Search results

As competition grows in the robot field and as more sophisticated applications emerge, it has become necessary to accurately predict robot cycle time. Especially in the area of robot assembly applications, it is necessary to estimate times to balance multi‐arm systems and to economically compare robot assembly systems to alternate methods. Using the Unimate 6000 robot system as a model and manual time methods as a guide, a robot time and motion method is developed. Three time estimating methods are discussed starting with a simple, approximate one and finishing with a detailed, accurate one. All three methods can be adapted for use with applications other than assembly and will be further evaluated in the future with other robot systems.

This paper aims to present an adaptive robust sliding mode tracking controller for a 6 degree-of-freedom industrial assembly robot with parametric uncertainties and external disturbances. The controller is used to achieve both stringent trajectory tracking, accurate parameter estimations and robustness against external disturbances.

The controller is designed based on the combination of sliding mode control, adaptive and robust controls and hence has good adaptation and robustness abilities to parametric variations and uncertainties. The unknown parameter estimates are updated online based on a discontinuous projection adaptation law. The robotic dynamics is first formulated in both joint spaces and workspace of the robot’s end-effector. Then, the design procedure of the adaptive robust sliding mode tracking controller and the parameter update law is detailed.

Comparative tests are also conducted to verify the effectiveness of the proposed controller, which show that the proposed controller achieves significantly better dynamic trajectory tracking performances as compared with conventional proportional derivative controller and sliding mode controller under the same conditions.

This is a new innovation for industrial assembly robot to improve assembly automation.

The purpose of this study has been to evaluate the technology of autonomous mobile manipulation in a real world industrial manufacturing environment. The objective has been to obtain experience in the integration with existing equipment and determine key challenges in maturing the technology to a level of readiness suitable for industry. Despite much research within the topic of industrial mobile manipulation, the technology has not yet found its way to the industry. To mature the technology to a level of readiness suitable for industry real-world experience is crucial. This paper reports from such a real-world industrial experiment with two mobile manipulators.

In the experiment, autonomous industrial mobile manipulators are integrated into the actual manufacturing environment of the pump manufacturer Grundfos. The two robots together solve the task of producing rotors; a task constituted by several sub-tasks ranging from logistics to complex assembly. With a total duration of 10 days, the experiment includes workspace adaptation, safety regulations, rapid robot instruction and running production.

With a setup time of less than one day, it was possible to program both robots to perform the production scenario in collaboration. Despite the success, the experiment clearly demonstrated several topics in need of further research before the technology can be made available to the industry: robustness and cycle time, safety investigations and possibly standardization, and robot and workstation re-configurability.

Despite the attention of research around the world, the topic of industrial mobile manipulation has only seen a limited number of real-world integrations. This work reports from a comprehensive integration into a real-world running production and thus reports on the key challenges identified from this integration.

More than half of the industrial robots throughout the world are used in the automobile industry. The following deals with the most important application so far, spot welding in car‐body construction, and one with a promising future, namely, assembly.

Sensors considerably increase the new applications of industrial robots. Assembly utilizations exist in the fields of part loading, the supervision of the gripping and part mating process, and tolerance compensation as well as the testing and checking of the assembly job. A couple of years ago sensor applications in assembly with industrial robots existed only in research laboratories and development institutions. Nowadays, industry cannot refuse to use them. Improvements on sensorics such as faster data processing and lower costs, as well as higher accuracies in measuring and a more favourable rate to price and efficiency, allow sensor guided robots in assembly with technical and economical significance. Assembly systems with industrial robots demand high flexibility, process supervision and control to increase output quality, and require manifold sensor utilizations.

The purpose of the following work was to work out the dependency to allow for the determination of the repeatability positioning error value of the robot at any given point in its workspace, without the necessity of conducting time-consuming measurements while routing a precise surface of repeatability positioning.

The presented dependency permits for the possibility to determine, even at the planning phase, the optimal connection point in the workspace, ensuring the best parameters for the process of machine assembly, without needless overestimation of precision of the utilized equipment. To solve the task the sequential quadratic programming (SQP) method implemented in the MATLAB(R) environment was used. To verify the hypothesis of the compatibility of the empirical distribution with the hypothetical distribution of the robot’s positioning error, the Kolmogorov test was used.

In this paper, it has been demonstrated theoretically and experimentally that the industrial robot accuracy can vary over a very wide range in the workspace. This provides an additional opportunity to increase reliability of the assembly process through the appropriate choice of the point of parts joining. The methodology presented here allows the designer of assembly workstations to rapidly estimate the repeatability of robot positioning and to allocate at the design stage of assembly process the optimal position in the robot workspace to ensure the required precision, without unnecessarily high accuracy of equipment used and, therefore, without inflated costs.

An alternative solution to the stated problem can be the proposed method for determining the robot’s positioning errors, requiring a much smaller amount of measurements to be taken that would be necessary to determine the parameters of the random variable errors of the joint coordinates of the robot and for their verification by the repeatability of positioning in randomly selected points in the workspace. Additionally discussed in the study, the methodology of identifying connection place was designed for typical combinations of machine parts, most frequently encountered in assembly process and was taken into account, typical limitations occurring in actual manufacturing conditions.

The role of microcomputers and their applications in industrial robotics is illustrated. The special case of an intelligent robot is examined in detail. The design of a microcomputer to be used for automatic spatial ordering of objects is presented, and the experimental results are briefly exposed and critically evaluated.

This paper aims to describe the development and testing of a system for the automated assembly of aircraft fuselage panels.

The system described in this paper uses a low‐cost industrial robot and laser stripe sensor to assemble stringers on to a fuselage panel prior to riveting. The method uses a combination of measurement and best fit placement algorithms to optimally locate parts relative to existing features.

The paper demonstrates that with a combination of metrology and mathematical processing standard industrial robots can be used to assemble aero‐structure subassemblies. The paper also demonstrates that the system can work within the tolerances required within the aerospace industry.

The paper introduces techniques for compensating for the inherent distortion that occurs in airframe components during manufacture. This is an enabling technology that will significantly increase the number of possible applications for industrial robots in the assembly of aero‐structures.

In the present era of Industry 4.0, the manufacturing automation is moving toward mass production and mass customization through human–robot collaboration. The purpose of this paper is to describe various human–robot collaborative (HRC) techniques and their applicability for various manufacturing methods along with key challenges.

Numerous recent relevant research literature has been analyzed, and various human–robot interaction methods have been identified, and detailed discussions are made on one- and two-way human–robot collaboration.

The challenges in implementing human–robot collaboration for various manufacturing process and the challenges in one- and two-way collaboration between human and robot are found and discussed.

The authors have attempted to classify the HRC techniques and demonstrated the challenges in different modes.

The purpose of this paper is to propose an on-line iterative compensation method combining with a feed-forward compensation method to enhance the assembly accuracy of a metrology-integrated robot system (MIRS).

By the integration of a six degrees of freedom (6DoF) measurement system (T-Mac), the robot’ movement can be tracked with real-time measurement. With the on-line measured data, the proposed iterative compensation for absolute positioning and the feed-forward compensation for relative linear motion are integrated into the assembly process to improve the assembly accuracy.

It is found that the MIRS exhibits good performance in both accuracy and efficiency with the application of the proposed compensation method. With the proposed assembly process, a component can be automatically aligned to the target in seconds, and the assembly error can be decreased to 0.021 mm for position and 0.008° for orientation on average.

This paper presents a 6DoF MIRS for high-precision assembly. Based on the system, a novel on-line compensation method is proposed to enhance the assembly accuracy. In this paper, the assembly accuracy and the corresponding distance parameter are given by a series of experiments as reference for assembly applications.