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The purpose of this paper is to solve the ground verification and test method for space robot system capturing the target satellite based on visual servoing with time-delay in 3-dimensional space prior to space robot being launched.

To implement the approaching and capturing task, a motion planning method for visual servoing the space manipulator to capture a moving target is presented. This is mainly used to solve the time-delay problem of the visual servoing control system and the motion uncertainty of the target satellite. To verify and test the feasibility and reliability of the method in three-dimensional (3D) operating space, a set of ground hardware-in-the-loop simulation verification systems is developed, which adopts the end-tip kinematics equivalence and dynamics simulation method.

The results of the ground hardware-in-the-loop simulation experiment validate the reliability of the eye-in-hand visual system in the 3D operating space and prove the validity of the visual servoing motion planning method with time-delay compensation. At the same time, owing to the dynamics simulator of the space robot added in the ground hardware-in-the-loop verification system, the base disturbance can be considered during the approaching and capturing procedure, which makes the ground verification system realistic and credible.

The ground verification experiment system includes the real controller of space manipulator, the eye-in-hand camera and the dynamics simulator, which can veritably simulate the capturing process based on the visual servoing in space and consider the effect of time delay and the free-floating base disturbance.

This paper aims to propose a system to acquire images automatically for digital reconstruction of heritage artifacts using a six-degree of freedom industrial manipulator.

A virtual environment is created using Robot Studio® software to integrate the trajectory and differential motion of the robot manipulator and the motion of camera while acquiring images. A new area similarity matrix method is proposed to reduce the number of images required for digital reconstruction using Autodesk Recap® software. Real-time experiments have been performed using objects such as minion, ultimaker robot and cube. Evaluation of the digital reconstruction is conducted using the contour area matching method.

The number of images required for reconstruction based on area similarity matrix method is reduced to 63 per cent when compared with the random selection method. Quality parameters such as surface area, volume, number of defect holes, vertices and faces are enhanced for the proposed method.

Digital reconstruction of large-sized heritage artifacts cannot be performed in this setup. But this can be overcome by fixing the manipulator on a mobile platform or overhead crane. This paper does not discuss the reconstruction of partially damaged heritage artifacts, which could be accomplished based on deep learning techniques.

Using this approach, off-the-shelf heritage artifacts and large-scale objects can be reconstructed digitally with a minimum number of images and without compromising the quality of original models.

To the best of the authors’ knowledge, area similarity-based approach in 3D digital reconstruction by coupling the kinematics of an industrial manipulator and camera is proposed for the first time. A fully automated digital reconstruction technology to preserve valuable heritage artifacts has been developed. It also highlights the space constraints of the industrial manipulator in digital reconstruction.

This study aims to propose a novel method based on model learning with sparsity inducing norms for estimating dynamic gravity terms of the serial manipulators. This method is realized by operating the robot, acquiring data and filtering the features in signal acquisition to adapt to the dynamic gravity parameters.

The core principle of the method is to analyze the dictionary composition of the basis function of the model based on the dynamic equation and the Jacobian matrix of an arm. According to the structure of the basis function and the sparsity of the features, combined with joint-angle and driving-torque data acquisition, the effective features of dynamic gravity parameters are screened out using L1-norm optimization and learning algorithms.

The theoretical analysis revealed that training data obtained based on joint angles and driving torques could rapidly update dynamic gravity parameters. The simulation experiment was carried out by using the publicly available robot model and compared with the previous disassembly method to evaluate the feasibility and performance. The real 7-degree of freedom (DOF) industrial manipulator was used to further discuss the effects of the feature selection. The results show that this estimation method can be fully operational and efficient in industrial applications.

This approach is applicable to most serial robots with multi-DOF and the dynamic gravity parameters of the robot are estimated through learning and optimization. The method does not require prior knowledge of the robot arm structure and only requires joint-angle and driving-torque data acquisition under low-speed motion. Furthermore, as it is a data-driven-based method, it can be applied to gravity parameters updating.

Different from previous general robot dynamic modelling methods, the sparsity of the analytical form of dynamic equations was exploited and model learning was formulated as a convex optimization problem to achieve effective gravity parameters screening. The novelty of this estimation approach is that the method does not only require any prior knowledge but also does not require a specifically designed trajectory. Thus, this method can avoid the laborious work of parameter calibration and the induced modelling errors. By using a data-driven learning approach, the new parameter updating process can be completed conveniently when the robot carries additional mass or the end-effector changes for different tasks.

The purpose of this paper is to present the design and implementation of a zero‐initial‐velocity self‐motion scheme on a six degrees of freedom (six‐DOF) planar robot manipulator.

In view of the existence of physical limits in an actual robot manipulator, both joint‐angle limits and joint‐velocity limits are initially incorporated into the proposed self‐motion scheme for practical purposes. The proposed self‐motion scheme is then reformulated as a quadratic program (QP) and resolved at the joint‐velocity level. By combining the zero‐initial‐velocity constraint, the resultant QP can prevent the occurrence of a large initial joint velocity. Finally, based on the conversion technique of QP to a linear variational inequality, a numerical computing algorithm is presented to solve the QP and the corresponding self‐motion scheme.

