Off-line Programming Research Articles

Automatic robot path integration using three-dimensional vision and offline programming

In manufacturing industries, offline programming (OLP) platforms provide an independent methodology for robot integration using 3D model simulation away from the actual robot cell and production process, reducing integration time and costs. However, traditional OLP platforms still require prior knowledge of the workpiece position in a predefined environment, which requires complex human operations and specific-purpose designs, highly reducing the autonomy of the systems. The presented approach proposes to overcome these problems by defining a novel automated offline programming system (AOLP), which integrates a flexible and intuitive OLP platform with a state-of-the-art autonomous object pose estimation method, to achieve an environment and model independent platform for automatic robotic manufacturing. The autonomous recognition capabilities of the three-dimensional vision system provide the relative position of the workpiece model in the OLP platform, with robustness against clutter, illumination, and object material. After that, the user-friendly OLP platform allows an efficient and automatic path generation, simulation, robot code generation, and robot execution. The proposed system precision and robustness are analyzed and validated in a real-world environment on four different sets of experiment. Finally, the proposed system’s features are discussed and compared with other available solutions for practical industrial manufacturing, showing the advantages of the proposed approach. Overall, despite sensor resolution limitations, the proposed system shows a remarkable precision and promising direction towards highly efficient and productive manufacturing solutions.

A Novel 3-D Path Extraction Method for Arc Welding Robot Based on Stereo Structured Light Sensor

With the rapid development of computer vision and industrial technology, the requirements of the intelligent welding robots are increasing in the real industrial production. The traditional teaching-playback mode and the off-line programming mode cannot meet the automation demand and self-adaptive ability of welding robots. In order to improve the efficiency of welding robots, this paper proposes a novel 3-D path extraction method of weld seams based on a stereo-structured light sensor. Faced with the low efficiency of the line-structured light and the poor robustness of passive vision, the seam extraction based on a point cloud processing algorithm is proposed which could well adapt to the weld seams with different types and different groove sizes. Meanwhile, the position information and pose information of weld seam are established to serve 3-D path teaching of a welding robot. The experimental results show that the maximum path extraction error of V-type butt joint is less than 0.7 mm. The proposed scheme could well serve for the 3-D path teaching task before welding.

A Novel Mesh Following Technique Based on a Non-Approximant Surface Reconstruction for Industrial Robotic Path Generation

Nowadays, industrial robot applications are required to customize the manufacturing of diverse products to reduce both downtime and standoff variability. The two methods for robot programming are regularly implemented to carry out that goal. The first one, online programming, requires a specialized operator to guide the robot through desired poses, and the quality of the result is directly limited by his skill level. On the other side, off-line programming uses software packaging to simulate robot applications before their implementation. It reduces downtime with respect to online programming but requires additional calibration steps. In this paper, a novel procedure is presented to obtain accurate surface approximations by combining linear interpolations generated during online programming with a triangulated surface reconstruction of a workpiece surface representation. The method uses a point cloud instead of a predefined mesh to reduce the standoff variability between the robotic tool center point and the surface. Additionally, a technique based on a penalized least squares method was implemented to smooth the trajectory, including position and orientation. The proposed methodology was validated with three well-known case studies involving real trajectories, with simulations in MATLAB and RobotStudio, as well as by experimentation with an industrial ABB robot. The quality of the results demonstrates a great efficiency of this method for path generation based on surface reconstruction.

An application to simulate and control industrial robot in virtual reality environment integrated with IR stereo camera sensor

The main goal of this research is to test for potential ways to control KUKA KR10 industrial arm manipulator using Virtual Reality technology and check for the advantages of applying this control methods. The final version of this application aims to achieve this goal by establishing an interaction between the user and the manipulator inside a virtual environment developed using the game engine Unity3D and the HTC VIVE Pro headset for the virtual visualization. By applying this control method, the user does not have to operate on site and instead he can work remotely. In addition to the ability to use off-line programming of the manipulator. The application is designed to simplify the controlling ways by displaying a complete virtual environment where the tridimensional model of the robotic arm can be visualized and programmed according to the real manipulator’s parameters and specifications. All the movements and parameters in the virtual environment can be synchronized with the real robot in an on-line or off-line path planning depending on the application or the task. The system integrates a set of virtual reality controllers and Leapmotion sensor as options to allow the user to control and see the robot and its parameters in the virtual environment. As a result of this research, the manipulator moves on the planned trajectory in a smooth way after applying some filtering techniques without losing its accuracy.

