Robotic Assembly Process Research Articles

Similar assembly state discriminator for reinforcement learning-based robotic connector assembly

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 parts are changed, it becomes difficult to apply RL-based methods to assemble various parts because additional learning may be required. Especially in the case of connector assembly, fine-tuning is essential because the shape changes depending on the type of connector. In this study, we propose a similar assembly state discriminator that transforms the state information (force, velocity, and RGB image) of reinforcement learning into generalized features to respond various types of connector assembly tasks. This method processes the data to include essential features for assembly regardless of connector type. By learning the RL model with the processed data using this method, the RL model trained for a specific connector can be efficiently applied to other types of connectors without fine-tuning. The assembly success rate for the 7 types of connectors (Harting, HDMI, USB, power, air jack, banana plug and PCIE) using the proposed method was demonstrated to be over 96 %.

Contact-based pose detection method for small components to optimise the digital twin-driven robotic assembly process

The robotic assembly has become pivotal in manufacturing, demanding precise pose detection of assembly components for efficient operations. This paper presents a contact-based pose detection method tailored for digital twin-based optimisation for the robotic assembly process, focusing on small component assembly challenges. The proposed technique achieves robust pose estimation by leveraging a strain gauge load cell-based calibration method. Experimental validation demonstrates close alignment between induced and measured errors, showcasing the efficacy of the method in mitigating assembly challenges. Despite minor deviations, the approach outperforms traditional vision-based methods, promising enhanced efficiency in robotic assembly tasks. Further refinement could bolster accuracy, fostering advanced robotic assembly capabilities.

An Effective Virtual Reality Paradigm for Robotic Assembly in First-Year Engineering Curriculum

An effective Augmented Reality and Virtual Reality paradigm is proposed to facilitate introductory robotics course in the first-year engineering curriculum. The AR/VR Application utilization and its impact on the students' learning with respect to robotic assembly and robotic application programming is emphasized in this article. The paper delves into a comprehensive review of the related works presented in the literature. The requirements for the physical assembly and virtual assembly of movable robots are meticulously highlighted. To facilitate course learning a robotic workshop involving steps introduction to robotics, and practical experience on the robot is conducted. The delivery of the course content is made much more effective by inculcating the Virtual experience of the Robotic assembly process. The virtual robotic assembly and manual physical robotic assembly process processes have their own uniqueness and importance and it is left to the students to pick them on a priority basis. Finally, the effectiveness of the proposed course is determined by conducting an online quiz, collecting student feedback, tabulating and analyzing the results.The results demonstrate the effectiveness of the proposed method in creating interest in robotics and related courses among first-year engineering students. Keywords— Augmented Reality(AR), Virtual Reality(VR), Build Your Own Robot(BYOR), Robotic assembly.

Vision based control strategy to suppress residual vibration of flexible beams for robotic assembly using wrist motion

Automated assembly tasks require industrial robots to improve the efficiency of the manufacturing process. Most rigid or flexible objects handled by robots vibrate due to motion and transient disturbance. This work proposes an active vision-based vibration suppression strategy for flexible beams by providing motion to the wrist of a robot during robotic assembly process, which reduces the time to suppress vibration. The proposed method uses a cheap monocular camera to identify objects through a virtual marker and measure their dimensions. Subsequently, finite element method based mathematical model of a flexible beam predicts the maximum error. The proposed second stage controller determines the controller input in terms of wrist motion based on the predicted maximum error. The performance of the controller is assessed through simulations and experiments on metallic beams with different material characteristics and dimensions. The controller suppresses vibration amplitude within a safe limit so that object is inserted into the slot. It was observed from experiments that the controller can reduce vibration amplitude by ~96% in less than 2 s and decrease suppression time up to ~97%. These improvements were achieved without disturbing the internal robot controller.

Enhancing Safety and Collaboration in Human Robot Interaction for Industrial Robotics

This research evaluates the aspect of collaboration between humans and robots in industrial robotics. It highlights the advantages of using robots in non-ergonomic tasks while at the same time recognizing that there are challenges preventing them from achieving manipulation accuracy with precision. Collaborative robots also known as robots, have been proposed to address these limitations. Safety has been identified as one of the most critical issues in collaborative environments, which calls for a discussion on various strategies and practices to ensure the safety of operators. The study explores many facets of human-robot interaction and collaboration such as physicality and proximity, house sharing, and collaboration. Furthermore, this article argues that it is vital to consider human aspects of human-robot interaction such as trustworthiness, mental effort, and fear. The final part presents a case study on incorporation of humans and robots in assembly and sealing process of refrigerator. Finally, this case underlines safety measures that need to be included during robot type selection and assembly process equipment used should match robot’s characteristics like size etc. This study suggests possible avenues for future inquiry including augmented reality methods and integrating safety constraints into design software and planning software.

