Closeness to singularity based on kinematics and dynamics and singularity avoidance of a planar parallel robot with kinematic redundancy

Planar parallel robots are appealing due to their structural simplicity, high stiffness, and large payload capacity. One major problem is that workspace and singularity of non-redundant parallel robots are unchangeable. Hence, when the desired path crossed with singularity or exceeded the workspace’s boundary, the robot is incapable of finishing the task. Another one is closeness to singularity. If one can know the distance between the end manipulator and singularity or workspace’s boundary, the robot will avoid lose control or breakdown. Compared with the traditional planar parallel robot, the planar parallel robot with kinematic redundancy possesses the advantages of avoiding singularity, expanding workspace by adjusting kinematic redundancy parameter. Therefore, the objective of this article is to present an offline action-strategy of a planar robot with kinematic redundancy to measure the closeness to singularity and avoid singularity. It includes two main parts: First, before the robot moves along the desired paths, the closeness to singularity was measured based on the performance of the kinematics and dynamics so that one can know where to pause the robot. Second, an algorithm is designed to previously find the proper kinematic redundancy parameters for changing singularity and workspace. Hence, the robot can smoothly move far from the singularity to finish all paths. The results indicate that the robot can adjust its configuration to well realize the goal by the offline action-strategy.

Dynamic model estimating and designing controller for the 2-DoF planar robot in interaction with cable-driven robot based on adaptive neural network

This study intends to investigate the dynamic model estimation and the design of an adaptive neural network based controller for a passive planar robot, performing 2-DoF motion pattern which is in interaction with an actuated cable-driven robot. In fact, the main goal of applying this structure is to use a number of light cables to drive serial robot links and track the desired reference model by the robot’s end-effector. The under study system can be used as a rehabilitation setup which is helpful for those with arm disability. In this way, upon applying sliding mode error dynamics, it is necessary to determine a vector that contains the matrices related to the robot dynamics. However, finding these matrices requires the use of computational approaches such as Newton-Euler or Lagrange. In addition, since the purpose of this paper is to express comprehensive methods, so with increasing the number of links and degrees of freedom of the robot, finding the dynamics of the robot becomes more difficult. Therefore, the Adaptive Neural Network (ANN) with specific inputs has been used for estimation unknown matrices of the system and the controller design has been performed based on it. So, the main idea in using an adaptive controller is the fact there is no pre-knowledge for the dynamic modeling of the system since the human arm could have different dynamic properties. Hence, the controller is formed by an ANN and robust term. In this way, the adaptation laws of the parameters are extracted by Lyapunov approach, and as a result, as aforementioned, the asymptotic stability of the whole of the system is guaranteed. Simulation results certify the efficiency of the proposed method. Finally, using the Roots Mean Square Error (RMSE) criteria, it has been revealed that, in the presence of bounded disturbance with different amplitude, adding the robust term to the controller leads to improve the tracking error about 34% and 62%, respectively.

Desired model compensation-based position constrained control of robotic manipulators

This work presents the design and the corresponding stability analysis of a desired model-based, joint position constrained, controller formulation for robotic manipulators. Specifically, provided that the initial joint position tracking error signal starts within some predefined region, the proposed controller ensures that the joint tracking error signal remains inside this region and approaches to zero asymptotically. Extensive numerical simulations and experimental studies performed on a two-link direct-drive planar robot are provided in order to illustrate the effectiveness and feasibility of the proposed controller.

Guidance and Control of a Planar Robot Manipulator Used in an Assembly Line

In order to achieve higher productivity and lower cost requirements, robot manipulators have been enrolled in assembling processes in last decades as well as other implementation areas such as transportation, welding, mounting, and quality control. As a new application of this field, the control of the synchronous movements of a planar robot manipulator and moving belt is dealt with in this study. Here, the mentioned synchronization is tried to be maintained in accordance with a guidance law which leads the robot manipulator to put selected components onto the specific slots on the moving belt without interrupting the assembling process. In this scheme, the control of the manipulator is carried out by considering the PI (proportional plus integral) control law. Having performed the relevant computer simulations based on the engagement geometry between the robot manipulator and moving belt, it is verified that the mentioned pick-and-place task can be successfully accomplished under different operating conditions.

A Simulator for Testing Planar Upper Extremity Rehabilitation Robot Control Algorithms

In this study, we took advantage of the emergence of accurate biomechanical human hand models to develop a system in which the interaction between a human arm and a rehabilitation robot while performing a planar trajectory tracking task can be simulated. Seven biomechanical arm models were based on the 11-degree-of-freedom Dynamic Arm Simulation model and implemented in OpenSim. The model of the robot was developed in MatlabSimulink and interaction between the arm and robot models was achieved using the OpenSim API. The models were tested by simulating the performance of each model while moving the end effector of a simulated planar robot model through an elliptical trajectory with an eccentricity of 0.94. Without assistance from the robot, the average root-mean-square error (RMSE) for all subjects was 3.98 mm. With the simulated robot providing assistive torque, the average RMSE error reduced to 2.88 mm. The test was repeated after modifying the length of the robot links, and an average RMSE of 2.91 mm recorded. A single-factor ANOVA test revealed that there was no significant difference in the RMSE for the two different robot geometries (p-value = 0.479), revealing that the simulator was not sensitive to robot geometry.

Natural Frequencies Identification by FEM Applied to a 2-DOF Planar Robot and Its Validation Using MUSIC Algorithm

In this paper, the natural frequencies (NFs) identification by finite element method (FEM) is applied to a two degrees-of-freedom (2-DOF) planar robot, and its validation through a novel experimental methodology, the Multiple Signal Classification (MUSIC) algorithm, is presented. The experimental platforms are two different 2-DOF planar robots with different materials for the links and different types of actuators. The FEM is carried out using ANSYS™ software for the experiments, with vibration signal analysis by MUSIC algorithm. The advantages of the MUSIC algorithm against the commonly used fast Fourier transform (FFT) method are also presented for a synthetic signal contaminated by three different noise levels. The analytical and experimental results show that the proposed methodology identifies the NFs of a high-resolution robot even when they are very closed and when the signal is embedded in high-level noise. Furthermore, the results show that the proposed methodology can obtain a high-frequency resolution with a short sample data set. Identifying the NFs of robots is useful for avoiding such frequencies in the path planning and in the selection of controller gains that establish the bandwidth.