Off-line programming of an industrial robot in a virtual reality environment

Industrial robots need to be programmed quickly in order to be practically deployable in the production of small batches. In programming by teaching or demonstration, when most of the program’s content involves handling tasks, gesture recognition or other multimodal interfaces may be exploited. However, when the main task concerns manufacturing processing, typically tracing an edge in seam welding, deburring or cutting, then positioning and orienting the tool to considerable accuracy are required. This can only be achieved, if suitable tracking sensors are used. The current work employs a 6 degree-of-freedom magnetic sensor, but any other equivalent sensor could be used, too. The sensor is attached to a suitable hand-held teaching tool that is constructed in accordance with the real end-effector tool, enabling continuous tracking of its position and orientation interactively. A virtual reality platform records this stream of data in real time, making it possible to exploit it primarily in off-line programming of the robot. In this mode both the robot and the manufacturing cell are virtual, inverse kinematics allowing for calculation of joint coordinates from end-effector coordinates. Collision and clearance checks are also straightforwardly implemented. An edge-tracing application in 3D space was programmed following this paradigm. The resulting curves of the tool tip in the virtual and the real environment were close enough when compared by using photogrammetry. If required, the VR environment also allows for remote on-line programming, without any major modifications.

Autonomous Robot-Guided Inspection System Based on Offline Programming and RGB-D Model.

Automatic optical inspection (AOI) is a control process for precisely evaluating the completeness and quality of manufactured products with the help of visual information. Automatic optical inspection systems include cameras, light sources, and objects; AOI requires expert operators and time-consuming setup processes. In this study, a novel autonomous industrial robot-guided inspection system was hypothesized and developed to expedite and ease inspection process development. The developed platform is an intuitive and interactive system that does not require a physical object to test or an industrial robot; this allows nonexpert operators to perform object inspection planning by only using scanned data. The proposed system comprises an offline programming (OLP) platform and three-dimensional/two-dimensional (3D/2D) vision module. A robot program generated from the OLP platform is mapped to an industrial manipulator to scan a 3D point-cloud model of an object by using a laser triangulation sensor. After a reconstructed 3D model is aligned with a computer-aided design model on a common coordinate system, the OLP platform allows users to efficiently fine-tune the required inspection positions on the basis of the rendered images. The arranged inspection positions can be directed to an industrial manipulator on a production line to capture real images by using the corresponding 2D camera/lens setup for AOI tasks. This innovative system can be implemented in smart factories, which are easily manageable from multiple locations. Workers can save scanned data when new inspection positions are included based on cloud data. The present system provides a new direction to cloud-based manufacturing industries and maximizes the flexibility and efficiency of the AOI setup process to increase productivity.

CNC centralized control for digitizing freeform surfaces by means of a conoscopic holography sensor integrated in a machining centre

This paper presents the integration of a conoscopic holography sensor (CH) in a machining centre (MC) by means of a centralized control on the machine's CNC (CNC centralized control). Besides the installation and extrinsic calibration of the sensor, the primary focus is the automation of the freeform digitizing process on the MC itself. To overcome the usual lack of compatibility between the respective interfaces of the CNC machine and the non-contact sensor, a system was developed to centralize the control intelligence on the machine's own CNC, enabling digitizing operations to be performed directly with the execution of an NC subroutine. In addition, three digitizing strategies are proposed: Non-Adaptive, Adaptive and Predictive-Adaptive. These require no planning tools or off-line programming prior to the digitizing process. The effectiveness of the extrinsic calibration method was validated by measuring a certified ballbar, and the integrated measuring system was checked by comparing the metrological results obtained by digitizing a freeform surface with those obtained by a CMM contact probe and with the CAD model used for machining the surface.