Influences of space perturbations on robotic assembly process of ultra-large structures

The space assembly of two flexible beams by a dual-arm space robot is a typical assembly scenario to construct ultra-large space structure. Yet, previous studies mainly focused on the assembly of small structures, neglecting the influences of space perturbations. Two models are developed in this research to investigate the effects of space perturbations on the space assembly process of ultra-large space structures. Firstly, a theoretical modelling method is proposed based on quasi-static hypothesis and linear structural mechanics. The theoretical model can be utilized for analytically estimating the transverse and axial distributed forces of the flexible beams, structural vibrations, and the control moments of the space robot. An orbit–attitude–structure coupled simulation model is then established to validate the theoretical model and study the dynamic behaviours more accurately, using absolute nodal coordinate formulation and natural coordinate formulation. Finally, the effects of the attitude angle, orbital radius, and lengths of beams on the dynamic responses during assembly are investigated. Theoretical and simulation results show that the control moments and structural vibration amplitude increase dramatically with the length of the beams. The effects of Coriolis force and gravity gradient must be considered for ultra-large space structures during assembly, otherwise the control moments and structural vibrations would be substantially underestimated. The results are instructive to the assembly strategy design as well as modular component design of ultra-large space structures.

BIM-based simulation of construction robotics in the assembly process of wood frames

One main challenge in the development/implementation of construction robotics is the need of accurate and explicit information as input for the robots to reliably perform the designated tasks. Building information modeling (BIM) can fill this gap by providing information to the construction phase that utilizes automated fabrication. However, current BIM authoring tools and construction workflows do not directly support robotic simulation and are not designed to be compatible with robotic technologies. Thus, the authors developed a simulation-based methodology to evaluate the automated assembly of wood frames. Results showed that the robotic assembly process was successfully simulated/analyzed on three test cases. Compared to manually creating such robotic simulations, the proposed approach was on average 39 times faster and is expected to dramatically reduce errors from design to build. The proposed approach opens a new door for practitioners to analyze a building design related to the use of robotics for its construction.

Research of the reliability of a robotic assembly based on the effect of rotation and low-frequency vibrations

Using various physical and technical effects in automatic assembly is a promising tendency to increase the technological reliability of the assembly process. The article presents a method for robotic assembly of cylindrical joints using the effect of rotational motion and low-frequency vibrations. The effect can be achieved by using low-frequency vibrations of the base part with the help of a vibrating device and the rotational movement of the installed part with the help of the rotational movement of the robot out-put link. The paper presented a mathematical model of the dynamics of the robotic assembly process of cylindrical joints. Experiments were set up and carried out to test the effectiveness of the proposed assembly method. The research results affirmed that with a rational technological mode of the robotic assembly process using the effect of rotation and low-frequency vibrations, the probability of jamming is completely eliminated and the assembly force is significantly reduced.

Online performance optimization for complex robotic assembly processes

The variations and uncertainties in complex assembly processes could cause conventional industrial robots failure to perform assemblies. Therefore, intelligent robots must be developed which can adapt to these variations and uncertainties; moreover, the assembly process parameters must be optimized to satisfy the performance requirements such as First Time Throughput (FTT) rate and cycle time. However, it is challenging to optimize the performance of complex robotic assembly systems. The existing solutions are not efficient and human knowledge is needed to perform experiments and explore optimal parameters. These requirements greatly limit the applications of robotic assembly in manufacturing automation. In this paper, a robotic assembly process optimization method is developed for complex assembly processes. We propose a modeling method based on Gaussian Process Regression (GPR) to construct a model to build the relationship between the process parameters (input) and system performance (output). The GPR surrogated Bayesian Optimization Algorithm (GPRBOA) is improved to iteratively optimize the robotic assembly performance. Two industrial assembly processes (a tight-tolerance peg-in-hole assembly process and a torque converter assembly process) are used to verify the proposed method. The experiments were performed many times and the results demonstrate that the proposed GPRBOA method can optimize the complex assembly process parameters effectively and efficiently. The proposed complex assembly process optimization method opens a door for online manufacturing process optimization and will greatly reduce the manufacturing cost.

