A collision-free path planning method is proposed based on learning from demonstration (LfD) to address the challenges of cumbersome manual teaching operations caused by complex action of yarn storage, variable mechanism positions, and limited workspace in preform weaving. First, by utilizing extreme learning machines (ELM) to autonomously learn the teaching data of yarn storage, the mapping relationship between the starting and ending points and the teaching path points is constructed to obtain the imitation path with similar storage actions under the starting and ending points of the new task. Second, an improved rapidly expanding random trees (IRRT) method with adaptive direction and step size is proposed to expand path points with high quality. Finally, taking the spatical guidance point of imitation path as the target direction of IRRT, the expansion direction is biased toward the imitation path to obtain a collision-free path that meets the action yarn storage. The results of different yarn storage examples show that the ELM-IRRT method can plan the yarn storage path within 2s–5s when the position of the mechanism changes in narrow spaces, avoiding tedious manual operations that program the robot movements, which is feasible and effective.

The remote management of equipment is part of the functionalities granted by the design principles of Industry 4.0. However, some critical operations are managed by operators, machine setup and initialization serve as a significant illustration. Since the initialization is a repetitive task, industrial robots with a smart vision system can undertake these duties, enhancing the autonomy and flexibility of the manufacturing process. The smart vision system is considered essential for the implementation of several characteristics of Industry 4.0. This paper introduces a novel solution for controlling manufacturing machines using an embedded camera on the robot. This implementation requires the development of an interactive interface, designed in accordance with the supervision system known as Manufacturing Execution System. The framework is implemented inside a manufacturing cell, demonstrating a quick response time and an improvement between the cameras.

Selective compliance articulated robot arms (SCARA) robotic manipulators find wide use in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-degrees of freedom (DOF) SCARA robotic manipulator. The dynamic model of the SCARA robot undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system, a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains, an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control method is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, it is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs and (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators. The nonlinear optimal controller for the 4-DOF SCARA robot is finally compared against a flatness-based controller implemented in successive loops.

It is well known that the use of multi-rate control techniques have improved the performance of many systems in general, and robotic systems, in particular. The main contribution of this paper is the generalization of the Reference Filtering control strategy from a dual-rate point of view, improving its inherent properties by overcoming the problem of sensor latency. In the paper, we discuss and analyze the improvements introduced by the novel dual-rate reference filtering control strategy in terms of convergence time, reachability and robustness. More specifically, we discuss the capability to solve positioning tasks, when hardware limitations are present with large sampling rates. In addition, a comparison is made between the single-rate and the proposed dual-rate control strategies to prove the advantages of the latter approach. A complete set-up has been prepared for validation, including a six degree of freedom (DOF) industrial manipulator, a smart camera and embedded hardware used as a high level controller.

This paper presents a persistent method for the identification problem of open-chained robotic systems. Based on the Projection Equation, a new, direct method to collect the dynamic and friction parameters in linear form is worked out. However, in this form, linear dependencies in the parameters occur and they are canceled out with the help of the QR algorithm. The obtained linear independent parameters are the base parameters of the system. To ensure a good excitation, the identification is improved by using optimized trajectories defined by Fourier-series, taking also physical constraints into account. The evaluation of the dynamic robot parameters is realized with a least squares error optimization. Furthermore, the result strongly depends on a special choice of weighting matrices for the error. Experimental results for a seven-axes robotic system (standard six-axes industrial manipulator mounted on a linear axis) are presented in detail. Additionally, the influence of temperature effects to base parameter changes is discussed.

As a fatigable part of industrial products, cable is a valuable research topic to predict the product lifetime. Since the cable fatigue is related to the bending radius in motion, this paper presents a cable motion capture and bending radius calculation method based on optical tracking system. In particular, a marker sorting algorithm is developed for further spline interpolation in cable motion tracking. The cable bending radius calculation precision is analysed as well. The Results show that the proposed method can successfully track cable motion with an acceptable error for cable lifetime prediction.

The absolute accuracy of a small industrial robot is improved using a 30-parameter calibration model. The error model takes into account a full kinematic calibration and five compliance parameters related to the stiffness in joints 2, 3, 4, 5, and 6. The linearization of the Jacobian is performed to iteratively find the modeled error parameters. Two coordinate measurement systems are used independently: a laser tracker and an optical CMM. An optimized end-effector is developed specifically for each measurement system. The robot is calibrated using fewer than 50 configurations and the calibration efficiency validated in 1000 configurations using either the laser tracker or the optical CMM. A telescopic ballbar is also used for validation. The results show that the optical CMM yields slightly better results, even when used with the simple triangular plate end-effector that was developed mainly for the laser tracker.

This paper reports on a continuation of research activities at the Loughborough University of Technology (LUT) which are aimed at evolving second generation pneumatic drives and provides an introduction to various aspects which must be considered in the design and use of industrial pneumatic servo-driven robots. The paper illustrates how a new generation of fast and accurate pneumatic servo drives, demonstrating excellent performance/cost characteristics, will become available and will rival electric and hydraulic counterparts in many areas of industrial control.

