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During the last two decades, parallel robots have become more ubiquitous, employed in a great variety of sectors, from food to aerospace industries. In fact, they are much more efficient than their serial counterparts in terms of performing fast motions and consuming less energy. However, due to their mechanical complexity, they present a highly complex non-linear dynamics, which makes the modelling and control tasks difficult. Aiming to improve the performance and robustness of the control laws already used to control this type of mechanisms, previously, the authors proposed two novel laws of hybrid control, implemented in the joint space, in order to improve the dynamic behavior of parallel robots when performing fast motion tasks. Among the goals of the current work, one can mention to adapt the two laws of hybrid control, proposed in the previous work, by implementing them in the task space. Additionally, the peculiarities related to the dynamic formulation and the tuning of controller gains are also shown. Furthermore, a comparison of the performances of the pure and hybrid control techniques, implemented in both joint and task spaces, is presented as well, by executing the same paths and using adequate metrics. In the selected paths, experiments revealed that the hybridization process of pure control laws in the task space provides a significant reduction of the path-tracking and steady-state errors. [ABSTRACT FROM AUTHOR]

The manufacturing sector is a fundamental pillar of worldwide economies, contributing markedly to global economic growth. However, the manufacturing industry is persistently confronted with issues impeding its development and expansion, such as manpower shortages, safety concerns, high initial investment for installation, and long return on investment. Within this context, machine tending has become a crucial component of the manufacturing process and potentially serves as a viable solution to the afore-mentioned predicaments. Over the past 5 years, implementing automated machine-tending systems has widely extended from simulation or laboratory environments to practical applications in manufacturing workshops as robotics and artificial intelligence develop rapidly. To fully benefit from the potential of machine-tending applications, it is necessary to comprehend and tackle its associated challenges. Therefore, this paper aims to contribute to the evolution of machine-tending applications by investigating the impacts of emerging trends of advanced technologies, such as autonomous mobile robots, computer vision, machine learning, and deep learning. This systematic literature review is based on the Protocol of Preferred Reporting Items for Systematic Review and Meta-Analyses to analyze the 50 scientific literature related to machine tending in the last five years. [ABSTRACT FROM AUTHOR]

This paper focuses on optimising pick-and-place tasks performed by a dual-arm collaborative robot in a specific shoe manufacturing industry environment. The robot must identify the pieces of a shoe placed on a tray, pick them up, and place them in a shoe mold for further processing. The shoe pieces arrive on the tray in random positions and angles and can be picked up in a different order. Optimising these tasks could increase the assembly speed of each unit and improve shoe production. To achieve this goal, a mathematical model based on binary integer linear programming (BILP) has been developed. This model determines the optimal sequence for picking and placing the shoe pieces in the mold, thus minimising the time required for picking and decision-making. The effectiveness of this approach has been tested using two 3-piece unit shoe models: one for training and another for validation. These models encompass a total of 500 trays. An analysis of the results reveals that BILP offers advantages for task motion planning in complex environments with multiple trajectories and the potential for collisions between arms. The model's generalizability to shoes with n assembly pieces further confirms its robustness for various piece counts. [ABSTRACT FROM AUTHOR]

Nowadays, there are many different industrial processes in which people spend several hours performing tedious and repetitive tasks. Furthermore, most of these processes involve the manipulation of dangerous materials or machinery, such as the toy manufacturing, where people handle ovens with high temperatures and make weary physical effort for a long period of time during the process. In this work, it is presented an automatic and innovative collaborative robotic system that is able to deal with the demoulding task during the manufacturing process of toy dolls. The intelligent robotic system is composed by an UR10e robot with a RealSense RGB-D camera integrated which detects the pieces in the mould using a developed vision-based algorithm and extracts them by means of a custom gripper located and the end of the robot. We introduce a pipeline to perform the demoulding task of different plastic pieces relying in the use of this intelligent robotic system. Finally, to validate this approach, the automatic method has been successfully implemented in a real toy factory providing a novel approach in this traditional manufacturing process. The paper describes the robotic system performance using different forces and velocities, obtaining a success rate of more than 90% in the experimental results. [ABSTRACT FROM AUTHOR]

This systematic literature review presents the latest advancements and insights about digital twin technology and robotics interfaced with extended reality in the context of Industry 4.0. As the extended reality technologies emerge, it results in an increasing overlap between digital twins and human-robot interactions in industrial settings, promoting collaboration between operators and cobots in manufacturing environments. The objective of this study is to serve as a valuable resource for researchers and practitioners working in the field of Industry 4.0. It aims to highlight the latest developments and innovations in the application of digital twins and robotics interfaced with extended reality technologies in manufacturing. By extracting data from relevant articles, it provides a comprehensive understanding of the current state-of-the-art in this field by: analyzing the favored extended reality interfaces for digital twin and robotics interactions; analyzing the digital twin and physical twin interaction; evaluating the digital twin application levels and pillars through extended reality interfacing; and introducing a new concept called augmented perception for creating new physical-digital interactions. [ABSTRACT FROM AUTHOR]

Industries of low-batches or one-off manufacturing aim for automation that is competitive enough to adapt to new or modified products daily through in-house knowledge that focuses on manufacturing processes and not on machine function programming. To solve this, a complete set of actions that utilize seamless data transfer from product design in CAD to a Plug & Produce automation concept is proposed together with a generic structure for the integration of standard industrial robots into agents. This structure enables agents to handle their local reference coordinate systems and locations relative to a global perspective. Seamless utilization of data from product designs to Plug & Produce will simplify and shorten the time of digital development through concurrently usable text-based and graphical configuration tools of a configurable multi-agent system. Needed data extracts directly from the product design as requirements of operational goals. Extraction of data from the product design, sequence of goals, and process plans, which are recipes of how to solve goals, can by this concept be configured by in-house knowledge that has the process knowledge but not necessarily programming competence. [ABSTRACT FROM AUTHOR]

Traditional end effectors for collaborative robots are generally either highly specialized to a specific shape of part or are unable to deal with high temperatures, indicating the existence of a niche for an end effector designed for both, leveraged in the automation of post-processing metal additive manufacturing parts. The design described and qualified in this manuscript is composed of a custom-fabricated 4140 alloy steel finger and an aluminum oxide–casted ceramic insulator. Characterization tests were performed to quantify the thermal and mechanical properties of the casted material, and thermal simulations were performed to optimize design. The simulated temperature difference across the body of the insulator is 767.58°C when placed in contact with a 1000°C steel plate, modeled from a conducted thermal shock test. With an expected maximum operating temperature of 800 to 1000°C, the insulator will withstand the conditions for grabbing. Additionally, a pair of thermocouples are incorporated in the gripper to monitor the temperature of the workpiece to ensure safe handling. The designed high-temperature gripper will be a useful tool in enabling capabilities of metal additive manufacturing as well as the safe handling of high-temperature objects. [ABSTRACT FROM AUTHOR]