Off-line path programming for three-dimensional robotic friction stir welding based on Bézier curves

Purpose Robotic friction stir welding (RFSW) is an innovative process which enables solid-state welding of aluminum parts using robots. A major drawback of this process is that the robot joints undergo elastic deformation during the welding, because of the high forces induced by the process. This leads to tool deviation and incorrect orientation. There is currently no computer-aided manufacturing/computer-aided design (CAD) software for generating off-line paths which integrates robot deflections, and the main purpose of this study is to propose an off-line methodology to plan a path for RFSW with the integration of the deflections. Design/methodology/approach The approach is divided into two steps. The first step consists of extracting position and orientation data from CAD models of the workpieces and adding the deflections calculated with a deflection model to generate a suitable path for performing RFSW. The second step consists of the smooth fitting of the suitable path using Bézier curves. Findings The method is experimentally validated by welding a curved workpiece using a Kuka KR500-2MT robot. A suitable tool position and orientation were calculated to perform this welding, an experimental procedure was set up, a defect-free weld was performed and a high accuracy was achieved in terms of position and orientation. Practical implications This method can help manufacturers to easily perform RFSW for three-dimensional workpieces regardless of the lateral tool deviation, loss of the right orientation and control force stability. Originality/value The originality of this method lies in compensating for robot deflections without using expensive sensors, which is the most commonly used method for compensating for robot deflection. This off-line method can lead to a reduction in programming time in comparison with teach programming method and leads to reduced investment costs in comparison with commercial off-line programming packages.

A High-Speed Seam Extraction Method Based on the Novel Structured-Light Sensor for Arc Welding Robot: A Review

In the modern manufacturing, the teaching-playback mode and the off-line programming mode of the welding robots still play the important roles. However, these modes cannot meet the autonomous and adaptive capabilities of the welding robots. To improve the flexibility of the welding robots, fast and accurate seam extraction is the key link to realize the intelligent welding robots. A fast and accurate seam extraction algorithm based on the novel structured light vision system is proposed in this paper. First, the digital light processing projector is used to construct the multi-function structured light vision sensor in this paper. It could generate different pattern images to adapt different welding tasks. Second, during the current research work about seam extraction, the seam extraction algorithm based on morphological image processing has been widely used and improved. However, these algorithms include much machine vision algorithms and the speed of these algorithms is too slow to meet real-time requirements. Meanwhile, these algorithms are difficult to adapt to different types of weld seam. In order to achieve fast and accurate extraction of various types of weld seams, the target tracking algorithm based on the kernelized correlation filters algorithm is applied into this paper. Experimental results show that the proposed method could well realize fast and accurate seam extraction of various types of weld seams.

The analysis of industrial robot – external axes system movements with the use of virtual off-line programming

Both, positioners as well as robot motion tracks to be integrated with industrial ro-bots as their external axes should fulfil high work requirements. The toughness structureof such systems resulted in high carrying capacity and repeatability of positioning must be compatible with the system kinematic ability to be used in typical technological appli-cation. During such systems design process its functional verification can be done withthe use of virtual off-line programming. The already complemented in PPU ZAP Robotyka in Ostrów Wielkopolski research methodic as well as results of analysis performed of newly developed manipulating machines as external axes of industrial robots.

Processing configuration off-line optimization for functionally redundant robotic drilling tasks

As a key technology of robotic assembly system, off-line programming (OLP) is an effective way to improve processing quality and efficiency. Currently, the basic functions of OLP systems, such as trajectory planning, three-dimensional task simulation and collision detection, could not achieve high machining precision and guarantee the quality stability. Thus, robot kinematics and stiffness performance optimization need to be investigated as secondary tasks in the special OLP system, on the basis of redundant kinematics characteristic of a serial robot system with external axis. First, a singularity measurement model of robot configuration is presented under the constraint of joint-limits to achieve the avoidance of singular and joint-limits configurations. Secondly, based on the robot static stiffness model, an axial stiffness identification method has been come up with to evaluate the stiffness performance in the processing direction. Next, with the combination of singularity measurement model and axial stiffness identification method, a redundancy resolution method is put forward to plan and optimize the configuration of robot system with external axis off-line, which keeps robots away from singularity and joint-limits, and meanwhile achieve the optimum stiffness during robotic drilling process. Finally, the validity of this method in improving drilling quality and stability is verified by the application in a robotic drilling system.

