Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based

Tool wear monitoring (TWM) is essential for enhancing the machining accuracy of intelligent manufacturing systems and ensuring the consistency and reliability of products. The complex and dynamic processing environment demands higher real-time monitoring and generalization ability of TWM. Traditional data-driven models lack guided training in physical processes and are limited by the amount of samples

Mixed reality remote collaboration assembly is a type of computer-supported collaborative assembly work that uses mixed reality technology to enable spatial information and collaboration status sharing among geographically distributed collaborators, including remote experts and local users. However, due to the abundance of mixed virtual and real-world information in the MR space and the limitations

Aero-engine nacelle acoustic liners are complex curved surface subassemblies with tens of thousands of dense acoustic holes for noise reduction. Traditional robotic drilling systems with a single spindle and conventional teaching programming cannot meet the high-quality and high-efficiency drilling requirements for nacelle acoustic liners. This paper developed a novel robotic multi-spindle drilling

Directed Energy Deposition (DED) is a free-form metal additive manufacturing process characterized as toolless, flexible, and energy-efficient compared to traditional processes. However, it is a complex system with a highly dynamic nature that presents challenges for modeling and optimization due to its multiphysics and multiscale characteristics. Additionally, multiple factors such as different machine

In the coming decades, robotized mobile machining equipment (RMME) is possible to evolve as a new branch of machine tools due to its exceptional flexibility. The frequency response function (FRF) serves as a theoretical foundation in controlling the vibration deformations that significantly limit the material removal efficiency of RMME. Model updating, aimed at minimizing errors between the theoretical

Variable impedance control (VIC) endows robots with the ability to adjust their compliance, enhancing safety and adaptability in contact-rich tasks. However, determining suitable variable impedance parameters for specific tasks remains challenging. To address this challenge, this paper proposes an imitation learning-based VIC policy that employs observations integrated with RGBD and force/torque (F/T)

The robotic manipulation of deformable linear objects (DLOs), such as cables, is a valuable yet complex skill. In particular, to realize tasks like cable routing and wire harness assembly, it is required that two robotic arms, grasping the ends of a DLO, move it from an initial shape to a final one where cable assembly can be performed. The manipulation must be performed following a collision-free

In robotic and automation industry, micromanipulation and micromanipulator have recognized significant advancements due to they are involved in handling of micro-sized parts from a few to hundreds of micrometers. In order to perform such precise grasping tasks, compliant grippers have been increasingly developed, and they have critically significant contributions in the high precision micromanipulation

The revolutionary advances in integrated components in current automotive industry have led to a sharply rising demand for aluminum alloy castings. Targeted quality inspection is thus proposed for components manufacturers to achieve high responsiveness and low operational cost. This suggests casting machine manufacturers to integrate advanced quality prediction functions into the next generation of

Digital twin tools for additive manufacturing (AM) are constrained by the underlying representations of component geometry that are currently in wide use. Mesh, voxel, and parametric surface representations require numerous conversions to intermediate representations at multiple points throughout the processing chain. Each conversion introduces additional error in the geometric representation and complicates

Trajectory accuracy, a crucial metric in assessing the dynamic performance of grinding robots, is influenced by the uncertain movement of the tool center point, directly impacting the surface quality of processed workpieces. This article introduces an innovative method for compensating trajectory errors. Initially, a strategy for error compensation is derived using differential kinematics theory. Subsequently

The joint deflection of robots in machining degrades product accuracy. Compliance error compensation has been investigated to reduce the static deflection of robotic machining. The challenge in compliance error compensation is accurately measuring the deflection or cutting force. External sensors have been used to measure them in robotic machining, but it is not practical. The authors proposed a nonlinear

Monitoring tool breakage during computer numerical control machining is essential to ensure machining quality and equipment safety. In consideration of the low cost in long-term use and the non-invasiveness to workspace, using servo signals of machine tools to monitor tool breakage has been viewed as the solution that has great potential to be applied in real industry. However, because machine tool

The present study aims at exploring the effect of communicating robots’ intent through visual cues, to the human on a complex human-robot collaborative task. Specifically, it aims to investigate (i) whether the use of such “anticipatory cues” will have a positive effect on task efficiency, human safety and collaborating fluency, (ii) the degree of this effect with varying robots’ speed and (iii) whether

Adaptive allocation of the machining allowance is the crucial factor in ensuring the machining accuracy of complex parts. In this work, we present a multi-objective constraint registration method. First, an improved point cloud segmentation method is developed by combining point search and region data expansion algorithms. Afterward, the machining allowance is accurately calculated by using statistical

