Search results

This purpose of this paper is to design a peg-in-hole controller for a cable-driven serial robot with compliant wrist (CDSR-CW) using cable tensions and joint positions. The peg is connected to the robot link through a CW. It is required that the controller does not rely on any external sensors such as 6-axis wrist force/torque (F/T) sensor, and only the compliance matrix’s estimated value of the CW is known.

First, the peg-in-hole assembly system based on a CDSR-CW is analyzed. Second, a characterization algorithm using micro cable tensions and joint positions to express the elastic F/T at the CW is established. Next, under the premise of only knowing the compliance matrix’s estimate, a peg-in-hole controller based on force/position hybrid control is proposed.

The experiment results show that the plug contact F/T can be tracked well. This verifies the validity and correctness of the characterization algorithm and peg-in-hole controller for CDSR-CWs in this paper.

First, to the authors’ knowledge, there is no relevant work about the peg-in-hole assembly task using a CDSR-CW. Besides, the proposed characterization algorithm for the elastic F/T makes the peg-in-hole controller get rid of the dependence on the F/T sensor, which expands the application scenarios of the peg-in-hole controller. Finally, the controller does not require an accurate compliance matrix, which also increases its applicability.

The purpose of the paper is to propose an efficient and accurate force/torque (F/T) sensing method for the robotic wrist-mounted six-dimensional F/T sensor based on an excitation trajectory.

This paper presents an efficient and accurate F/T sensing method based on an excitation trajectory. First, the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity. Therefore, the sensing accuracy is improved. Then, the excitation trajectory with optimized poses is used for robot following and data acquisition. The data acquisition is not limited by poses and its time can be significantly shortened. Finally, the least squares method is used to identify parameters and sense contact forces/torques.

Experiments have been carried out on the self-developed robot manipulator. The results strongly demonstrate that the proposed approach is more efficient and accurate than the existing widely-adopted method. Furthermore, the data acquisition time can be shortened from more than 60 s to 3 s/20 s. Thus, the proposed approach is effective and suitable for fast-paced industrial applications.

The main contributions of this paper are as follows: the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity; and the excitation trajectory with optimized poses is used for robot following and data acquisition.

Steer-by-wire (SBW) system mainly relies on sensors, controllers and motors to replace the traditionally mechanical transmission mechanism to realize steering functions. However, the sensors in the SBW system are particularly vulnerable to external influences, which can cause systemic faults, leading to poor steering performance and even system instability. Therefore, this paper aims to adopt a fault-tolerant control method to solve the safety problem of the SBW system caused by sensors failure.

This paper proposes an active fault-tolerant control framework to deal with sensors failure in the SBW system by hierarchically introducing fault observer, fault estimator, fault reconstructor. Firstly, the fault observer is used to obtain the observation output of the SBW system and then obtain the residual between the observation output and the SBW system output. And then judge whether the SBW system fails according to the residual. Secondly, dependent on the residual obtained by the fault observer, a fault estimator is designed using bounded real lemma and regional pole configuration to estimate the amplitude and time-varying characteristics of the faulty sensor. Eventually, a fault reconstructor is designed based on the estimation value of sensors fault obtained by the fault estimator and SBW system output to tolerate the faulty sensor.

The numerical analysis shows that the fault observer can be rapidly activated to detect the fault while the sensors fault occurs. Moreover, the estimation accuracy of the fault estimator can reach to 98%, and the fault reconstructor can make the faulty SBW system to retain the steering characteristics, comparing to those of the fault-free SBW system. In addition, it was verified for the feasibility and effectiveness of the proposed control framework.

As the SBW fault diagnosis and fault-tolerant control in this paper only carry out numerical simulation research on sensors faults in matrix and laboratory/Simulink, the subsequent hardware in the loop test is needed for further verification.

Aiming at the SBW system with parameter perturbation and sensors failure, this paper proposes an active fault-tolerant control framework, which integrates fault observer, fault estimator and fault reconstructor so that the steering performance of SBW system with sensors faults is basically consistent with that of the fault-free SBW system.