Collaborative tasks in multiple systems have attracted considerable attention in contemporary manufacturing environments. Collaborative robots are representative agents for various collaborative industrial tasks. This study focuses on contactless delivery by considering multiple agents. A contactless delivery operation must be performed with well-synchronized cooperation among the sender, a receiver, and flying dynamics of the deliverable. The most challenging task is to predict the catching point of a thrown package by considering both collaborative robots. Accurate catching-point prediction and relevant operations were achieved using the proposed physics-informed neural network-based hybrid multi-stream deep learning framework. Various cooperative environments were considered using multi-modal input data and manufacturing conditions. The proposed framework incorporates these constraints, and the prediction is guided by flying dynamics and trajectory data. The effectiveness of the proposed framework was demonstrated by implementing multi-agent and related manufacturing environments in a digital twin system. The effectiveness of the proposed framework was proven experimentally using analyses and comparisons with existing machine learning methods. [ABSTRACT FROM AUTHOR]

The development of autonomous finishing operations in manufacturing process has the potential to decrease the costs and increase the quality of the operations. In this context, robotic manipulators have been introduced in sanding and polishing applications. Inspired by the recent development in machine learning and robotics, this paper is focused on designing a system capable of estimating the surface roughness using only a force torque sensor integrated with a robotic manipulator that performs the sanding of fiberglass panels. We present an investigation into the usage of convolution neural networks on the force-torque data to produce a quantitative estimation of surface roughness. To validate the results obtained a profilometer is used to gather pre- and post-operation data. The establishment of a relationship between measured force data and post-operation surface roughness will be used to develop a prediction of the surface quality for sanding operation using robotic manipulators. This project intents to act as proof-of-concept that traditional robotic sensors, can be used beyond their original scope, minimize the complexity of robotic systems integrated into manufacturing processes. [ABSTRACT FROM AUTHOR]

System engineering (SE) methods and principles are nowadays widely adopted in the product development processes, especially in the industrial sector, where saving production time and costs are primary goals. This work describes an application of a particular SE methodology, the V-model-based design, in which the system development lifecycle is divided on the basis of a graphical V-shaped scheme, called V-model. Following this approach, a new concept of charging arm for Robotic Train Inspection Monorail (TIM) of Large Hadron Collider (LHC) at CERN (Conseil Européen pour la Recherche Nucléaire) has been developed. The current charging arm version is affected by several issues and limits that have led to the necessity of a new solution. Starting from the first stages of functional requirements (FRs) definition and decomposition (left side of the "V"), a new concept has been implemented, in order to be tested for its verification and validation (right side of the "V"). As part of the principles of SE, the process has been based on virtual models of the product and on virtual simulations of its operation, rather than on the realization of time-consuming and expensive physical models and tests, even if a final physical prototype has also been built and some physical operative tests have also been carried out on it. These tests have showed that the new product appears to fulfill each one of its FRs and overcome the limits imposed by the previous version. The future commissioning and operative tests in the real operating condition and location shall definitely validate the new product. [ABSTRACT FROM AUTHOR]

During the curved surface lapping processing by robot, the surface quality of the processed workpieces cannot be fully guaranteed because of the uncontrollability of lapping contact force. Therefore, the accurate control of the contact force between the tool and the workpiece is important to improve the processing quality. This paper proposes an impedance control strategy based on an optimized environmental model to address the serious constraints brought by the uncertainty of the environmental model in impedance control on the compensation accuracy of contact force and constructed a contact environmental model of elastic abrasives based on neural network algorithm, which improved the compensation accuracy of contact force through iterative iteration and prediction between the environmental model and the impedance model. Constant force control is achieved through accuracy compensation, which ultimately leads to an improvement in the surface quality of the workpiece. Through comparison experiments, it is found that compared with the unoptimized method, the force control tracking error is reduced by 60.9%, the contact force variance is reduced by 25.7%, the contact force error during curved surface force control lapping process is reduced by 58.3% and the contact force variance is reduced by 52.5%, and the workpiece roughness Ra value is reduced by 37.2%. Therefore, the robotic constant force control system based on optimized environmental model can achieve a better force control effect, which can realize accurate and stable control of contact force during curved surface lapping process by robot, and has certain potential for engineering application. [ABSTRACT FROM AUTHOR]

Superalloys are widely used in aerospace and energy fields by virtue of superior physical properties, especially in high-temperature environments. However, superalloys have poor machinability and are typical difficult-to-machine materials. Robotic belt grinding is an effective and popular method for finish machining superalloys, offering significant advantages such as high material removal capacity, low heat input, and fewer workpiece damages. Moreover, robots can be well integrated with multi sensors, such as infrared radiation cameras, force sensors, microphones, and high-speed cameras. These sensors help to realize real-time monitoring of grinding processes, thus benefiting the grinding quality control. Despite many developments in recent decades, there is a lack of comprehensive review of robotic belt grinding of superalloys, particularly advanced techniques and methods to achieve precision profile finishing and desired properties. Therefore, after introducing a typical intelligent robotic grinding system, this paper reviews five important aspects that need further research for robotic belt grinding of superalloys: typical tools and grinding parameters selection, surface integrity analysis and control, tool condition motoring, material removal, and finishing control, as well as the force distribution and thermal analysis. The typical applications, potentials, and limitations are also introduced. As an emerging technology, artificial intelligence (AI) is imperative to realize intelligent robotic belt grinding. Hence, this paper pays more attention on AI-based models of grinding processes. [ABSTRACT FROM AUTHOR]

Process monitoring is essential to enable process parameter optimization, deformation prediction, and fault diagnosis in robotic milling. However, expensive costs and installation requirements limit the use of industrial sensors in machining process. This paper proposed a sensorless method to predict force-induced deformation and surface waviness. First, the tracking errors of tooltip was calculated based on the robot joint tracking errors and the robot kinematic model. Subsequently, the idle running and cutting process signals monitored by the robot controller were used to calculate the cutting force acting on tooltip based on Kalman filter and robot static model. On this base, the force-induced deformation, considering the posture error of the robot flange coordinate system, was calculated using the estimated milling force and the flexible model. Finally, the effectiveness of the proposed method was verified by a series of cutting experiments. [ABSTRACT FROM AUTHOR]