For a robotic workcell with multiple robots, several interconnection methods are presented in terms of a processor-based architecture. The concept of the multiple processor system (MPS) or multiple computer system (MCS) is used to formulate and analyze the multi-robot interconnection system (MRIS). The MRIS is modelled as a queueing network, and mathematical analysis is done on the basis of modelling. Performance evaluation is achieved for the MRIS through the mean value analysis with the response time and the probability of service failure under different workloads. The results together with some comments suggest a useful guideline for a selecting an appropriate interconnection method for the MRIS subject to the system environment and application.

A new method of optimal cost trajectory planning based on a graph searching algorithm is presented. Various heuristic functions which play the key role in the construction of effective algorithms for solving such problems are proposed. Some numerical examples are given based on the kinematic and dynamic models of a IRb-6 ASEA robot. This method rooted in AI has less computational complexity than a dynamical programming method applying to the same optimal-cost trajectory planning problem.

This paper presents a novel approach to designing and manufacturing of a universal gripper to be used with industrial robots in flexible assembly systems. Important issues that impact greatly on the efficiency of the gripper are also discussed in this paper. Such issues include the degree of compliance allowed by the robotic wrist and the way these grippers are actuated. The gripper has been proven to be extremely flexible and low in cost.

When fitting contacts to connectors, the flexibility of the wires and the irregularity of the contact shapes have proved to be the greatest obstacles in developing automation. Within the framework of the present project, two methods for fitting irregular and flexible parts have been developed, both using industrial robots supported by vibrating tools. For theoretical analysis the irregular, flexible part is mathematically idealized. The tests are carried out with these idealized parts and crimp contacts. These tests proved that the vibration method is suitable for fitting irregular, flexible parts.

Operational space control of industrial robots is addressed in this document. We analyze a two-loop hierarchical control with the resolved motion rate controller (RMRC) as outer loop and the joint velocity PI controller as inner loop; the latter is the typical velocity controller used in industrial robots. We prove, by the first time, that these simple controllers make the solutions of the closed-loop system uniformly ultimately bounded. Additionally, we give some simple guidelines for the selection of the control gains so as to ensure an explicit bound of the tracking error.

In this paper, we propose a generic method to model the dynamic intercept and manipulation capability of vision-based industrial robot systems. In order to verify the method, we present experiments using our industrial workcell prototype to dynamically intercept and manipulate semi-randomly moving objects.

A stochastic ellipsoid modelling of repeatability is proposed for industrial manipulator robots. The covariance matrix of angular position is determined introducing the jump process, which reveals to be a first and second order stationary Gaussian process.

From this accurate covariance matrix, the stochastic ellipsoid theory gives the density of position in the workspace around the mean position. Hence the pose repeatability index can be computed in different locations. Computed and experimental repeatability are compared. Experimental repeatability variability is studied. A new “intrinsic repeatability index” is proposed. In conclusion, the modelling reflects well the location and load influence on the repeatability.

To increase operator safety in robotic working cells, a capacitive sensor for the detection of humans has been developed. The sensor consists of two electrically conducting planes, insulated electrically from the ambient. When the dielectric or conductive conditions in the space between the planes are altered, e.g. a person enters, the sensor will indicate the presence of the person. The strength of the electric field caused by the sensor is kept low by lock-in amplifier technique. In the article the basic detection principle, the sensor electronics and the sensor signal handling are described and some practical experiments are presented.

For securing and increasing the quality of various material processing technologies a flexible sensor data integration is indispensable. Hence, a powerful and configurable sensor-robot-system was designed and implemented, integrating sensor data into industrial robot controls within the interpolation or the position control clock rate. Different controllers were designed and the system responses of the control loops were simulated and optimized by an efficient control design tool. Experimental results on the achievable path accuracy are presented. Finally, some application for the developed sensor control loops are introduced.

Industrial robots have a high positioning accuracy and stiffness but their work spaces are limited because their bases are fixed to the ground. To enlarge the work spaces, this paper proposes a novel mechanism, a wire suspended manipulator with three degrees of freedom. First, the kinematics of the mechanism is derived from both force and geometric constraints. Second, the volume of the work space is numerically calculated. After the evaluation of manipulability of the wire suspended system, guidelines for designing parameters are studied.

Common geared industrial robots call for force control methods with special properties such as good rejection of frictional disturbances, smoothness of corrective motions, and more. A new method is presented which meets these requirements and provides a high control bandwidth. In the manner of hybrid control, directions of a task frame can be selected to be force, impedance or position controlled. A joint-based inner position loop and a superimposed predictive force controller are used. Practical results include data from a robotic grinding facility. Here, the controller proved robustness and good performance under rough conditions.