1,720,988 research outputs found
An Integrated Architecture for Robotic Assembly and Inspection of a Composite Fuselage Panel with an Industry 5.0 Perspective
No full textAeronautical robotic applications use quite large, heavy robots with huge end effectors that are frequently multifunctional. An assembly jig to hold a fuselage panel and two medium-sized six-axis robots fixed on linear axes, referred to as the internal and the external robot with respect to the curvature of the panel, make up the Lean robotized AssemBly and cOntrol of composite aeRostructures (LABOR) work cell. A distributed software architecture is proposed in which individual modules are developed to execute specific subprocesses, each implementing innovative algorithms that solve the main drawbacks of state-of-the-art solutions. Real-time referencing adopts a point-cloud-based strategy to reconstruct and process the part before drilling, avoiding hole positioning errors. Accurate concentric countersink diameters are made possible through the automatic adjustment of the drilling tool with respect to the skin panel, which guarantees its orthogonality, as well as the implementation of process parameter optimization algorithms based on historical results that compensate for the wear of the drilling bits. Automatic sealing and fastening strategies that involve the measurement of the main fastener quality parameters allow for the complete verification of the entire assembly process of each part. Additionally, an advanced multimodal perception system continuously monitors the collaborative workspace to ensure safe human–robot collaboration (HRC) tasks. Through this integrated architecture, LABOR substantially reduces expenses and facilitates maintenance and programming
A Hybrid Architecture for Safe Human–Robot Industrial Tasks
Full text linkIn the context of Industry 5.0, human–robot collaboration (HRC) is increasingly crucial for enabling safe and efficient operations in shared industrial workspaces. This study aims to implement a hybrid robotic architecture based on the Speed and Separation Monitoring (SSM) collaborative scenario defined in ISO/TS 15066. The system calculates the minimum protective separation distance between the robot and the operators and slows down or stops the robot according to the risk assessment computed in real time. Compared to existing solutions, the approach prevents collisions and maximizes workcell production by reducing the robot speed only when the calculated safety index indicates an imminent risk of collision. The proposed distributed software architecture utilizes the ROS2 framework, integrating three modules: (1) a fast and reliable human tracking module based on the OptiTrack system that considerably reduces latency times or false positives, (2) an intention estimation (IE) module, employing a linear Kalman filter (LKF) to predict the operator’s next position and velocity, thus considering the current scenario and not the worst case, and (3) a robot control module that computes the protective separation distance and assesses the safety index by measuring the Euclidean distance between operators and the robot. This module dynamically adjusts robot speed to maintain safety while minimizing unnecessary slowdowns, ensuring the efficiency of collaborative tasks. Experimental results demonstrate that the proposed system effectively balances safety and speed, optimizing overall performance in human–robot collaborative industrial environments, with significant improvements in productivity and reduced risk of accidents
Dynamic Safety Evaluation and Risk Mitigation Strategies for Collaborative Kitting
No full textThe Collaborative Kitting (CoKitting) approach in manufacturing combines human dexterity and robot repeatability to simplify assembly tasks, improving efficiency and safety. The proposed methodology aligns with the Industry 5.0 (I5.0) perspective, aiming at optimizing the collaborative task by proposing guidelines for both quantitative safety definition and reactive control algorithms. The first aspect is pursued by a review of the applicable norms and the development of advanced vision algorithms and AI-based strategies for the continuous human pose monitoring and behavioural models prediction with the objective of realising a real-time risk assessment. The second aspect anticipates interactions and minimises risks by introducing novel collision avoidance algorithms which re-plan in real time trajectories that avoid contact between the robot and any obstacles present in the work area, whether fixed or mobile, by considering the evaluated safety index
A Comparative Analysis on a Limited Image Dataset for Accurately Detecting Improperly Polished Surfaces for Industrial Applications
Full text linkThe objective of this study is to identify the optimal object detection architecture for training on a specific type of defect detection, namely incorrectly polished surfaces on aluminium elements. In order to facilitate a meaningful comparison of the various architectures, a maximum training time of approximately one hour was established for each architecture. Using the Darknet framework and a specific dataset, five architectures were compared (for the time being). The parameters of the various architectures, including network size, number of batches, and so forth, were modified according to a well-defined and systematic procedure. The preliminary findings indicate that the YOLOv4-tiny network exhibits superior training performance on this dataset, rendering it an optimal choice for industrial applications. This research provides support to small and medium-sized enterprises (SMEs) by identifying effective object detection architectures for quality control and highlighting avenues for advancing AI-driven defect detection in manufacturing
Dynamic Safety Evaluation and Risk Mitigation Strategies for Collaborative Kitting
Full text linkThe Collaborative Kitting (CoKitting) approach in manufacturing combines human dexterity and robot repeatability to simplify assembly tasks, improving efficiency and safety. The proposed methodology aligns with the Industry 5.0 (I5.0) perspective, aiming at optimizing the collaborative task by proposing guidelines for both quantitative safety definition and reactive control algorithms. The first aspect is pursued by a review of the applicable norms and the development of advanced vision algorithms and AI-based strategies for the continuous human pose monitoring and behavioural models prediction with the objective of realising a real-time risk assessment. The second aspect anticipates interactions and minimises risks by introducing novel collision avoidance algorithms which re-plan in real time trajectories that avoid contact between the robot and any obstacles present in the work area, whether fixed or mobile, by considering the evaluated safety index
Grasp Control for Enhancing Dexterity of Parallel Grippers
No full textA robust grasp controller for both slipping avoidance and controlled sliding is proposed based on force/tactile feedback only. The model-based algorithm exploits a modified LuGre friction model to consider rotational frictional sliding motions. The modification relies on the Limit Surface concept where a novel computationally efficient method is introduced to compute in real-time the minimum grasping force to balance tangential and torsional loads. The two control modalities are considered by the robot motion planning algorithm that automatically generates robot motions and gripper commands to solve complex manipulation tasks in a material handling application
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Three-flavor solar neutrino oscillations with terrestrial neutrino constraints
No full textWe present an updated analysis of the current solar neutrino data in terms of three-flavor oscillations, including the additional constraints coming from terrestrial neutrino oscillation searches at the CHOOZ (reactor), Super-Kamiokande (atmospheric), and KEK-to-Kamioka (accelerator) experiments. The best fit is reached for the subcase of two-family mixing, and the additional admixture with the third neutrino is severely limited. We discuss the relevant features of the globally allowed regions in the oscillation parameter space, as well as their impact on the amplitude of possible CP-violation effects at future accelerator experiments and on the reconstruction accuracy of the mass-mixing oscillation parameters at the KamLAND reactor experiment
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