Serial Robot Manipulators Research Articles

A dynamic model for GPS based attitude determination and testing using a serial robotic manipulator

A computational algorithm is developed for estimating accurately the attitude of a robotic arm which moves along a predetermined path. This algorithm requires preliminary input data obtained in the static mode to yield phase observables for the precise, 3-axis attitude determination of a swinging manipulator in the dynamic mode. Measurements are recorded simultaneously by three GPS L1 receivers and then processed in several steps to accomplish this task. First, artkconv batch executable converts GPS receiver readings into RINEX format to generate GPS observables and ephemeris for multiple satellites. Then baseline vectors determination is carried out by baseline constrained Least-Squares Ambiguity Decorrelation (LAMBDA) method that uses double difference carrier phase estimates as input to calculate integer solution for each baseline. Finally, attitude determination is made by employing alternatively Least-squares attitude determination (LSAD) in the static mode and extended Kalman filter in the dynamic mode. The algorithm presented in this paper is applied to recorded data on Mitsubishi RV-M1 robotic arm in order to produce attitude estimates. These results are confirmed by another set of Euler angles independently evaluated from robotic arm postures obtained along the predefined trajectory.

A Comparative Study Between the Successive Screw Displacement and Quaternion Based Methods Used in Forward Kinematics of Serial Robot Manipulator

A Comparative Study Between the Successive Screw Displacement and Quaternion Based Methods Used in Forward Kinematics of Serial Robot Manipulator

Design, analysis and modelling of a hybrid controller for serial robotic manipulators

SUMMARYWhen the end-effector of a robotic arm grasps different payload masses, the output of joint motion will vary. By using a model reference adaptive control approach, the payload variation effect can be solved. This paper describes the design for a hybrid controller for serial robotic manipulators by combining a PID controller and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators is compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+ MRAC controllers is better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

An online method for serial robot self-calibration with CMAC and UKF

The aim of this paper is to propose an online self-calibration method which is used to estimate the kinematic parameters errors of the serial robot manipulators. In this method, a position marker and an inertial measurement unit (IMU) are solidly fixed at the robot end-effector (EE). The position is determined with a position sensor by tracking the marker and the orientation is measured by the IMU in real time. The Factored Quaternion Algorithm (FQA) is used to represent the orientation in a quaternion. In order to eliminate the influence of the noises and the measurement errors from the sensors, the Cerebellar Model Articulation Controller (CMAC) algorithm is adopted to estimate poses of the robot EE. With the estimated poses, the errors between the actual and the nominal kinematic parameters of the robot manipulator could be identified by the Unscented Kalman Filter (UKF). This method only takes several uncomplicated steps but performs with high autonomy and accuracy. Several experiments are carried out with a GOOGOL GRB3016 robot to verify this method and the results indicate that it is indeed of high convenience, precision and efficiency.

Inverse kinematic solutions of 6-D.O.F. biopolymer segments

SUMMARYWe present two methods to find all the possible conformations of short six degree-of-freedom segments of biopolymers which satisfy end constraints in position and orientation. One of our methods is motivated by inverse kinematic solution techniques which have been developed for “general” 6R serial robotic manipulators. However, conventional robot kinematics methods are not directly applicable to the geometry of polymers, which can be treated as a degenerate case where all the “link lengths” are zero. Here, we propose a method which extends the elimination method of Kohli and Osvatic. This method can be applied directly to the geometry of biopolymers. We also propose a heuristic method based on a Lie-group-theoretic description. In this method, we utilize inverse iterations of the Jacobian matrix to obtain all conformations which satisfy end constraints. This can be easily implemented for both the general 6R manipulator and polymers. Although the extended elimination method is computationally faster than the Jacobian method, in cases where some of the joint angles are 180° (i.e., where the elimination method fails), we combine these two methods effectively to obtain the full set of inverse kinematic solutions. We demonstrate our approach with several numerical examples.

Adaptive Sliding Mode Control of a 6-DOF RLED Robot Manipulator with Uncertain Parameters and External Disturbances

This paper addresses the end-effector position and orientation tracking problem of a 6-degrees of freedom (DOF) rigid link electrically driven (RLED) revolute joint serial robot manipulator with uncertain parameters and external disturbances. System uncertainties and external disturbances are bounded but their upper limits are unknown. The input matrix, which is always invertible and not necessarily a diagonal matrix, is also assumed to be uncertain with a certain bound. An adaptive sliding mode control (ASMC) is designed to solve the tracking problem given these uncertainties. Note that the designed control method can be applied to any RLED serial robot manipulator. No regression matrices are required and the uncertainty upper limits are not necessarily known. Furthermore, the controller computation time can be reduced by considering some parts of the system dynamics and the nth time-derivative reference signals of nth order system, in this case desired joint jerk signals, as unknown bounded uncertainties. The desired trajectory is defined in operational space while the designed ASMC works in joint space. The methods to convert the end-effector pose, velocity, acceleration, and jerk from operational space to joint space are also explained. The Lyapunov stability criterion is applied to prove the convergence of the adaptive gain of ASMC, the sliding surface, and system stability. Finally, simulation results verified ASMC performance.