Comparative analysis of the manual and robotic upholstery frame assembly processes. Study based on many years of research

A robotization of assembly is the real implementation of Industry 4.0 in the furniture industry. The robotization objective is to obtain favorable values of production process parameters (performance, productivity, quality) and to improve human wellbeing at work. Our aim was to present and compare the quality parameters of a selected furniture production process, performed in a very long series, containing more than 30 thousand products. The analysis included the results of the long-term measurements of the quality level of upholstery frames produced by the modified and improved, on the basis of operational conclusions, robotized line for the serial production of upholstery frames and by the simultaneously used nonrobotic line for assembly of frames of the same construction. The results obtained show that robotized assembly leads to a much lower percentage of defective products than in the case of the nonrobotic technology, the causes and types of defects in the products are also different, and it is easier to prevent these defects and remove them. The cognitive findings identified problems and challenges, not found in traditional technologies, caused by the using of manufacturing robots in furniture production.

Online Modeling and Parameter Optimization Method for Robotic Complex Assembly Process of Gear

Online Modeling and Parameter Optimization Method for Robotic Complex Assembly Process of Gear

Skeletal composites: robotic fabrication processes for lightweight multi-nodal structural components

The research presented in this chapter describes the novel robotic fabrication strategies for multi-nodal structural components made from lightweight fiber composite materials. The paper contextualizes the research within a larger area of composite manufacturing in architecture and focuses on the developed methodologies for adaptive, material-efficient production. This research builds on coreless filament winding processes that eliminate the need for large surface molds and wasted materials for composite production. This process allows for large geometrically differentiated structural building components to be easily produced adaptively for architectural applications. The research tests the production of complex components for a vertical lattice structural system. The multi-nodal structural components enable continuous material and fiber orientations across the intersections of the lattice while simplifying connections. Key improvements presented in this paper included the robotic assembly process for the reconfigurable winding frames that reduce assembly times and increase accuracy, computational techniques for developing winding syntax, and physical simulation of material orientations for robotic path planning. This is followed by a conclusion and outlook to discuss the tested results on a full-scale demonstrator and the future design potentials.

Modeling and Identification of an Industrial Robot with a Selective Modal Approach

The stiffness properties of industrial robots are very important for many industrial applications, such as automatic robotic assembly and material removal processes (e.g., machining and deburring). On the one hand, in robotic assembly, joint compliance can be useful for compensating dimensional errors in the parts to be assembled; on the other hand, in material removal processes, a high Cartesian stiffness of the end-effector is required. Moreover, low frequency chatter vibrations can be induced when low-stiffness robots are used, with an impairment in the quality of the machined surface. In this paper, a compliant joint dynamic model of an industrial robot has been developed, in which joint stiffness has been experimentally identified using a modal approach. First, a novel method to select the test configurations has been developed, so that in each configuration the mode of vibration that chiefly involves only one joint is excited. Then, experimental tests are carried out in the selected configurations in order to identify joint stiffness. Finally, the developed dynamic model of the robot is used to predict the variation of the natural frequencies in the workspace.

Mathematical model of a robotized assembly in the presence of vibrations and gripper rotation

The assembly method using the effect of rotational motion and vibration is considered. The presence of rotation allows to signifi cantly reducing the friction force in connection, which prevents the assembly process. The effect is achieved due to using the rotation of robot gripper and the vibrating device. A mathematical dynamics model of the robotic assembly process is presented

Motion planning of skillful motions in assembly process through human demonstration

ABSTRACT Skillful motions in the actual assembly process are challenging for the robot to generate with conventional motion planning approaches because some states during the human assembly can be too skillful to realize automatically due to the narrow passage. To deal with this problem, this paper develops a motion planning method using the human demonstration, which can be applied to complete skillful motions in the robotic assembly process. To demonstrate conveniently without redundant third-party devices, we attach augmented reality (AR) markers to the manipulated object to track and capture its poses during the human demonstration. To overcome the problem brought by the coarse resolution of the vision system, we extract the most important key poses from the demonstration data and employ them as clues to execute motion planning to suit the target precise task. As for the selection of key poses, two policies are compared, where the first and the second derivative of the main changing parameter of every key pose serve as criteria to determine the priority of utilizing key poses. Besides, a solution to deal with colliding key poses is also proposed. The effectiveness of the presented method is verified through some simulation examples and actual robot experiments.

