallel coordinated harvesting paradigm for dual-arm systems was introduced, leading to the construction and validation of a six-degree-of-freedom bimanual apple-harvesting robot. Leveraging the kinematic architecture of the AUBO-i5 manipulator, three spatial layout configurations for dual-arm systems were evaluated, culminating in the adoption of a “workspace-overlapping Type B” arrangement. A functional prototype of the bimanual apple-harvesting system was subsequently fabricated. The study further involved developing control architectures for two end-effector types: a compliant gripper and a vacuum-based suction mechanism, with corresponding operational protocols established. A networked communication framework for parallel arm coordination was implemented via Ethernet switching technology, enabling both independent and synchronized bimanual operation. Additionally, an intersystem communication protocol was formulated to integrate the robotic vision system with the dual-arm control architecture, establishing a modular parallel execution model between visual perception and motion control modules. A coordinated bimanual harvesting strategy was formulated, incorporating real-time trajectory and pose monitoring of the manipulators. Kinematic simulations were executed to validate the feasibility of this strategy. Field evaluations in modern Red Fuji apple orchards assessed multidimensional harvesting performance, revealing 85.6% and 80% success rates for the suction and gripper-based arms, respectively. Single-fruit retrieval averaged 7.5 s per arm, yielding an overall system efficiency of 3.75 s per fruit. These findings advance the technological foundation for intelligent apple-harvesting systems, offering methodologies for the evolution of precision agronomic automation. Full article

This paper presents studies of a digital twin system. A conceptual model of the system is proposed to be used to control an industrial robot and can be integrated into different fields of application such as industry, manufacturing, farming, livestock breeding and others. On the principle of software engineering, the overall architecture of the system is developed, and its constituent elements are presented in detail. A kinematic analysis of the considered industrial robot is presented. To realize the digital twin, a simulation model of the industrial robot was developed to fully meet the dimensions and kinematic characteristics of the real one. Experiments have been made on the operation of the system so as to compare the movements of the real and simulated robot. The results obtained show almost identical motions both in the end effector of the robots and in the motions of each of the joints. A short methodology for the steps of creating systems using digital twins is presented to assist developers and scientists. Full article

As a core component of a fully automatic pepper transplanter, the performance of the seedling-picking mechanism is of particular significance. However, existing seedling-picking mechanisms have problems such as being prone to damaging the seedling roots and substrate, as well as having poor stability. To develop a highly efficient, stable, and minimally damaging seedling-picking mechanism, this study proposed a design scheme for a stem-clamping-and-pulling-out-type seedling-picking end actuator driven by a non-circular gear system. The specific methods and objectives include the following: (1) designing a differential non-circular gear system to replicate a manual picking trajectory accurately; (2) establishing a kinematic model and developing optimization software to determine the optimal parameter combination; (3) experimentally validating the mechanism’s performance through virtual simulations and bench tests. The bench tests showed that the mechanism could complete two seedling-picking operations per rotation, extracting an entire row (eight plants) in a single rotation at a speed of 30 r/min. The measured angles of the end effector at four key postures were highly consistent with simulation and high-speed camera data, with all key posture errors less than 1°. These results demonstrate the mechanism’s high accuracy, efficiency, and reliability. Full article

This study presented an autonomous shield-cutting end-effector for maize surrounding weeding (SEMSW), addressing the challenges of the low weed removal rate (WRR) and high seedling damage rate (SDR) in northern China’s 3–5 leaf stage maize. The SEMSW integrated seedling positioning, robotic arm control, and precision weeding functionalities: a seedling positioning sensor identified maize seedlings and weeds, guiding XYZ translational motions to align the robotic arm. The seedling-shielding anti-cutting mechanism (SAM) enclosed crop stems, while the contour-adaptive weeding mechanism (CWM) activated two-stage retractable blades (TRWBs) for inter/intra-row weeding operations. The following key design parameters were determined: 150 mm inner diameter for the seedling-shielding disc; 30 mm minimum inscribed-circle for retractable clamping units (RCUs); 40 mm ground clearance for SAM; 170 mm shielding height; and 100 mm minimum inscribed-circle diameter for the TRWB. Mathematical optimization defined the shape-following weeding cam (SWC) contour and TRWB dimensional chain. Kinematic/dynamic models were introduced alongside an adaptive sliding mode controller, ensuring lateral translation error convergence. A YOLOv8 model achieved 0.951 precision, 0.95 mAP50, and 0.819 mAP50-95, striking a balance between detection accuracy and localization precision. Field trials of the prototype showed 88.3% WRR and 2.2% SDR, meeting northern China’s agronomic standards. Full article