Study of inter-operational breaks impact on materials flow in flexible manufacturing system

Present development of advanced technologies in production and logistics, orientation for a customer needs and global, competitive market determines a creation of flexible manufacturing systems. Each FMS consisting of the automated and robotized subsystems of production, assembly, inter-operational transport and storage should be treated as a complete logistics system in which the efficient flow of materials is realized, at every stage of processing. The efficiency of the system is based on possibility of quick, automated retooling and reprogramming for the manufacturing of new products, especially in the production for individual order. Except that, according to modern concepts of enterprise management, one of the factors to improve material flow is to minimize unnecessary inter-operative interruptions. The inter-operational breaks include many factors: handling and transport, waiting for a technological operation and assembly, quality control, unpredictable failures. While technological times are almost impossible to shorten, all issues related with logistics are possible to improve. The inter-operational breaks don’t create added value, they’re only waste. They often remain outside the research sphere or are treated marginally as a loss included in the manufacturing process. The article describes study on an effective method of searching for negative inter-operational breaks in advanced manufacturing processes and eliminating them. Advanced software for off-line programming of machine tools, robots, automated transport and warehouse systems and general-purpose simulation software for production and logistics gives possibility to conduct research on limiting the impact of inter-operational breaks on FMS.

The virtual commissioning technology applied in the design process of a flexible automation system

This paper describes an application of the virtual commissioning technology applied to the design of a robotized manufacturing cell. Virtual commissioning requires the integration of different technologies, such as PLC (programmable logic controller) programming, device communication with OPC (OLE for process control), off-line robot programming, HIL (hardware-in-the-loop), as well as the design of devices and tools using computer-aided design (CAD) applications. Within this application, the virtual commissioning resource evaluates the operation of an assembly line, simulates several processes in a digital environment, tests real equipment and tools and integrates a system that shares the signals of the sensors and actuators with the simulation environment in the computer. The case study described herein compares a conventional design process of a car floor spot welding station to the design approach using virtual commissioning. The robotic welding cell is controlled by a PLC integrated in a simulation environment that uses two industrial robots created in the Process Simulate Robotics application of Siemens Tecnomatix®.

A multi-layer control hierarchy for heavy duty vehicles with off-line dual stage dynamic programming optimization

In this paper, a multi-level, comprehensive control technique for a heavy duty vehicle, capable of reducing fuel consumption while complying with engine constraints on both operating conditions and smoke emissions has been developed. The higher control layer, using road data, engine and vehicle parameters, computes the optimal speed and gear shifting profiles through an off-line, dual step dynamic programming algorithm. Since fuel consumption alone could be potentially decreased by driving at lower speeds and thus increasing travel time, this last aspect is also taken into account in the presented algorithm. The lower control layer, operating in real time, computes suitable powertrain control signals assuring the tracking of both reference speed and gear trajectories, while respecting the constraints imposed on engine operation. After the general description of the optimal control problem aimed at minimizing fuel consumption, an approach for its solution, implemented in the higher control layer, is presented. Afterwards, the lower control layer is described. In conclusion, the effectiveness of the developed control structure and the achievable improvement in terms of fuel consumption in comparison with a traditional fixed-point cruise controller are assessed through simulations in different driving scenarios.

DUSTBUSTER: AN AUTONOMOUS VACUUM CLEANING ROBOT

This paper proposes the development of an autonomous robot which is controlled by sensors and an Android Phone (optional). The implementation of AI concepts in the development of a software application for off-line robot task programming. We can use concept of the designed programming application to power the knowledge base for task accumulation. This work aims at the cleaning a house on its own, without human interference. In the current scenario, the economical versions of iRobot Roomba (currently in the market) cannot develop a map of its own; however, this feature is present in the luxurious versions. As the luxurious versions aren’t affordable, our Dustbuster will prove to be an efficient and economic stopgap solution.

Off-line scan path planning for robotic NDT

This work presents computer-aided scan path generation for robotic non-destructive testing of complex shaped test-pieces. Off-line programmed scan path was used to robotically inspect an aluminium fixed leading edge skin panel of an aircraft wing by means of swept frequency eddy currents method. Eddy currents probe was deployed by means of a six-axis robotic arm KUKA KR5 arc. Reverse engineering of the test-piece was carried out to reconstruct CAD model of its surface. Positioning accuracy of the performed continuous scan was measured with a laser tracker in accordance with ISO 9283:1998 and is reported in the paper. The positional uncertainty of the NDT scan calculated as the standard deviation of the measured path coordinates from the command path coordinates does not exceed 0.5 mm which is rather moderate taking in account uncertainties associated with the off-line robot programming.