An integrated review of automation and robotic technologies for structural prefabrication and construction

AbstractBuilding construction has developed from the use of primitive tools to that of machinery, with a tendency toward automation. Automation of processes and robotics can improve efficiency, accuracy and safety in construction. On the other hand, structural prefabrication for construction is increasingly being adopted worldwide to enhance productivity and to alleviate the environmental impact of conventional construction processes. The combination and application of automation and prefabrication technologies may therefore introduce new developments to the construction industry. This paper provides a comprehensive review of the use of automation technology for structural prefabrication and construction, including recent developments, challenges and future trends. Five stages following the sequence of construction are proposed: design, construction management, robotic manufacturing, autonomous transportation and automatic structural assembly. The paper concludes that the widespread use of automation technology is preferable to structural prefabrication for construction, and that the design for robotic construction introduced through connection innovations may be beneficial as a means of avoiding complex operations and thus improving the efficiency of robotic assembly processes.

Towards a next-generation production system for industrial robots: A CPS-based hybrid architecture for smart assembly shop floors with closed-loop dynamic cyber physical interactions

Given the multiple varieties and small batches, the production of industrial robots faces the ongoing challenges of flexibility, self-organization, self-configuration, and other “smart” requirements. Recently, cyber physical systems have provided a promising solution for the requirements mentioned above. Despite recent progress, some critical issues have not been fully addressed at the shop floor level, including dynamic reorganization and reconfiguration, ubiquitous networking, and time constrained computing. Toward the next generation production system for industrial robots, this study proposed a hybrid architecture for smart assembly shop floors with closed-loop dynamic cyber physical interactions. Aiming for dynamic reorganization and reconfiguration, the study also proposed modularized smart assembly units for the deployment of physical assembly processes. Enabling technologies, such as multiagent system (MAS), self-organized wireless sensor actuator networks, and edge computing, were discussed and then integrated into the proposed architecture. Furthermore, a multijoint robot assembly process was selected as a target scenario. Thus, an MAS was developed to simulate the coordination and negotiation mechanisms for the proposed architecture on the basis of the Java Agent Development Framework platform.

Research of the Effect of Rotation and Low-Frequency Vibration on the Robotic Assembly Process

Research of the Effect of Rotation and Low-Frequency Vibration on the Robotic Assembly Process

Support Vector Regression for Optimal Robotic Force Control Assembly

Abstract Advanced industrial robotic assembly requires the process parameters to be tuned to achieve high efficiency: short assembly cycle (AC) time and high first-time throughput (FTT) rate. This task is usually undertaken offline because of the difficulties in real-time modeling and the lack of efficient algorithms. This paper proposes a support vector regression (SVR)-enabled method to optimize the assembly process parameters without interrupting the normal production process. To reduce the risk of obtaining a local minimum, we consider the trade-off between exploration and exploitation and propose an adaptive optimization process to balance the production processes and the optimization outcome. The proposed methods have been verified using a typical peg-in-hole robotic assembly process, and the results are compared with design of experiment (DOE) methods and genetic algorithm (GA) method in terms of efficiency and accuracy. The experimental results show that our methods are able to maintain the high FTT rate when it drops below 99%, shorten the average AC time by 3.4%, and reduce the number of assembly trials to find the optimized process parameters by 99.6%.

Bridging the Gap between Automated Manufacturing of Fuel Cell Components and Robotic Assembly of Fuel Cell Stacks

Recently demonstrated robotic assembling technologies for fuel cell stacks used fuel cell components manually pre-arranged in stacks (presenters). Identifying the original orientation of fuel cell components and loading them in presenters for a subsequent automated assembly process is a difficult, repetitive work cycle which if done manually, deceives the advantages offered by either the automated fabrication technologies for fuel cell components or by the robotic assembly processes. We present for the first time a robotic technology which enables the integration of automated fabrication processes for fuel cell components with a robotic assembly process of fuel cell stacks into a fully automated fuel cell manufacturing line. This task uses a Yaskawa Motoman SDA5F dual arm robot with integrated machine vision system. The process is used to identify and grasp randomly placed, slightly asymmetric fuel cell components, to reorient them all in the same position and stack them in presenters in preparation for a subsequent robotic assembly process. The process was demonstrated as part of a larger endeavor of bringing to readiness advanced manufacturing technologies for alternative energy systems, and responds the high priority needs identified by the U.S. Department of Energy for fuel cells manufacturing research and development.