Robotic systems are key in industry 4.0 context. While there are many robot models available in the market, the number of grippers with sensing capabilities at an affordable cost is reduced. Traditional robot grippers are targeted to perform specific tasks, with unchangeable configurations and limited ability to adapt to different working scenarios. In this paper, we present the design and fabrication of a modular and low-cost 3D-printable robotic gripper to grasp and hold different objects. It is a parallel gripper with a two-finger two-motor configuration. The power transmission was conceived to maximize the grasping force while keeping the gripper compactness. The gripper structure is 3D-printed and includes three different types of fingers: (1) hard fingers, (2) flexible fingers, and (3) soft fingers. Objects to grasp are recognized using an embedded camera with integrated computer vision processing. The gripper components are integrated into a common network for monitoring and control. Experimental tests were conducted with objects from the YCB dataset featuring different sizes, weights and shapes. Results indicate that it can grasp different objects, reaching a maximum force of 76 N per finger and a positioning accuracy in the millimetres range. [ABSTRACT FROM AUTHOR]

Sealing process is an essential procedure that demands standardization and monitoring during the application to ensure quality. It prevents leakages, corrosion and electrical discharges on components of different products. Most of industrial manufacturers perform the manual application method, which require a proper skill to seal parts. The sealing process could be much more effective if carried out by an automated system, capable of managing the extrusion of the sealant during its application, providing a standardized procedure and favoring the human factors caused by poor working conditions. This article proposes an automated end-effector that continuously measures the contact force of the sealant during its application and also monitors the width and texture of the fillet through a computer vision technique. In order to testify the performance of the proposed system, a case study has been performed with the developed force sensing end-effector coupled to industrial robot manipulator. The results show the possibility of employing online monitoring of sealing application in order to ensure quality during the process. [ABSTRACT FROM AUTHOR]

Robots bring eventful impacts to the workplace, benefiting from the advantages of implementing any technology should be based on the premise of safety. This work proposes a systematic method to establish a postprocessor module for any specified 6R articulated robot. Instead of obsessively emphasizing achieving the desired locations and orientations by hand guiding grab and dragging a robotic arm for operation in teaching mode, the significant end-effector poses are calculated to form a new path for the joints efficiently in this study. Since robotic motion control is usually a complex system whose users must be well trained and acquainted with using them. There is a need for a GUI solution that can provide intuitive robotic motion control on the current location by the user independently, easy setup, arrangement, adjustment, and monitoring robot motion tasks. The proposed system simplifies the interaction between the technician and the industrial robotic arm in the case of robotic motion control and tracking at a distant location. The presented method is fully adapted to alternate between joint angles and end-effector poses on a graphic user interface system. After developing the capabilities of the solver, a functional postprocessor is programmed inside the proposed GUI system. Examples with specified posture and predefined movements are demonstrated for corroborating the algorithm. The results show considerable efficiency and reliability in task planning and are fully supported for automatic path generation. [ABSTRACT FROM AUTHOR]

With the development of intelligent factories, collaborative robotic arms are becoming the critical equipment for flexible production lines, and digital twin is the best way to realize intelligent and digitized collaborative robotic arm. This paper designs and develops a collaborative robotic arm monitoring system based on digital twin and proposes a six-dimensional system architecture. Key technologies such as equipment twin modeling for the assembly process, multi-source heterogeneous data acquisition, and digital twin–driven real-time monitoring are studied. The system is driven by twin models and real-time data, and based on the key physical characteristics of the collaborative robotic arm. The model and data are effectively integrated to realize real-time monitoring of the assembly process and provide support for intelligent decision-making. The effectiveness and feasibility of the system are verified by running the application on the UR5 and UR10 collaborative robotic arm assembly test benches. [ABSTRACT FROM AUTHOR]

With the rapid development of modern industry, the surface of workpieces is becoming increasingly complex, and workpieces present the trend of small personalized batches. Robot polishing has become one of the required precision machining methods because of their excellent flexibility, ample working space, and strong maneuverability. Therefore, this paper reviews a series of precision machining methods based on robotic technology. First of all, the seven aspects of the operating principle of industrial robot polishing system like robot polishing force control technology, robot polishing trajectory planning, robot polishing path planning, robot teaching programming technology, robot polishing vibration control, multi-robot polishing control technology, and commercial robotic polishing systems, have been carried on in detailed by discussion and analysis. Secondly, researches on the basic architecture of the polishing robot are concluded by two aspects as researches on structure classification of the polishing robot and design of robot polishing end-effector. Finally, the study of robot polishing and future work are summarized. [ABSTRACT FROM AUTHOR]

The grinding of blades for aeroengines under constant normal contact force is challenging. The surface roughness (Ra) and profile dimensional accuracy of the blades have notable influence on the overall performance and service life of aeroengines. This study aimed to minimize the influence of the changes in the normal contact force on Ra and the uniformity of material removal depth (MRD) in the cut-in/cut-off stage of robotic abrasive belt grinding and in the parts that undergo large changes in curvature. First, we established models for predicting Ra and MRD using orthogonal central composite design theory and a broad learning system algorithm. Second, by combining the established predictive model and applying the sensor-measured grinding force, we established a multiple learning backtracking search algorithm to derive the adaptive process parameters for the optimization objective function. Finally, the grinding quality was experimentally evaluated using the obtained process parameters, and the maximum errors between the test values and model-predicted values of Ra and MRD were 14.2% and 13.4%, respectively. The test results indicated that the method proposed in this article may be effective for achieving consistent Ra and MRD, which can considerably improve the quality of blade grinding. [ABSTRACT FROM AUTHOR]

Automobile flexible sheet metal parts are prone to produce non-negligible grasping deformation, and choosing an appropriate layout of grasping points is an important means to reduce the grasping deformation for sheet metal parts. It is challenging to optimize the layout of grasping points efficiently and accurately because of the large number of robot fingers due to a large size sheet part. In order to improve the optimization efficiency and reduce the computational cost, this paper proposes a two-stage optimization design method for the layout of grasping points based on GSA-Kriging surrogate model. First, the number of robot fingers and their feasible range are determined according to the stability of robotic grasping operation and the degree of deformation at different positions. Then, according to the position distribution of grasping points, they are divided into two stages for optimization. Finally, GSA-Kriging surrogate model and gravitational search algorithm (GSA) are used to find the optimal layout of grasping points. In this paper, the layout of grasping point optimization of a certain car door sheet part is utilized as a case to validate the proposed method and we have designed an experimental system to test the proposed grasp method on a curved sheet part. The result shows that the GSA-Kriging surrogate model is more accurate and more stable than Kriging and other surrogate models. At the same time, the two-stage optimization method improves the optimization efficiency while reducing the calculation cost and burden. [ABSTRACT FROM AUTHOR]

