Conventional Industrial Manipulator Research Articles

Tolerance dataset: mating process of plug-in cable connectors for wire harness assembly tasks

In this research, we studied the mating tolerance of various plug-in cable connectors and provide a mating tolerance dataset of 70 different connectors. This dataset will be highly advantageous to industries for wire harness assembly tasks using robots. Understanding the mating tolerance is crucial for automating the mating process because it is closely related to the control specifications of a robotic manipulator. Our system uses a 2-finger Robotiq adaptive gripper attached to a 6 degree-of-freedom industrial robot (ABB Robotics) to test the mating process of wire harness assembly tasks. In addition, we use 70 types of wire harness connectors with different numbers of pins widths, lengths, and thicknesses, and various shapes, to test the mating tolerance. The results indicate that the connector mating tolerance of our dataset is more generous than the repeatability of conventional industrial manipulators, and further demonstrate the suitability of the position control methods to wire harness assembly tasks.

Light automation for aircraft fuselage assembly

ABSTRACTThe ever-growing need to improve manufacturing processes has led recently to an increase in the number of automation solutions used to assemble aircraft structural elements. A process of interest to this industry is the alignment of fuselage sections, which is currently done either manually or by complex, expensive automated systems. The manual method introduces a significant production delay and most automated systems have limited flexibility. This article presents an integration solution implemented in an alternative low-cost, high-flexibility alignment robotic cell. The performance of an optical coordinate measuring machine (CMM) as feedback source for the adaptive control of a conventional industrial manipulator is assessed. Laser interferometry readings are used as reference. The contribution of the work lies in the execution of experiments based on the EN ISO 9283 standard (Manipulating industrial robots - performance criteria and related test methods) to determine the adequacy of the commercial off-the-shelf system to the tolerances and requirements of the fuselage alignment process at hand. The optimal configuration of the integrated system attained the nominal alignment position with an average accuracy of 0.16mm and $0.004^\circ$ , partially meeting the required tolerances, and the obtained values are nearly 16x better compared to a baseline, open-loop manipulator. These results serve as reference for the aerospace industry in the development of the next generation of tools and automated assembly processes.

Model-based sensorless robot collision detection under model uncertainties with a fast dynamics identification

This article presents a novel model-based sensorless collision detection scheme for human–robot interaction. In order to recognize external impacts exerted on the manipulator with sensitivity and robustness without additional exteroceptive sensors, the method based on torque residual, which is the difference between nominal and actual torque, is adopted using only motor-side information. In contrast to classic dynamics identification procedure which requires complicated symbolic derivation, a sequential dynamics identification was proposed by decomposing robot dynamics into gravity and friction item, which is simple in symbolic expression and easy to identify with least squares method, and the remaining structure-complex torque effect. Subsequently, the remaining torque effect was reformulated to overcome the structural complexity of original expression and experimentally recovered using a machine learning approach named Lasso while keeping the involving candidates number reduced to a certain degree. Moreover, a state-dependent dynamic threshold was developed to handle the abnormal peaks in residual due to model uncertainties. The effectiveness of the proposed method was experimentally validated on a conventional industrial manipulator, which illustrates the feasibility and simplicity of the collision detection method.

Anthropomorphic Low-Inertia High-Stiffness Manipulator for High-Speed Safe Interaction

In this paper, a manipulator is proposed for safe human–robot interaction at high speed. The manipulator has both low mass and inertia and high stiffness and strength. It is basically a cable-driven manipulator; nevertheless, by using a unique lightweight tension-amplification mechanism, the manipulator retains high stiffness and strength. The joint stiffness, which is strongly related to the motion control performance, is amplified by the quadratic order. Both 1-degree of freedom (DOF) and 3-DOF joint mechanisms using the tension-amplification mechanism are presented and combined to develop a 7-DOF anthropomorphic manipulator named LIMS. The mass and inertia beyond the shoulder were 2.24 kg and 0.599 kg·m2, respectively, which are lower than those of a human. The stiffness of the developed elbow joint was 1410 N·m/rad, which is approximately seven times higher than that of a human. Considering the ratio of stiffness to inertia, the manipulator is expected to show a control performance that is comparable to those of conventional industrial manipulators. Comprehensive experiments, including joint stiffness tests and high-speed interaction tests, were conducted to verify the feasibility of the developed manipulator.

Development of a Prototype Robotic System for Radiosurgery with Upper Hemispherical Workspace.

This paper introduces a specialized robotic system under development for radiosurgery using a small-sized linear accelerator. The robotic system is a 5-DOF manipulator that can be installed above a patient to make an upper hemispherical workspace centered in a target point. In order to determine the optimal lengths of the link, we consider the requirements for the workspace of a linear accelerator for radiosurgery. A more suitable kinematic structure than conventional industrial manipulators is proposed, and the kinematic analysis is also provided. A graphic simulator is implemented and used for dynamic analysis. Based on those results, a prototype manipulator and its control system are under development.

Identification of dynamic parameters and feedforward control for a conventional industrial manipulator

Dynamic compensation control algorithms can improve the performance of conventional industrial manipulators if an accurate dynamic model is available. Usually, the structure of the dynamic model is known but the actual values of the dynamic parameters are either unknown or not accurately known. It is thus required to perform an identification of these parameter using available algorithms. In this paper, feedforward model-based control is experimented on a conventional industrial robot, the SMART-3 6.12R by COMAU, based on a dynamic parameter identification. Despite the fact that the conditions for the experiments are far from those provided by research set-ups, the obtained results have confirmed that it is worth using feedforward compensation control, either in a complete or in a partial form, even on an industrial set-up.

Energy-based identification of dynamic parameters for a conventional industrial manipulator

It is well-known that an accurate knowledge of the dynamic model of a manipulator can significantly improve the trajectory tracking capabilities by resorting to model-based control algorithms. While the structure of the dynamic model can be simply obtained by considering rigid- body motion laws, the actual values of the dynamic parameters (inertias, masses, centers of gravity) are either unknown or not accurately known. Algorithms have been proposed which estimate these parameters from measurements taken during manipulator motion. This paper deals with identification of dynamic parameters for a conventional industrial manipulator, performed via an algorithm based on the energy theorem for mechanical structures. The purpose here is to show that such an identification leads to good results even with all the limitations set by the conventional industrial set-up. Also, the results are compared with those obtained with identification algorithms based on the dynamic model of the manipulator.

Identification of Dynamic Parameters for a Conventional Industrial Manipulator

Dynamic compensation control algorithms can improve the performance of conventional industrial manipulators if an accurate dynamic model is available. It is true that usually the structure of the dynamic model is known but the actual values of the dynamic parameters are either unknown or not accurately known. It is thus required to perform an identification of these parameters based on measurements made on the manipulator during assigned motion. This paper describes the identification of the dynamic parameters for a conventional industrial robot. Algorithms are available to perform the identification when ideal conditions are present. Despite of the fact that the conditions for the experiments are far from those provided by research set-ups, the obtained results have confirmed that identification of dynamic parameters can be effectively performed even on an industrial set-up.