Trajectory planning is crucial in the motion planning of robots, where finding the time-optimal path parameterization (TOPP) of a given path subject to kinodynamic constraints is an important component of trajectory planning. The tangential discontinuity at the intersection of continuous line segments limits the speed of trajectory planning and can easily cause jitter and over-constraint phenomena

Nowadays, Industry 5.0 starts to gain attention, which advocates that intelligent manufacturing should adequately consider the roles and needs of humans. In this context, how to enhance human capabilities or even liberate humans from the processes of perception, learning, decision-making, and execution has been one of the key issues to be addressed in intelligent manufacturing. Large language models

Carbon fiber reinforced polymers (CFRP) have significant applications in aerospace and automotive manufacturing. However, due to the complexity of CFRP structures, manufacturing defects are challenging to avoid and even affect the mechanical properties. Timely detection and repair are essential to ensure product quality. In this study, we propose a robotized framework for real-time detection and in-situ

In the field of robotic polishing, achieving uniform material removal typically involves addressing the issue of constant contact force control. However, multi-source external disturbances in the polishing scenarios of complex workpiece surfaces can severely affect the robot’s force control accuracy. To enhance the responsiveness and disturbance rejection capabilities of robots in the compliant polishing

Path smoothing and trajectory planning are universally applied in computer-numerical-control (CNC) machining to avoid natural discontinuity of tangency and curvature at the junctions of G01 blocks. However, most existing methods primarily focus on path-centric indicators that consider the toolpath as a continuous curve, such as contour error and manufacturing efficiency, neglecting the global machining

Robotic machining could provide a solution for removing supports from metal additive manufactured workpieces, replacing labor-intensive work. However, the robot’s intrinsic weaknesses of low positioning accuracy and structural rigidity primarily restrict its applications. Improving the accuracy of robotic machining remains an unresolved issue. A mixed solution is proposed, in which a portable CNC machine

Visual recognition of weld beads is essential for post-weld robotic grinding. The recognition of thin-walled weld bead boundary, especially the backside boundary, remains challenging due to the diverse features such as debris, misalignment, and deformation. Based on point cloud from a laser scanner, we present a robust and accurate backside boundary recognition method for girth weld beads of thin-walled

The process design intent is the concentration of the technologists’ design cognitive process which contains the experiential knowledge and skills. It can reproduce technologists’ design thinking process in process design and provides guidance and interpretability for the generation of process results. The machining process route, as a core component of a part's entire manufacturing process, contains

Human–robot collaborative polishing can integrate the capabilities of humans and automation to deal with complex polishing tasks. Traditional impedance-control-based human–robot collaboration (HRC) requires operators to physically interact with robots for a good polishing performance, which brings unsafety to operators. To address this issue, a corrective shared control architecture using haptic feedback

Generating model-free grasps in complex scattered scenes remains a challenging task. Most current methods adopt PointNet++ as the backbone to extract structural features, while the relative associations of geometry are underexplored, leading to non-optimal grasp prediction results. In this work, a parallelized graph-based pipeline is developed to solve the 7-DoF grasp pose generation problem with point

Automating fabric manipulation in garment manufacturing remains a challenging task due to the characteristics of limp sheet materials and the diversity of fabrics used. This paper introduces an adaptive and optimized robotic fabric handling system, designed to address these challenges. The system comprises an industrial robot, four needle grippers, and a novel adaptive gripper jig system capable of

Owing to the advantages of good flexibility and low cost, robots are gradually replacing manual labor as an effective carrier for the grinding and polishing of aeroengine blades. However, the geometric features of blades are complex and diverse, and the contour accuracy and surface quality requirements are high, making the robotic grinding and polishing of blades still a challenging task. For this

This article focuses on improving the compliance, efficiency, and robustness of batch precision assembly of small-scale pegs flexibly absorbed by a suction cup. The main contribution is that a force–vision fusion fuzzy control method (FVFFC) is proposed to achieve precision assembly with unknown clearance or interference fit. Both visual and force features are designed to describe the state of the

In recent years, with the deepening integration of digital twins (DT) and the Industrial Internet of Things (IIoT), solutions based on digital twins have been widely applied in IIoT scenarios. However, most existing solutions tend to overlook the latency issue during the interaction between mobile devices, such as industrial mobile robots (IMR), and their DTs while in motion. Excessive interaction

This study presents the Reconfigurable and Responsive Robot Manufacturing (R3M) architecture, a novel framework engineered to autonomously adapt to fluctuating product variants and demands within manufacturing environments. At the heart of R3M lies an integrated architecture that ensures a seamless data flow between critical modules, facilitated by an advanced communication platform. These modules