Robotic grinding has been gradually applied in the field of blade grinding due to its high precision and high flexibility. One important task in robotic grinding is to determine the position of the workpiece coordinate system. In addition, the mounting errors that exist during robotic grinding operations can lead to machining deviations. To solve above problems, this paper presents a vision-based robot workpiece posture error calibration method to fulfill the precision grinding requirements of aero-engine blades. Firstly, the 3D laser scanner is used to obtain point cloud information of aero-engine blades, where the blades are fixed to the end flange of the robot. Due to environmental interference and the limitation of the scanning angle, the initial point cloud is large and redundant; thus, this study applies statistical filtering, voxel filtering, and cluster segmentation for pre-processing. Therefore, to solve the problem of low efficiency of traditional ICP for aligning residual point clouds, this paper proposes to use the trimmed ICP algorithm to improve the alignment speed and accuracy between the obtained point cloud and the discrete CAD model point cloud to calibrate the pose errors of aero-engine blades. The experiments verified that the calibration method proposed in this paper has high precision and good surface machining consistency. The overall surface roughness of the blade is reduced from over Ra8μm to about Ra0.4 μm, which meets the technological requirements. [ABSTRACT FROM AUTHOR]

A patina is essentially the weathered look a piece of leather takes on as it ages. The patina finishing aspect can be also generated or grown artificially by scrubbing the leather surface with specific products. These kinds of manual finishing operations on small objects are delicate and regularly need slight corrections carried out by skilled artisans, which adds complexity to the process automation and implies various key aspects to consider. This research presents a novel approach for automatic and semiautomatic shoe patina growing in the footwear industry using a new co-creative method based on cooperative robotics. The system automates the process in pursuit of operator time-saving without reducing the work finishing quality. For this purpose, the use of a collaborative robot with a built-in constant contact force control and a collaborative tool are used in this research. The use of both tools in complementarity with the knowledge of the craftsman leads the robot end-effector adaptation to the inherent curved surfaces over the shoe. Besides, some orientation corrections are applied based on the CAD model for the task to be accurately accomplished. The solution has been successfully integrated in a real production line, and it is currently in use. [ABSTRACT FROM AUTHOR]

This paper describes the dynamic mosaic planning method developed in the context of the PICKPLACE European project. The dynamic planner has allowed the development of a robotic system capable of packing a wide variety of objects without having to adjust to each reference. The mosaic planning system consists of three modules: First, the picked item monitoring module monitors the grabbed item to find out how the robot has picked it. At the same time, the destination container is monitored online to obtain the actual status of the packaging. To this end, we present a novel heuristic algorithm that, based on the point cloud of the scene, estimates the empty volume inside the container as empty maximal spaces (EMS). Finally, we present the development of the dynamic IK-PAL mosaic planner that allows us to dynamically estimate the optimal packing pose considering both the status of the picked part and the estimated EMSs. The developed method has been successfully integrated in a real robotic picking and packing system and validated with 7 tests of increasing complexity. In these tests, we demonstrate the flexibility of the presented system in handling a wide range of objects in a real dynamic packaging environment. To our knowledge, this is the first time that a complete online picking and packing system is deployed in a real robotic scenario allowing to create mosaics with arbitrary objects and to consider the dynamics of a real robotic packing system. [ABSTRACT FROM AUTHOR]

Disassembly is the first step in the remanufacturing of a product. This paper presents the design of a robot end-of-arm tool for removing a peg from a hole, a common operation in the disassembly of mechanical products. The device is a compliant structure that enables the peg to be pulled out of a closely fitting hole without jamming or wedging. The device is reminiscent of the Remote Centre Compliance (RCC) mechanism used by assembly robots to insert cylindrical pegs into cylindrical holes with small clearances. However, whereas the RCC mechanism has primarily to withstand compressive forces, the proposed compliant device must resist tensile forces because of the nature of disassembly operations. The paper details a finite-element modelling study of peg removal with and without using the compliant structure. The results obtained show that the structure markedly reduces the stresses at the points of contact between the peg and the hole and, consequently, the risk of damage to the components being disassembled. [ABSTRACT FROM AUTHOR]

Remanufacturing automation must be designed to be flexible and robust enough to overcome the uncertainties, conditions of the products, and complexities in the planning and operation of the processes. Machine learning methods, in particular reinforcement learning, are presented as techniques to learn, improve, and generalise the automation of many robotic manipulation tasks (most of them related to grasping, picking, or assembly). However, not much has been exploited in remanufacturing, in particular in disassembly tasks. This work presents the state of the art of contact-rich disassembly using reinforcement learning algorithms and a study about the generalisation of object extraction skills when applied to contact-rich disassembly tasks. The generalisation capabilities of two state-of-the-art reinforcement learning agents (trained in simulation) are tested and evaluated in simulation, and real world while perform a disassembly task. Results show that at least one of the agents can generalise the contact-rich extraction skill. Besides, this work identifies key concepts and gaps for the reinforcement learning algorithms' research and application on disassembly tasks. [ABSTRACT FROM AUTHOR]

Automate finishing processes is a global challenge in several industrial sectors. Concretely, when dealing with aero-engine components, only simple finishing processes are automated nowadays. Most of the high-added value components manufactured are finished hand working, using deburring and polishing manual techniques. The driver of the proposed work is to achieve the necessary knowledge to introduce in a production line a complete finishing process for automated robotic deburring applications with low machinability materials (Inconel 718 in this case-study) on aero-engine casings with complex geometries: extruded casting bosses, internal features, etc. For this purpose, a three-step methodology is presented and analysed, providing a feasible workflow combining visual inspection for part positioning and edge location, with multi-edge solid tools and flexible abrasive tools to automate finishing operations, taking into account all process singularities. Results show that, using correct techniques, processes and parameters, an automated finishing process reducing operating time can be implemented in production lines. [ABSTRACT FROM AUTHOR]

The use of industrial robots for machining large parts has attracted more and more attention. Previous studies have shown that ball-end milling is greatly affected by the process parameters. Besides, robotic machining is also affected by various posture-dependent robot performances. However, these two critical aspects are usually treated separately in many works studying robotic machining. In this paper, a robotic machining system consisting of a six-axis industrial robot, a two-axis positioner and a linear track was developed. The combined effects of milling process parameters and robot postures on the machining results were experimentally investigated. Grey relational analysis–based multi-objective optimization was conducted for lower cutting force and better surface quality. A group of process parameters and robot postures were obtained as the optimal combination that generally yields the best milling performance. The results allow users to preliminarily determine the main factors affecting the quality of robotic machining. [ABSTRACT FROM AUTHOR]

The poor rigidity of large composite material components in the helicopter has an important impact on robotic milling stability. Based on the machining stability of robotic edge trimming process, a method for calculating the component overhang is proposed in this paper. Firstly, the stability model of robotic longitudinal-torsional ultrasonic milling component (RCUM-LT) with poor rigidity is established by machining dynamics analysis. Then, the influence mechanism of variables such as ultrasonic vibration energy, workpiece overhang, and edge thickness on the stability region of robotic edge milling is explored emphatically. The calculation results show that the intake of ultrasonic energy suppresses robotic milling chatter effectively. As a result, the stability region of RCUM-LT is increased by 361.79%. In addition, the smaller the component overhang, the better the stability of edge milling will be. The effect of component thickness on RCUM-LT stability is the combined action result of modal property and dynamic milling force. Considering the influence of three variables on the stability region comprehensively, a reasonable boundary curve of the adsorption position is achieved according to RCUM-LT stability model. It provides technical support for realizing robotic edge milling composite material with high efficiency and stability. Finally, the verification experiments are carried out for stability lobes and optimal overhang length. The results show that the experimental results of RCUM-LT stability are in good agreement with the theoretical prediction. With the adsorption method proposed by this study, the surface roughness and its consistency of machined surface are significantly improved. [ABSTRACT FROM AUTHOR]