Feature-based five-axis path planning method for robotic additive manufacturing

Additive manufacturing has been developed for decades and attracts significant research interests in recent years. Usually, the stereolithography tessellation language format is employed in additive manufacturing to represent the geometric data. However, people gradually realize the inevitable drawbacks of the stereolithography tessellation language file format, such as redundancy, inaccuracy, missing of feature definitions, and lack of integrity. In addition, it is almost impossible to apply the simple polygonal facet representation to the five-axis manufacturing strategy. Hence, there are quite few researches and applications on the five-axis additive manufacturing, in spite of its common applications in the subtractive machining. This article proposes a feature-based five-axis additive manufacturing methodology to enhance and extend the additive manufacturing method. The additive manufacturing features are defined and categorized into two5D_AM_feature and freeform_AM_feature. A feature extraction method is proposed that can automatically recognize the additive manufacturing features from the input model. Specially for the freeform_AM_feature, a five-axis path planning method is proposed and split into three stages: (1) offset the reference surface, (2) spatially slice the freeform layers, and (3) generate the toolpaths for each freeform layer. Real additive manufacturing five-axis toolpaths can be obtained using the proposed algorithm that performs as a secondary developed plug-in in the CATIA® environment. A robotic additive manufacturing system is constructed for the implementation of the five-axis additive manufacturing tasks, which are generated by the proposed algorithms and post-processed after simulation and off-line programming. Some examples are printed to validate the feasibility and efficiency of the proposed method.

CAD-based robot path planning and simulation using OPEN CASCADE

In manufacturing industries, human operators are required in many manufacturing processes, which is time-consuming and not cost-effective. In the present approach, a CAD-based off-line programming (OLP) platform is developed based on OPEN CASCADE (OCC) open source libraries. The developed platform works as a human-robot interface (HRI), offers friendly interaction in an intuitive way, so that in few minutes with basic information, any user can generate a robot path from a CAD model and visualize the simulation graphically. The platform provides important steps such as loading CAD models to define a task, extracting CAD information to generate a path, checking the reachability of the manipulator, and simulation to check and prevent the possible collision before generating a robot program. To evaluate the industrial usability of the proposed platform, a robot program for gluing application is generated from simulation and mapped to a real 6-Degree Of Freedom industrial manipulator.

Survey on Human-Robot Interaction for Robot Programming in Industrial Applications

The recent trends in modern industry highlight an increasing use of robots for a wide range of applications, which span from established manufacturing operations to novel tasks characterized by a close collaboration with the operators. Although human-robot collaboration allows to relieve operators of exhausting works, an effective collaboration requires a straightforward interaction to foster the use of robot assistants. This paper provides a comprehensive survey on human-robot interaction approaches and related interfaces addressed to robot programming. An overview of on-line and off-line robot programming techniques is first presented. Then, novel intuitive interaction means, such as those based on multi-modal interaction, virtual and augmented reality, are considered. The paper aims at pointing out that collaborative robotics can effectively reduce operator’s physical workload if easy to use interfaces for robot programming are provided.

Lateral stability control of vehicles based on the calculation and allocation of component forces

A vehicle lateral stability control method for real-time calculation and dynamic allocation of the longitudinal force and yaw moment of vehicle tyres is proposed. The achievable range of the longitudinal force and yaw moment of the tyre are calculated in real time through off-line numerical optimisation and nonlinear programming. The calculated values are then adjusted to within the available range and allocated dynamically. A controller for the slip rate and front wheel slip angle is used to ensure that the tyre friction can trace each component force. The proposed method avoids estimating the lateral force of vehicle rear wheels while ensuring accuracy. The results of simulations and driver-in-loop tests demonstrated that the proposed method can improve the track-holding ability while reducing the influence of a road surface with a low adhesion coefficient on vehicle stability. The method ensures high and dynamic tracking performance and lateral stability.