Series elastic actuators (SEAs) represent a key technological solution to enhance safety, performance, and adaptability in robotic devices for physical training. Their ability to decouple the rigid actuator’s mechanical impedance from the load, combined with passive absorption of external disturbances, makes them particularly suitable for pediatric applications. In children aged 2 to 5 years—where motor control is still developing and movements can be unpredictable or unstructured—SEAs provide a compliant mechanical response that ensures user protection and enables safe physical interaction. This study explores the role of SEAs as a central component for imparting compliance and backdrivability in robotic systems designed for upper-limb training. A dynamic model is proposed, incorporating interaction with the user’s limb, along with a computed torque control strategy featuring integral action. The system’s performance is validated through simulations and experimental tests, demonstrating stable trajectory tracking, disturbance absorption, and effective impedance decoupling. The results support the use of SEAs as a foundational technology for developing safe adaptive robotic solutions in pediatric contexts capable of responding flexibly to user variability and promoting secure interaction in early motor development environments. Full article

This study presents a quasi-static optimization framework for the pressure-based control of a multi-segment soft continuum manipulator. The proposed method circumvents traditional curvature and length-based modeling by directly identifying the quasi-static input–output relationship between actuator pressures and the 6-DoF end-effector pose. Experimental data were collected using a high-frequency electromagnetic tracking system under monotonic pressurization to minimize hysteresis effects. Transfer functions were identified for each coordinate–actuator pair using the System Identification Toolbox in MATLAB, and optimal actuator pressures were computed analytically by solving a constrained quadratic program via a manual active-set method. The resulting control strategy achieved sub-millimeter positioning error while minimizing the number of actuators engaged. The approach is computationally efficient, sensor-minimal, and fully implementable in open-loop settings. Despite certain limitations due to sensor nonlinearity and actuator hysteresis, the method provides a robust foundation for feedforward control and the real-time deployment of soft robots in quasi-static tasks. Full article

Protein functional effector (pfe)RNAs were introduced in 2015 as PIWI-interacting-like small noncoding (nc)RNAs and were later categorized as a novel group based on being 2′-O-methylated at their 3′-end, directly binding and affecting protein function, but not levels, and not matching known RNAs. Here, we document that human pfeRNAs match fragments of GenBank database-annotated human ncRNAs. PDLpfeRNAa matches the 3′-half fragment of a mitochondrial transfer (t)RNA, and PDLpfeRNAb matches a 28S ribosomal (r)RNA fragment. These PDLpfeRNAs are known to bind to tumor programmed death ligand (PD-L)1, enhancing or inhibiting its interaction with lymphocyte PD-1 and consequently tumor immune escape, respectively. In a validated 8-pfeRNA-set classifier for pulmonary nodule presence and benign vs. malignant nature, seven here match one or more of the following: transfer, micro, Y, PIWI, long (lnc)RNAs, and a PDLpfeRNAa fragment. The previously identified chromosomal locations of these pfeRNAs and their matches partially overlap. Another 2-pfeRNA set was previously determined to distinguish between controls, patients with pulmonary tuberculosis, and those with lung cancer. One pfeRNA, previously shown to bind p60-DMAD and affect apoptosis, complements small nucleolar RNA SNORD45C, matching smaller 18S rRNA and lncRNA segments. Thus, pfeRNAs appear to have a common origin with known multifunctional ncRNA fragments. Differential modification may contribute to the multifunctionality of ncRNAs. For instance, for tRNA fragments, stabilizing 3′-end 2′-O-methylation, 3′-aminoacylation, and glycosylation modifications may regulate protein function, translation, and extracellular effects, respectively. One ncRNA gene can encode multiple fragments, multiple genes can encode the same fragment, and differentially modified ncRNA fragments might synergize or antagonize each other. Full article