A main challenge in the additive manufacturing (AM) field is the possibility to create structures with embedded actuators and sensors: addressing this requirement would lead to a reduction of manual assembly tasks and product cost, pushing AM technologies into a new dimension for the fabrication of assembly-free smart objects. The main novelty of the present paper is the one shot fabrication of a 3D printed soft finger with an embedded shape memory alloy (SMA) actuator and two different 3D printed sensors (strain gauge and capacitive force sensor). 3D printed structures, fabricated with the proposed approach, can be immediately activated after their removal from the build plate, providing real-time feedback because of the embedded sensing units. Three different materials from two nozzles were extruded to fabricate the passive elements and sensing units of the proposed bioinspired robotic finger and a custom-made Cartesian pick and place robot (CPPR) was employed to integrate the SMA spring actuator into the 3D printed robotic finger during the fabrication processes. Another novelty of the present paper is the direct integration of SMA actuators during the 3D printing process. The low melting thermoplastic polycaprolactone (PCL) was extruded: its printing temperature of 70 °C is lower than the SMA austenitic start temperature, preventing the SMA activation during the manufacturing process. Two different sensors based on the piezoresistive principle and capacitive principle were studied, 3D printed and characterized, showing respectively a sensitivity ratio of change in resistance to finger bending angle to be 674.8 Ω ∘ Angle and a capacitance to force ratio of 0.53 pF N . The proposed manufacturing approach paves the way for significant advancement of AM technologies in the field of smart structures with embedded actuators to provide real-time feedback, offering several advantages, especially in the soft robotics domain. Highlights: • One shot fabrication of a smart bioinspired finger equipped with a shape memory alloy (SMA) actuator, piezoresistive strain gauge and capacitive sensor • Automated integration of the SMA spring actuator during the 3D printing process by exploiting the low melting thermoplastic polycaprolactone and a pick and place robot • Study of the process parameters to reduce the 3D printed strain gauge resistance of 142% [ABSTRACT FROM AUTHOR]

Currently, the quality check of bike frame still heavily relies on human operation. In practice, an entire checking process usually takes more than 30 min to complete. To overcome this dilemma, this paper aims to develop a fast high-precision measurement system using robotic arm based on 3D geometry mathematical model. Instead of four points needed to find coefficients of a space sphere, only three investigation points are required to achieve the sphere axis coordinates for measurement. The personal computer (PC) works as a control core, which to perform the mathematical model and control robotic arm movement. The robotic arm combined with contact sensor (probe) is used to move to the desired inspection points in shaft length, internal diameter, verticality, and parallelism following up the designated path planning route. The experimental results confirm that the proposed system can accurately reach the measurement outcomes. The entire checking cycle can be completed in 3 min at the range of 0.15 mm error, effectively reducing the process time with a high precision. [ABSTRACT FROM AUTHOR]

Human–robot collaborative systems are being increasingly adopted in manufacturing environments due to their application flexibility, adaptability, and cost-effectiveness. The majority of robotic systems use electrical current sensors to measure joint torque in industrial robot arms and limit the robot's impact in the event of an unanticipated acceleration/deceleration, such as in the event of a collision with a human operator. However, these electrical current sensors are known to experience sensor drift, which results in measurement inaccuracy that can result in improper joint-torque or end-effector force readings. This paper provides a method to compensate for electrical current drift using a neural network-based controller to control robot velocity. To evaluate the compensation method, an experimental setup was developed where a robot joint collided with the biofidelic test device that mimics the deformation response of the human forearm while simultaneously measuring deformation and contact force using an embedded soft force sensor. The proposed method was shown to compensate for electrical current drift and therefore reduce resulting contact forces between the robot and the biofidelic test device. Hence, this research provides a method to quantify the behavior of electrical current sensor drift on human–robot collision and presents a data-driven methodology for compensation. [ABSTRACT FROM AUTHOR]

This paper presents the development of a robotic manipulator system for three-dimensional (3D) printing. Most closed-loop inverse kinematics (IK) methods that handle IK problems result in a robotic manipulator with a slight deviation, which may lead to inappropriate material stacking and defective objects or even damage the extruder. These methods are feasible when manipulating the motion of the robotic arm, but using these methods on the robotic arm for 3D printing can cause errors. Here, a null-space control with three potential fields to ensure completion of the primary task without disturbance, namely joint limit avoidance, singularity avoidance, and orientation error minimization, is applied to provide a safe solution. Minimizing orientation error can avoid extruder flipping, and a singular value decomposition-based singularity avoidance method is proposed to make calculations faster and more accessible. The null-space control method with three potential fields was numerically simulated. The proposed method and robotic manipulator system, conducted in freeform surface printing, were experimentally validated. [ABSTRACT FROM AUTHOR]

The pneumatic constant force control device has been widely used in robot deburring, sanding, polishing, and other fields due to its good flexibility, simple control, and low cost. The force control accuracy of the pneumatic constant force system could be greatly affected by its nonlinear hysteresis characteristics in the process from the cylinder input to the force output at the end of the device. A rational Bezier-based state fitting method (BSFM) has been presented for calibrating the inherent nonlinearity of the low-cost pneumatic constant force system. Compared with the most widely used PSFM, which is a polynomial-based state fitting method, the BSFM could calibrate the strong inherent nonlinearity of the system more smoothly with the lower ordered model and in a continuous form rather than the piecewise form of the PSFM. The BSFM could maintain a balance between simplicity and precision. Through a series of comparative experiments with different contact forces and feed rates, the proposed method has smaller force overshoot and when active force control is turned on, the force variation is greatly reduced to less than 2 N. The average roughness of the workpiece reached 0.4 µm after polishing. [ABSTRACT FROM AUTHOR]