This paper aims to propose a new technique for programming robotized machining tasks based on intuitive human–machine interaction. This will enable operators to create robot programs for small-batch production in a fast and easy way, reducing the required time to accomplish the programming tasks.

This technique makes use of online walk-through path guidance using an external force/torque sensor, and simple and intuitive visual programming, by a demonstration method and symbolic task-level programming.

Thanks to this technique, the operator can easily program robots without learning every robot-specific language and can design new tasks for industrial robots based on manual guidance.

The main contribution of the paper is a new procedure to program machining tasks based on manual guidance (walk-through teaching method) and user-friendly visual programming. Up to now, the acquisition of paths and the task programming were done in separate steps and in separate machines. The authors propose a procedure for using a tablet as the only user interface to acquire paths and to make a program to use this path for machining tasks.

The six-axis force/torque sensor based on a Y-type structure has the advantages of simple structure, small space volume, low cost and wide application prospects. To meet the overall structural stiffness requirements and sensor performance requirements in robot engineering applications, this paper aims to propose a Y-type six-axis force/torque sensor.

The performance indicators such as each component sensitivities and stiffnesses of the sensor were selected as optimization objectives. The multiobjective optimization equations were established. A multiple quadratic response surface in ANSYS Workbench was modeled by using the central composite design experimental method. The optimal manufacturing structural parameters were obtained by using multiobjective genetic algorithm.

The sensor was optimized and the simulation results show that the overload resistance of the sensor is 200%F.S., and the axial stiffness, radial stiffness, bending stiffness and torsional stiffness are 14.981 kN/mm, 16.855 kN/mm, 2.0939 kN m/rad and 6.4432 kN m/rad, respectively, which meet the design requirements, and the sensitivities of each component of the optimized sensor have been well increased to be 2.969, 2.762, 4.010, 2.762, 2.653 and 2.760 times as those of the sensor with initial structural parameters. The sensor prototype with optimized parameters was produced. According to the calibration experiment of the sensor, the maximum Class I and II errors and measurement uncertainty of each force/torque component of the sensor are 1.835%F.S., 1.018%F.S. and 1.606%F.S., respectively. All of them are below the required 2%F.S.

Hence, the conclusion can be drawn that the sensor has excellent comprehensive performance and meets the expected practical engineering requirements.

The purpose of this study which resulted in this work is to propose an optimization method of sensors distribution for structural impact localization.

This paper presents a multi-objective optimization study of a novel sensors distribution technique, where two optimization objective functions are considered: sensors number and sensors location optimization performance index. In addition, the finite element analysis, the time-frequency transform and the principal component analysis are combined to quantize the above objective functions. The non-dominated sorting genetic algorithm II (NSGA-II) is used to acquire Pareto solutions.

The effectiveness of this method is validated through a prototype laboratory called the piezoelectric intelligent structure where promising results are obtained.

An optimization method of this novel sensors distribution technique is built and produced a set of efficiency solutions for the real-world problem of impact localization where two conflicting objectives are involved.

Aiming at the problems of geometric precision misalignment and unconsidered physical constraints between large components during the measurement-assisted assembly, a self-adaptive alignment strategy based on the dynamic compliance center (DCC) is proposed in this paper, using force information to guide alignment compliantly.

First, the self-adaptive alignment process of large components is described, and its geometrical and mechanical characteristics are analyzed based on six-dimensional force/torque (F/T). The setting method of DCC is studied and the areas of DCC are given. Second, the self-adaptive alignment platform of large components driven by the measured six-dimensional F/T is constructed. Based on this platform, the key supporting technologies, including principle of self-adaptive alignment, coordinate transfer, calculation of six-dimensional F/T and alignment process control, are illustrated.

Using the presented strategy, the position and orientation of large component is adjusted adaptively responding to measured six-dimensional F/T and the changes of contact states are consistent with the strategy. Through the setting of DCC, alignment process runs smoothly without jamming.

This strategy is applied to the alignment experiment of large components muff coupling. The experimental results show that the proposed alignment strategy is correct and effective and meets the real-time requirement.

This paper proposed a novel way to apply force information in large component self-adaptive alignment, and the setting method of DCC was presented to make the alignment process more feasible.