The proposed zero‐initial‐velocity self‐motion scheme eliminates the phenomenon of the abrupt and drastic increase in joint velocity at the beginning of the self‐motion task execution. Simulative and experimental results based on a practical six‐DOF planar robot manipulator further verify the realizability, effectiveness and accuracy of the proposed self‐motion scheme. Based on the simulative results, the joint angle and the joint velocity meet the joint physical constraints.

The paper provides effective methods for handling the physical limits, the design of zero‐initial velocity, and the conversion from joint angle and joint velocity to motor‐driving pulses. Thus, the effective and safe self‐motion control of a manipulator is realized.

The paper describes the design and implementation of a zero‐initial‐velocity self‐motion scheme.

Describes the experience of setting up a cooperative arm system based on individual open‐architecture controllers. Two six‐degree‐of‐freedom industrial manipulators, one of which is mounted on a moving track, are installed to realize a cooperative experimental set‐up. The main issues related to the cooperative manipulation are overviewed and its potential applications in industry are discussed. A brief description of the system’s components is given. The most relevant problems encountered in setting up the cooperative system based on individual control architectures are detailed. The result of the experience is that by using available industrial manipulators, rather than prototypes, and without re‐designing the controller hardware, it is possible to realize a cooperative manipulator system.

The purpose of this paper is to review the progress made in arc welding automation using trajectory planning, seam tracking and control methodologies.

This paper discusses key issues in trajectory planning towards achieving full automation of arc welding robots. The identified issues in trajectory planning are real-time control, optimization methods, seam tracking and control methodologies. Recent research is considered and brief conclusions are drawn.

The major difficulty towards realizing a fully intelligent robotic arc welding system remains an optimal blend and good understanding of trajectory planning, seam tracking and advanced control methodologies. An intelligent trajectory tracking ability is strongly required in robotic arc welding, due to the positional errors caused by several disturbances that prevent the development of quality welds. An exciting prospect will be the creation of an effective hybrid optimization technique which is expected to lead to new scientific knowledge by combining robotic systems with artificial intelligence.

This paper illustrates the vital role played by optimization methods for trajectory design in arc robotic welding automation, especially the non-gradient approaches (those based on certain characteristics and behaviour of biological, molecular, swarm of insects and neurobiological systems). Effective trajectory planning techniques leading to real-time control and sensing systems leading to seam tracking have also been studied.

The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid colliding with other objects and achieve accurate movements. Trajectory planning algorithms are the soul of motion control of industrial robots. A predefined space trajectory can let the robot move through the desired spatial coordinates, avoid colliding with other objects and achieve accurate movements.

The mathematical expressions of the proposed algorithm are deduced. The speed control, position control and orientation control strategies are realized and verified with simulations, and then implemented on a six degrees of freedom (6-DOF) industrial robot platform.

A fixed-distance trajectory planning algorithm based on Cartesian coordinates was presented. The linear trajectory, circular trajectory, helical trajectory and parabolic trajectory in Cartesian coordinates were implemented on the 6-DOF industrial robot.

A simple and efficient algorithm is proposed. Enrich the kind of trajectory which the industrial robot can realize. In addition, the industrial robot can move more concisely, smoothly and precisely.

In the USSR industrial robots (automatic manipulators) are considered to be one of the most important means of achieving complex industrial automation. They provide a means for human emancipation from dangerous, hard and boring labour and solution to the problem of the more efficient use of labour resources. At present the programs for development, production and application of industrial robots are being implemented in the Soviet Union on the basis of a state integrated 5‐year plan covering the key branches of industry and involving the Academy of Sciences and Higher Educational Institutions. A second similar program will be completed by 1980. It is based on the principle of central state unification of the major components of robots, a series of standard sizes and consequently the development of robot‐equipped standard technological complexes. Simultaneously, research is being carried on in the development of the next generation of robot devices. Some other aspects of the problem are also being investigated including the development of methods for evaluating the economic efficiency of robot application as well as social aspects and training of personnel.

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 paper is to present the development and validation of a methodology which allows modeling and solving the inverse and direct dynamic problem in real time in robot manipulators.

The robot dynamic equation is based on the Gibbs‐Appell equation of motion, yielding a well‐structured set of equations that can be computed in real time. This paper deals with the implementation and calculation of the inverse and direct dynamic problem in robots, with an application to the real‐time control of a PUMA 560 industrial robot provided with an open control architecture based on an industrial personal computer.

The experimental results show the validity of the dynamic model and that the proposed resolution method for the dynamic problem in real time is suitable for control purposes.

The accuracy of the applied friction model determines the accuracy of the identified overall model and consequently of the control. This is especially obvious in the case of the PUMA 560 robot, in which the presence of friction is remarkable in some of their joints. Hence, future work should focus on identifying a more precise friction model. The robot model could also be extended by incorporating rotor dynamics and could be applied for different robot configurations as parallel robots.

Gibbs‐Appell equations are used in order to develop the robotic manipulator dynamic model, instead of more usual dynamics formulations, due to several advantages that these exhibit. The obtained non‐physical identified parameters are adapted in order to enable their use in a control algorithm.