The potential of additive methods to integrate with machine learning (ML) models in hybrid manufacturing is significant in developing closed-loop processes for intelligent and adaptive control. This study presents a framework to defect mitigation that leverages a hybrid deep convolutional neural network (CNN) architecture with laser powder bed fusion additive systems. It connects on-site optical vision and sensor streams to identify process abnormalities and report real-time remedial actions. The hybrid CNN automatically connects reported anomalies to the physical actuation where quality issues might occur in a closed-loop fashion. This enables self-learning and autonomous corner-cutting while offering a pathway to new applications in digital manufacturing, such as surface finish optimisation and shape adaptation within a single build. In a case study, we demonstrate that our framework enables inspection and control at a level never seen before, as demonstrated by its precision in product inspection with an F-score of 93.8% and its ability to adjust control at a frequency exceeding 10 Hz. This work not only enables new learning paradigms for the development of real-time control systems for hybrid manufacturing, but also accelerates the process of AI-driven intelligent manufacturing by equipping industrial production systems with intelligence, flexibility and resilience. Our technique for tight coupling of process signals and actuation is a significant technical breakthrough in this critical pathway. [ABSTRACT FROM AUTHOR]

Low-pressure turbine blades are the most erosion-exposed moving parts of the steam turbine. This article brings a detailed overview of an innovative system applying a stellite coating to the leading edge of the steam turbine blades using the robotic laser cladding technology. The system is based on a software that gathers scanned data of the shape-specific workpiece from a laser profile scanner, creates a 3D model of the workpiece and generates a set of laser cladding trajectories that are used for the task of robot navigation during the laser cladding process. The navigation algorithm accounts for the workpiece-specific requirements of the laser cladding process as well as collision avoidance necessities. The shape and thickness of the resulting layer of the laser-cladded coating alloy are verified by an external 3D scanning system showing the compliance of the system with the requirements as well as a space for future development. The feasibility of the developed method is also verified by multiple material and metallographic tests. [ABSTRACT FROM AUTHOR]

Chatter is a key problem that restricts the quality and efficiency of robotic milling, and the modal characterization of the robotic milling system is an important factor that affects the chatter. Doppler vibration measurement experiment shows that the vibration mode of the robotic milling system changes significantly with different modal frequencies under the sweep frequency excitation. The low-frequency mode shape is mainly manifested as the vibration of the robotic structure, while the high-frequency vibration mode shape is mainly manifested as the vibration of the spindle-tool structure. Therefore, the dominant modes of chatter are different under diverse cutting parameters, and the chatter suppression strategies are also significantly different. In order to provide a theoretical basis for the targeted chatter suppression under different cutting parameters, this paper studies the influence law of the robotic structure modes and spindle-tool structure modes on the chatter in the robotic milling system and establishes the analytical method of the dominant mode for the chatter of the robotic milling system. Firstly, the vibration mode shape of the robotic milling system is measured by a Doppler laser vibrometer, then the type of chatter is determined. Based on the classification of chatter types, the dynamic model considering the chatter dominated by robot mode and spindle-tool mode is established. Then, based on the variation law of chip wave phase difference (CWPD), a chatter participation degree analysis (CPDA) method is proposed to analyze the dominant mode for the chatter. The accuracy of the CPDA method on judging the dominant mode for the chatter is verified through a robotic milling experiment. The analysis results show that the number of teeth, modal parameters, and spindle speed will affect the change of dominant mode for the chatter. Finally, based on the analysis of the CWPD, a rapid evaluation index called the modal influence factor (MIF) for chatter dominant mode is proposed. The MIF proposed in this paper can effectively realize the judgment of the dominant mode for the chatter and provide theoretical support for chatter-free machining of the robotic milling system. [ABSTRACT FROM AUTHOR]

This paper aims to study tasks' allocation problem in a single-station collaborative robot assembly system 4.0. Two products with identical demands are run in a system simultaneously in mixed mode to reduce the idle time and improve the system utilization. The idle time occurs due to balancing difficulties and particularly in this case restrictions in the task vs. robot-worker feasibility matrix. It is not allowed for the resources to assemble a same product simultaneously to avoid any direct contact between resources. Thus, the products are swapped between resources as needed to complete the assembly tasks. Two approaches, a novel mathematical model and the shortest processing time (SPT) rule, are propounded in this study to reduce the cycle and idle times and enhance the production rate of an assembly system. The two proposed methods rely on dividing the timeline of a station into unknown stages with unknown lengths. The performance of the proposed mathematical model and SPT rule are evaluated by two performance measures: the total number of stations and the % average station utilization. The obtained results are compared to the results of the modified COMSOAL heuristic. The findings revealed that the novel mathematical model dominated results. It guaranteed minimizing the cycle time and maximizing the production rate compared to the SPT rule and modified COMSOAL heuristic. However, many companies value a 1-s reduction in cycle time as valuable. This directly relates to the reduction of direct resources costs and the total number of stations. [ABSTRACT FROM AUTHOR]

Narrow space characteristic is a common structural feature of aircraft assembly, which puts forward higher requirements for the end-effector of a robot drilling system. This paper proposed a new robotic simple and fast drilling system for aircraft automatic assembly. The robot drilling system and control scheme are designed. The end-effector is designed and calculated theoretically. The workflow of the whole system is designed and analyzed. Besides, a new calibration method is proposed for the system calibration includes the calibration of the robot end-effector and the calibration of the robot system relative to the machined parts. Finally, some drilling experiments are designed to verify the effectiveness of the proposed system. The results show that the newly designed robotic drilling system can meet the requirements of aircraft part drilling, such as the drilling accuracy is better than 0.5 mm, the drilling process is more stable, and the rigidity of the system is better. The drilling error of the hole diameter of this system can be controlled below 0.1 mm. The relative distances between holes in the X and Y direction and the hole edge distance meet the technical requirements, and all errors can be controlled to less than 0.5 mm, respectively. [ABSTRACT FROM AUTHOR]

Traditional computer numeric control (CNC) machines have high accuracy but are limited by workpiece size and axes. Therefore, many researchers attempted to equip six-axis industrial robots (IRs) with milling end-effectors to explore the robot's large and flexible working envelope. However, IRs lack stiffness and have limited force, resulting in low accuracy, poor surface roughness (SR), and low material removal rate (MRR). On the contrary, electric discharge machining (EDM) is a non-conventional process capable of shaping complex profiles in any conductive material. Since the EDM process has no physical contact between the electrode and the workpiece, it can machine diverse hard-to-cut materials accurately and free of vibration. However, to this day, EDM is found in limited conditions of CNC machines only. Thus, this research investigates a synergistic combination of IR and milling EDM. Adopting advanced CAM tools and offline programming, it examines pre-designed electrodes working analogue to conventional milling to perform the desired machining by intricate cutting paths. The results deliver a robotic machining technique able to cut hard materials using small industrial robots yet free of vibration and not pose dependent. [ABSTRACT FROM AUTHOR]