Six-axis force sensors play an important role in civilian and military fields because of their multifunctionality. In the context of sensor structure design, sensitivity and sensitivity isotropy are often considered. This paper aims to study the possible relationship between the sensitivity/sensitivity isotropy and structural parameters of an 8/4–4 parallel six-axis force sensor. A comprehensive evaluation index and structural optimization design scheme are suggested in the end.

Based on the conditional number of the Jacobian matrix spectral norm, the sensitivity and sensitivity isotropy of the sensor are derived. Orthogonal experiments are used to determine the degree of primary and secondary factors that have a substantial effect on the sensor characteristics. The relationship between the performance indices and the structural parameters is analyzed by the performance atlas method. The comprehensive evaluation index lays the foundation for the structural optimization design of an 8/4–4 parallel six-axis force sensor.

The variation in each performance index of the sensor for each of the structural parameters is analyzed, and the structural parameters of the sensor with the desired performance indices can be easily selected from the performance atlases. A comprehensive performance evaluation index with a target value of 1 is proposed, and the overall influence of the structural parameters on the sensor performance index is investigated. A simulation example shows the feasibility of the proposed evaluation index.

The importance of each structural parameter of the 8/4–4 parallel six-axis force sensor is determined through orthogonal experiments in this paper. Relations among the structural parameters meeting the performance indices are derived and shown in the performance atlases. A comprehensive evaluation index is proposed to analyze the overall sensor performance.

The purpose of this paper is to introduce a novel device to handle a robot manipulator which can grip large‐size panels. This concept arises from questioning why the glazing task is always performed manually and it is assumed that if the panel is handled by worker's bare hands, the material is lifted by a robot system and can be assembled to a frame easily and intuitively.

This study proposes the intuitive manipulator device (IMD) which can be attached on the panel directly and connected to it with the coordinate of robot end‐effector based on a virtual coordinate of IMD. The virtual coordinate is defined by the detection of the location of the IMD from the robot end‐effector using IR sensor scanning and origin point estimation method. In this study, the robot manipulator system is operated by a combination of the commands of two IMDs to perform the panel assembly test and its aspect of input commands is compared with the previous force‐control based human‐robot cooperative systems.

The proposed system shows the better performance while reducing the frequent force reflection of robot system against an environment and simplifies the instant input source for robot control system. Those are caused by the intuitiveness of visual servoing performed by operators and the minimization of a force control strategy by utilizing the operator's own sensitivity. The proposed system shows the possibility of efficiency improvement and simple mechatronic system to realize the automation of panel assembly task.

The proposed device alternates the expensive 6‐axis F/T sensor system to handle the robot manipulator by using the two 3‐axis load cell and those force/torque combinations. Also, the developed device is portable and can attach on the material anywhere. That is why this system could cover various sizes of materials. This system minimizes the computational load to control the robot system and improves the efficiency of an assembly task based on the human‐robot cooperation strategy.

This paper aims to propose a dynamic trajectory-tracking control method for robotic transcranial magnetic stimulation (TMS), based on force sensors, which follows the dynamic movement of the patient’s head during treatment.

First, end-effector gravity compensation methods based on kinematics and back-propagation (BP) neural networks are presented and compared. Second, a dynamic trajectory-tracking method is tested using force/position hybrid control. Finally, an adaptive proportional-derivative (PD) controller is adopted to make pose corrections. All the methods are designed for robotic TMS systems.

The gravity compensation method, based on BP neural networks for end-effectors, is proposed due to the different zero drifts in different sensors’ postures, modeling errors in the kinematics and the effects of other uncertain factors on the accuracy of gravity compensation. Results indicate that accuracy is improved using this method and the computing load is significantly reduced. The pose correction of the robotic manipulator can be achieved using an adaptive PD hybrid force/position controller.

A BP neural network-based gravity compensation method is developed and compared with traditional kinematic methods. The adaptive PD control strategy is designed to make the necessary pose corrections more effectively. The proposed methods are verified on a robotic TMS system. Experimental results indicate that the system is effective and flexible for the dynamic trajectory-tracking control of manipulator applications.