Point clouds are widely used to construct models of workpieces using 3D scanners, especially where high-quality robotic and automatic 3D scanning is required in industries and manufacturing. In recent years, Point Cloud Quality Assessment (PCQA) has garnered increasing attention as it provides quality scores for entire point clouds, addressing issues such as downsampling and compression distortions

Virtual Reality (VR) and Augmented Reality (AR) technologies have been separately applied to enhance a wide range of design and manufacturing operations across various industries. Most VR applications are primarily focused on product prototyping and personnel training, whereas AR is commonly used to facilitate manual operations in manufacturing such as assembly and maintenance tasks. This study proposes

In automated fiber placement (AFP), addressing the continuous motion planning challenge of redundant layup manipulators in complex environments, this paper proposes an offline redundancy optimization algorithm based on improved RRT* (Rapidly-exploring Random Trees). This algorithm maximizes the utilization of kinematic redundancy to derive smooth joint trajectories devoid of collisions and singularities

In emerging manufacturing facilities, robots must enhance their flexibility. They are expected to perform complex jobs, showing different behaviors on the need, all within unstructured environments, and without requiring reprogramming or setup adjustments. To address this challenge, we introduce the A3CQP, a non-strict hierarchical Quadratic Programming (QP) controller. It seamlessly combines both

Digital Twin (DT) technology, which integrates multi-source information, is extensively applied for comprehensive monitoring, predicting, and optimizing manufacturing processes. The core of this technology is the Digital Twin Virtual Model (DTVM), which acts as a virtual mirror reflecting the real-world physical processes within a digital environment. In processes like tube bending, constructing a

A robotic grinding system requires a force-controlled grinding module to provide a consistent surface roughness and a robot arm to position the grinding module to reach a wide range of surface area on a workpiece. Existing pneumatic grinding modules are heavy and bulky and cannot provide very accurate force control. Articulated 6-axis robot arms are often used for positioning the grinding module, but

Digital Twin (DT) is a promising technology that offers versatile services to enhance manufacturing intelligence. However, the agility, reliability and analysis capabilities of existing DT services are severely challenged when applied and deployed at large-scale production lines. To address the aforementioned issues, a microservice-based DT system with redundant architecture is proposed. First, a scalable

Freeform surface parts play a significant role in the aerospace industry, the mold- manufacturing industry and the automobile industry, and it is energy-saving, material-saving, time-saving and environmentally beneficial to remanufacture the damaged components to restore their functionality and performance. Due to the complex geometry of the freeform surface wear, the adaptive remanufacturing of freeform

Human-centric assembly is emerging as a promising paradigm for achieving mass personalization in the context of Industry 5.0, as it fully capitalizes on the advantages of human flexibility with robot assistance. However, in small-batch and highly customized assembly tasks, frequently changes in production procedures pose significant cognition challenges. To address this, leveraging computer vision

For dynamic collision-free trajectory planning in dual-robot and human collaborative tasks, this paper develops an online dual-robot Mutual Collision Avoidance (MCA) scheme based on convex optimization. A novel convex optimization formulation model, named Disciplined Convex programming by Shifting reference paths (DCS), is proposed for solving the single-robot trajectory optimization problem. Furthermore

In light of the global economic downturn and the intricate division of labor in manufacturing, the imperative for advanced manufacturing services and Manufacturing Service Collaboration (MSC) has escalated significantly. As manufacturing services gravitate towards aggregation on manufacturing service platforms, platform-aggregated MSC has emerged as an inevitable and compelling trend, capturing the

The concept of Operator 4.0 has been recently defined to evolve the modern industrial scenarios by defining a knowledge sharing process from/to operators and industrial systems, creating personalized skills, and introducing digital tools towards socially sustainable factories. In this context, dynamic and adaptive user interfaces can make humans part of the intelligent factory system, supporting human

This paper addresses an integrated rack assignment and robot routing problem arising in robotic movable fulfillment systems (RMFS). This NP-hard planning task goes beyond current literature by simultaneously optimizing movable rack selection and multi-agent collision-free path finding, rather than decomposing them. A mixed integer programming (MIP) model with a new level-space-time network representation

On the landscape of solutions to deal with delicate objects, the development and use of soft grippers is a topic of increasing interest, with a large number of prototypes proposed by the research community employing non-linear soft materials and based on diverse actuation means. However, increasing compliance usually leads to the reduction of lifting capacity. As a recent promising approach, shear