Since industrial robots have redundant degree-of-freedom (DOF), both tool orientation and redundant angle have to be well planned to determine a unique robotic posture. The existing sequential planning method mainly uses the method developed specifically for machine tools to plan tool orientation and then adjusts the redundant angle to improve the robot stiffness, ignoring the differences in stiffness, configuration, etc. between robots and machine tools and the influence of tool orientation on the stiffness. Moreover, due to the kinematics of robot is highly nonlinear, the tool orientation with maximum stiffness cannot guarantee smooth joint motion. To address these problems, this paper proposes an integrated strategy that considers comprehensively robot stiffness and joint motion to plan the tool orientation and redundant angle simultaneously. The stiffness feasible space (SFS) of the robot along the entire tool path is first constructed, which is used as constraint for the subsequent tool orientation and redundant angle planning. Then, a machining error-controllable joint smoothing model is proposed to smooth three joints subjected to the heavy kinematic loads to improve the kinematics performance, and the other three joints are used to maintain the tool at its planned position to control the machining error. To simplify the solving process, an alternate strategy of first generating tool orientation and redundant angle and then checking stiffness constraints is developed, and the iteration solving is repeated until all the generated tool orientations and redundant angles are in their SFSs. Meanwhile, the machining error caused by the smoothing of joint motion is also controlled. Finally, the conducted experiments validate the proposed method. [ABSTRACT FROM AUTHOR]

Aiming at the redundant degree of freedom problem of six-axis industrial robot performing five-axis milling task, a new optimization method of robotic milling redundant degrees of freedom considering chatter stability was proposed. Firstly, based on the zero-order approximation method, the limit cutting depth of robotic milling regenerative chatter is established as a function of redundant degrees of freedom. Then, taking the limit cutting depth of robotic milling regenerative chatter as the optimization objective, and combined with the constraints of robot motion performance (avoiding joint limit, singular posture, and collision), an optimization model of redundant degrees of freedom considering chatter stability was established. Finally, the discrete optimization search algorithm is used to solve the optimization model to determine the optimal redundant degree of freedom. The milling experimental results showed that the new optimization method of robotic milling redundant degrees of freedom considering chatter stability proposed in this paper can effectively avoid robotic milling regenerative chatter and improve machining quality and efficiency. [ABSTRACT FROM AUTHOR]

In order to solve the problem of the trajectory planning of robotic plasma cladding for complex surface coating, the concept of non-uniform rational B-spline (NURBS) function open-/closed-loop mapping is proposed firstly in this work to explore the new approach of the trajectory planning for complex NURBS surfaces. The trajectory planning is carried out by a 2D-NURBS curve C(u) on a 2D plane, which is mapped on a predefined 3D-NURBS surface S(u,v) using the NURBS surface function to form a 3D mapping curve named NURBS function mapping (NURBS-FM) curve. Using the fixed step (FS) interpolation, the equal chord length (ECL) interpolation, the equal arc length (EAL) interpolation, and the equal bow height (EBH) interpolation, etc., a complex curve can be interpolated. The FS/ECL/EAL/EBH can be defined as constraint. Depending on where the constraint is applied, the NURBS-FM can be divided into open-loop mapping and closed-loop mapping. The NURBS function open-loop mapping (NURBS-FOLM) is carried out along the route of u → C(u) → S(u,v), while the NURBS function closed-loop mapping (NURBS-FCLM) along the route of u → C(u) → S(u,v) → u → .... The constraint is applied to the 2D-NURBS curve in NURBS-FOLM, while to the 3D NURBS-FM curve in NURBS-FCLM. The NURBS-FOLM and NURBS-FCLM can ensure that the interpolation points on the 2D-NURBS curve and 3D NURBS-FM curve have the ECL/EAL/EBH characteristics, respectively. When the 3D NURBS-FM curve is regarded as plasma cladding trajectory, the NURBS-FCLM can provide engineers with a new ECL/EAL/EBH interpolation method for cladding trajectory. Using the NURBS-FCLM approach based on the serial robotic plasma cladding, a high entropy alloy coating is prepared on Q235 substrate which employed the AlCoCrCuNiNb high entropy alloy powder with optimized parameters (Ar flow, ion gas flow, current, powder feeding speed, cladding feedrate) = (6L/min, 1.7L/min, 115A, 15 mm/s, 1.4 mm/s). The formation of the complex spacial curve coating on the complex surface is well without obvious defects. The simulation and experiment verify that the NURBS-FCLM is feasible and effective. It provides the technical and theoretical basis for the serial robotic plasma cladding trajectory planning of complex surface coating. With the increasing application of complex parts in various industries, the NURBS-FOLM and NURBS-FCLM technologies have more and more broad application prospects in the manufacturing of new complex product coatings and remanufacturing of old ones based on serial robotic laser/arc cladding platform. [ABSTRACT FROM AUTHOR]

For decades, researchers have struggled to solve 6-axis robotic vibration while machining hard-to-cut materials. On the other hand, wire electric discharge machining (WEDM) stands out as a non-conventional machining process able to cut large and complex profiles of any conductive hard-to-cut material with minor non-contact forces. Thus, WEDM is a promising process to be combined into a robot to overcome vibration and low accuracy. However, the robot characteristics of a high degree of freedom combined with payload limitation oblige to separate the heavy wire winding system from the robot end-effector, demanding an equally high degree of freedom and unconventional solutions to feed and control the wire electrode. This study designs and reports experimental findings of the first robotic WEDM apparatus based on a high-speed winding system with 600 m of wire length, capable of controlling the wire speed from 1 to 10 m/s and wire tension from 0.1 to 10 N. The system adopts flexible outer cases to travel and reciprocate the wire into a 7-axis robotic system composed of a 6-axis robot and an external rotating axis. The proposed design is a highly dynamic process whose wire tension and speed are achieved by a hybrid controller to cope with the non-linear relation of speed and tension provided by the magnetic clutch. It combines a regression open-loop control for optimality and wire breakage avoidance with a closed-loop control to guarantee admissibility while coping with wire friction disturbances. The findings review a novel wire winding system capable of controlling usual wire disturbance and stepped surface of reciprocating high-speed WEDM as well as additional friction and elastic behaviour of the flexible case, delivering wire tension of ± 12% along with stable EDM process and uniform surface roughness between wire reciprocation areas with a Ra of 2.94 μm. Potential adoption of the method can finally make 6-axis robots a feasible and advantageous technique compared to computer numeric control (CNC) while shaping monolithic and complex workpieces of conductive and hard-to-cut materials. [ABSTRACT FROM AUTHOR]