The commercialization of selective broccoli harvesters, a critical response to agricultural labor shortages, is hampered by end effectors with large operational envelopes and poor adaptability to complex field conditions. To address these limitations, this study developed and evaluated a novel end-effector with an integrated transverse cutting mechanism and a foldable grasping cavity. Unlike conventional fixed cylindrical cavities, our design utilizes actuated grasping arms and a mechanical linkage system to significantly reduce the operational footprint and enhance maneuverability. Key design parameters were optimized based on broccoli morphological data and experimental measurements of the maximum stem cutting force. Furthermore, dynamic simulations were employed to validate the operational trajectory and ensure interference-free motion. Field tests demonstrated an operational success rate of 93.33% and a cutting success rate of 92.86%. The end effector successfully operated in dense planting environments, effectively avoiding interference with adjacent broccoli heads. This research provides a robust and promising solution that advances the automation of broccoli harvesting, paving the way for the commercial adoption of robotic harvesting technologies. Full article

Although artificial intelligence technologies have significantly enhanced autonomous robots’ capabilities in perception, decision-making, and planning, their autonomy may still fail when faced with complex, dynamic, or unpredictable environments. Therefore, it is critical to enable users to take over robot control in real-time and efficiently through teleoperation. The lightweight, wearable myoelectric armband, due to its portability and environmental robustness, provides a natural human–robot gesture interaction interface. However, current myoelectric teleoperation gesture control faces two major challenges: (1) poor intuitiveness due to visual-motor misalignment; and (2) low efficiency from discrete, single-degree-of-freedom control modes. To address these challenges, this study proposes an integrated myoelectric teleoperation interface. The interface integrates the following: (1) a novel hybrid reference frame aimed at effectively mitigating visual-motor misalignment; and (2) a finite state machine (FSM)-based control logic designed to enhance control efficiency and smoothness. Four experimental tasks were designed using different end-effectors (gripper/dexterous hand) and camera viewpoints (front/side view). Compared to benchmark methods, the proposed interface demonstrates significant advantages in task completion time, movement path efficiency, and subjective workload. This work demonstrates the potential of the proposed interface to significantly advance the practical application of wearable myoelectric sensors in human–robot interaction. Full article

Recent years have seen significant interest among agricultural researchers in using robotics and machine vision to enhance intelligent orchard harvesting efficiency. This study proposes an improved hybrid framework integrating YOLO VX deep learning, 3D object recognition, and SLAM-based navigation for harvesting ripe fruits in greenhouse environments, achieving servo control of robotic arms with flexible end-effectors. The method comprises three key components: First, a fruit sample database containing varying maturity levels and morphological features is established, interfaced with an optimized YOLO VX model for target fruit identification. Second, a 3D camera acquires the target fruit’s spatial position and orientation data in real time, and these data are stored in the collaborative robot’s microcontroller. Finally, employing binocular calibration and triangulation, the SLAM navigation module guides the robotic arm to the designated picking location via unobstructed target positioning. Comprehensive comparative experiments between the improved YOLO v12n model and earlier versions were conducted to validate its performance. The results demonstrate that the optimized model surpasses traditional recognition and harvesting methods, offering superior target fruit identification response (minimum 30.9ms) and significantly higher accuracy (91.14%). Full article

Traditional path-planning algorithms for robotic manipulators typically focus on end-effector planning, often neglecting complete collision avoidance for the entire manipulator. Additionally, many existing approaches suffer from high time complexity and are easily trapped in local extremes. To address these challenges, this paper proposes a goal-biased bidirectional artificial potential field-based rapidly-exploring random tree* (GBAPF-RRT*) algorithm, which enhances both target guidance and obstacle avoidance capabilities of the manipulator. Firstly, we utilize a Gaussian distribution to add heuristic guidance into the exploration of the robotic manipulator, thereby accelerating the search speed of the RRT*. Then, we combine the modified repulsion function to prevent the random tree from trapping in a local extreme. Finally, sufficient numerical simulations and physical experiments are conducted in the joint space to verify the effectiveness and superiority of the proposed algorithm. Comparative results indicate that our proposed method achieves a faster search speed and a shorter path in complex planning scenarios. Full article