In sheet metal forming, the quality of a formed part is strongly influenced by the local lubrication conditions on the blank. Fluctuations in lubrication distribution can cause failures such as excessive thinning and cracks. Predicting these failures in real-time for the entire part is still a very challenging task. Machine learning (ML) based digital twins and advanced computing power offer new ways

Facing the new generation intelligent manufacturing, traditional manufacturing models are transitioning towards large-scale customized productions, improving the efficiency and flexibility of complex manufacturing processes. This is crucial for enhancing the stability and core competitiveness of the manufacturing industry, and human-robot collaboration systems are an important means to achieve this

Advanced metalworking industries need high-performance materials to pursue the sustainable goal of reducing the consumption of hydrocarbons. The ability to work at elevated temperatures and resist environmental corrosion, among many other mechanical and physical properties, is also imperative for the operating conditions. Despite meeting this sector's physical and mechanical demands, some of these

In the process of metal cutting, realizing effective monitoring of tool wear is of great significance to ensure the quality of parts machining. To address the tool wear monitoring (TWM) problem, a tool wear monitoring method based on data-driven and physical output is proposed. The method divides two Physical models (PM) into multiple stages according to the tool wear in real machining scenarios, making

Accurate tool wear prediction during machining is crucial to manufacturing since it will significantly influence tool life, machining efficiency, and workpiece quality. Although existing data-driven methods can achieve competitive performance in tool wear prediction, their main emphasis is on fixed operating conditions with sufficient training samples, which is impractical in engineering practice.

Map construction is the initial step of mobile robots for their localization, navigation, and path planning in unknown environments. Considering the human-robot collaboration (HRC) scenarios in modern manufacturing, where the human workers’ capabilities are closely integrated with the efficiency and precision of robots in the same workspace, a map integrating geometric and semantic information is considered

In practice, the process of robot assembly in an unstructured environment faces difficulties due to the presence of unpredictable environmental errors related to vision and pose. Therefore, to minimize the uncertain environmental errors during the robotic assembly process in an unstructured environment, several studies have considered a reinforcement learning (RL)-based approach. However, if assembly

Additive Manufacturing (AM) has revolutionized the production landscape by enabling on-demand customized manufacturing. However, the efficient management of dynamic AM orders poses significant challenges for production planning and scheduling. This paper addresses the dynamic scheduling problem considering batch processing, random order arrival and machine eligibility constraints, aiming to minimize

Manufacturing is transformed towards smart manufacturing, entering a new data-driven era fueled by digital technologies. The resulting Smart Manufacturing Systems (SMS) gather extensive amounts of diverse data, thanks to the growing number of sensors and rapid advances in sensing technologies. Among the various data types available in SMS settings, time-series data plays a pivotal role. Hence, Time-Series

Vision-based weld seam tracking has become one of the key technologies to realize intelligent robotic welding, and weld deviation detection is an essential step. However, accurate and robust detection of weld deviations during the microwelding of ultrathin metal foils remains a significant challenge. This challenge can be attributed to the fusion zone at the mesoscopic scale and the complex time-varying

This paper addresses the crucial aspect of position error modeling and compensation in industrial servomechanisms with the aim to achieve accurate control and high-performance operation in industrial robots and automated production systems. The inherent complexity and nonlinear behavior of these modules, usually consisting of a servomotor and a speed reducer, often challenge traditional analytical

In the context of Industry 4.0, ensuring the compatibility of digital twins (DTs) with existing software systems in the manufacturing sector presents a significant challenge. The Asset Administration Shell (AAS), conceptualized as the standardized DT for an asset, offers a powerful framework that connects the DT with the established software infrastructure through interoperable knowledge representation

The future manufacturing system must be capable of supporting customized mass production while reducing cost and must be flexible enough to accommodate market demands. Additionally, workers must possess the knowledge and skills to adapt to the evolving manufacturing environment. Previous studies have been conducted to provide customized manufacturing information to the worker. However, most have not

With the development of intelligent manufacturing, robots are being increasingly applied in manufacturing systems due to their high flexibility. To avoid production disruptions caused by robot failures, higher requirements are imposed on the resilience of systems, specifically in terms of resistance, response, and recovery capabilities. In response to this, this paper investigates the resilient scheduling

Hand-eye calibration is a prerequisite for robot vision system applications. However, due to the lack of image features, implementing hand-eye calibration with a line-structured light sensor is limited by complex procedures and special reference objects. The aim of this paper is to develop a stable and undemanding eye-in-hand calibration method with a 2D laser sensor that can be adapted to random measurement