In the automatic polishing process, the wear of polishing tools and the change of polishing parameters will affect the Preston coefficient, which makes it difficult to establish an accurate material removal model to achieve stable and excellent polishing quality. In this paper, a robotic polishing parameter optimization method considering time-varying wear is proposed to address these issues. First, combining the rich information in the theoretical modeling method with the data-driven regression method, a material removal regression model incorporating prior knowledge is proposed, which greatly reduces the large amount of experimental data required by the original regression model. The proposed model is able to track the wear variation of the sandpaper as well as the effect of polishing parameters. Then, based on the proposed prediction model, the genetic algorithm is used to optimize the polishing parameters in order to achieve better machining quality and less energy consumption. Finally, the experimental verification is carried out on the hybrid robot polishing test bench. The results show that the proposed material removal regression model incorporating prior knowledge has higher prediction accuracy and less required experimental data than existing models. The proposed robot polishing parameter optimization method can effectively compensate for tool wear and ensure the consistency of material removal during polishing while reducing energy consumption. [ABSTRACT FROM AUTHOR]

This paper proposes a novel constant force tracking control scheme based on an impedance controller with online stiffness and reverse damping force (OSRDF) to track desired force. An interaction contact force between the robot end-effector and its environment was represented and analyzed using the full mechanical second-order system and individual spring model. A position-based impedance controller is used to receive a contact force signal to track the constant desired force. The proposed approach tracks the desired contact force and reference trajectory based on reference position and velocity. This OSRDF controller is implemented by adjusting the online stiffness parameter and merging the inverse damping force with the force tracking error to compensate for the unknown environment and reduce the force error to zero. A Lyapunov function is applied to investigate the stability of the OSRDF impedance controller during implementation. Simulation studies and experimental tests on a seven degree of freedom (7DOF) robot manipulator are performed to evaluate the efficiency of the proposed method compared to the traditional constant impedance controller. The results showed the validity and effectiveness of the OSRDF method and revealed a relationship between the end-effector velocity and force tracking error. The proposed approach improves force tracking accuracy with simpler computational processes in simulation and practice. [ABSTRACT FROM AUTHOR]

Compared with traditional CNC machine tools, industrial robots have higher flexibility and lower cost in the machining field. However, the relatively low stiffness of the robot makes it difficult to meet the accuracy requirements. In this paper, a robot machining posture optimization method is proposed to improve the performance. First, a deformation index considering the robot stiffness compensation matrix K C is proposed to evaluate the stiffness performance of the robot machining trajectory. Then, by minimizing the deformation index under consideration of kinematic constraints, a robot posture optimization model is established. The discrete Dijkstra optimization method is proposed to solve the global optimal solution to the model. Finally, the effectiveness of the robot deformation index and posture optimization method has been verified by a series of simulations and experiments in the Motoman ES165D robot. [ABSTRACT FROM AUTHOR]

Joint deformation greatly influences machining accuracy for a robotic arm. In this paper, the deformation characteristics of the robotic arm with hybrid kinematic chains are investigated to improve its machining accuracy. Firstly, the deformation model of the joints has been established based on the Strain energy method and Castigliano theorem according to the robot structure. Secondly, the deformation influence coefficient (DIC) is defined to investigate the deformation influence of main components on the end-effector, and the deformation characteristics are evaluated by the simulation. Finally, a small size robotic arm prototype is established and robotic drilling comparative experiments are conducted. The theoretical and experimental results show that the machining method can be selected according to the DIC, in which the force can be applied to the components with better stiffness. On the other hand, the deformation of driving components can also be reduced when the DIC cannot be adjusted to meet the accuracy requirement. [ABSTRACT FROM AUTHOR]

For robotic polishing of curved surfaces with compliant polishing disc, it is critical to accurately control the tilt angle of the polishing disc and normal contact force between the disc and the workpiece surface simultaneously. As conventional industrial robots lack force control capability, a 3-DOF two-rotational-one-translational (2R1T) force-controlled end-effector based on the 3-PPS parallel mechanism is developed for robotic polishing. During the polishing process, the changes of the tilt angle of the end-effector's moving platform will result in displacement variations of the contact point, owing to the inherent parasitic motion of the end-effector module, the geometry of the disc, and the compliance of the disc. Without proper compensation of the displacement variation, the control accuracy of contact force will be significantly decreased. To tackle this problem, a parametric model is established to predict the contact point variation. A hybrid orientation/force control architecture with compensation of the contact point variation is proposed. Based on the kinematic analysis, orientation control is achieved through a position controller. The force tracking control considering the uncertainty of the environment is achieved through an admittance controller. By introducing the contact point compensation model into the control architecture, the control accuracy of the contact force is significantly improved. The proposed control architecture is evaluated on a macro-mini manipulator consisting of a 6-DOF industrial robot and the 2R1T force-controlled end-effector. The experimental results indicate that the orientation control is accurate and the mean force errors with three different kinds of tilt angle references are reduced by 78.9 % , 81.1 % and 72.3 % compared to the conventional hybrid orientation/force control, respectively, which validate the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

The force-controlled end-effectors for industrial robots usually face the problems of low output force, poor control accuracy, or slow dynamic response. This paper presents a pneumoelectric force-controlled end-effector (PFE) for industrial robots to perform continuous contact operations. The end-effector possesses the advantages of both the pneumatic drive having large force-mass ratio and the electric direct drive having high force control accuracy and fast dynamic response. Through dynamic modeling and analyses, a force coordination control method based on impedance control is proposed for the PFE. The pneumatic cylinder is actuated by a semi-closed loop, while the voice coil motor (VCM) is controlled through a closed loop to improve the output force, accuracy, and dynamics. Impedance controller is utilized to reduce the impact caused by the critical contact between the tool and workpiece. Simulation analyses show that the force-mass ratio has increased, while the friction influence and overshoot has been reduced. In addition, prototype experiments verify the effectiveness of force control method and demonstrate that the PFE is able to achieve good performances such as control accuracy, step response, and dynamic bandwidth. Compared with the traditional pneumatic end-effector, the force control hysteresis is almost reduced from 41.9 to 0% without apparent creeping phenomenon. The rise time of the step response also decreases from 435 to 6.5 ms, and the bandwidth reaches 47 Hz. The PFE with force coordination control shows great potential in robotic deburring, grinding, and polishing applications. [ABSTRACT FROM AUTHOR]

With an advantage of "single-sided welding and double-sided forming," plasma arc welding (PAW) has a great application potential in modern industrial production. The welding quality can be guaranteed by sensing and controlling of the keyhole. However, it is difficult to make an on-line observation on the back of base metal, and realize a dynamic registration of the visual sensor and welding torch. In this study, it has investigated the relationship between the welding condition and image feature of keyhole. Image processing is designed to obtain the weld pool image and conduct a template matching of the keyhole. The target feature of weld zone will be extracted and processed in real time. Besides, it has designed a digital controller for the welding robot and power source in this study and discussed control method to stabilize the keyhole and achieve good welding quality. Eventually, experiments are conducted to inspect the comprehensive performance of the welding control system with varying disturbance. This study is of important significance for the visual sensing and controlling of the keyhole in PAW. It will provide technical support for the weld quality control, and promote the development of welding technology based on machine vision in intelligent manufacturing field. [ABSTRACT FROM AUTHOR]