Robot-Assisted Landing of VTOL UAVs: Design and Comparison of Coupled and Decoupling Linear State-Space Control Approaches

This paper addresses the problem of landing a VTOL UAV using a serial robotic manipulator fixed to the landing surface, which assists the UAV during the last, most challenging, landing phase. In this phase, UAV and manipulator are connected via a universal hinge, which decouples the flying vehicle’s and the robot’s end-effector orientation. The main contribution of the paper is the design of a linear state-space controller for position and orientation of the UAV while it is fixed to the manipulator. Furthermore, we compare a coupled and a decoupling realization of the model-based controller with a model-free controller. Both model-based controllers consider the dynamics of an attitude-controlled aerial vehicle and use the acceleration of the robot’s end-effector as control input. All three controllers are validated and compared in experiments using a KUKA/DLR light-weight robot on a nonmoving base and an AR.Drone 2.0 quadrotor. The experimental results show that decoupling is superior to the coupled and the model-free approach, since the orientation of the UAV rotorcraft is controlled more precisely.

Time-Optimal Path Parameterization for Redundantly Actuated Robots: A Numerical Integration Approach

Time-optimal path parameterization (TOPP) under actuation bounds plays a fundamental role in many robotic theories and applications. This algorithm was first developed and perfected for classical serial robotic manipulators whose actuation is nonredundant. Yet, redundantly actuated systems, such as parallel manipulators or humanoid robots in multicontact tasks, are increasingly common in all fields of robotics. Here, we extend the classical algorithm of TOPP (a.k.a. numerical integration approach) to the case of redundantly actuated systems. As illustration, we present an application to multicontact trajectory planning for a humanoid robot.

Guest editorial on reconfigurable and deployable mechanisms

With the development of science and technology and with a particular emphasis on the progress of deep space and undersea exploration, traditional mechanisms with limited adaptability and flexibility are facing challenges. Reconfigurable and deployable mechanical systems being capable of adapting themselves to variable tasks have been attracting great attentions in both academia and industry. Especially in space applications, the deployable antenna and the solar array are widely used as deployable mechanisms. With the increasing requirements upon transformation, dexterity, modularization, reconfigurability, and reliability, related theory and technology of reconfigurable and deployable mechanisms will be continuously enriched, driving the scientists to put more initiative and enthusiasm into this field. In this special issue, 4 articles out of 16 submissions are finally accepted. In the article titled ‘‘Application of gene structure and mitosis concepts to the study and design of folding mechanisms,’’ a novel approach based on a consideration of gene structure, mitosis, and cell fusion was proposed to the study and design of metamorphic mechanisms. Work in the article titled ‘‘The automatic drilling system of 6R-2P mining drill jumbo’’ mainly focuses on a mining drill jumbo which is a redundant serial robotic manipulator with 8 degrees of freedom, six revolute joints, and two prismatic joints. In the article titled ‘‘On a Jansen leg with multiple gait patterns for reconfigurable walking platforms,’’ a novel reconfigurable Theo Jansen linkage that can produce a wide variety of gait cycles was present. In the article titled ‘‘Modeling on thermally induced coupled micromotions of satellite with complex flexible appendages,’’ the authors investigated the deployable mechanism for the satellite application. All of these works are interesting, reflecting the state of the art under developing in this area. The reconfigurable and deployable mechanisms will provide many innovative ways to meet the future tasks. For example, a reconfigurable rover can display a high degree of mobility, versatility, and robustness to adapt to irregular terrain in planetary exploration; modular manipulators, composed of a set of modular links and joints with various sizes, can be assembled into appropriate configurations for various given tasks. We believe that there are still plenty spaces for research and development of the reconfigurable and deployable mechanisms. Jinguo Liu, Xilun Ding, Yan Jin, Ketao Zhang and Guangbo Hao State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China Robotics Institute, Beijing University of Aeronautics and Astronautics, Beijing, China School of Mechanical & Aerospace Engineering, Queen’s University Belfast, Belfast, UK Centre for Robotics Research, King’s College London, Strand, UK School of Engineering, University College Cork, Cork, Ireland

Comparison of four different heuristic optimization algorithms for the inverse kinematics solution of a real 4-DOF serial robot manipulator

In this study, a 4-degree-of-freedom (DOF) serial robot manipulator was designed and developed for the pick-and-place operation of a flexible manufacturing system. The solution of the inverse kinematics equation, one of the most important parts of the control process of the manipulator, was obtained by using four different optimization algorithms: the genetic algorithm (GA), the particle swarm optimization (PSO) algorithm, the quantum particle swarm optimization (QPSO) algorithm and the gravitational search algorithm (GSA). These algorithms were tested with two different scenarios for the motion of the manipulator's end-effector. One hundred randomly selected workspace points were defined for the first scenario, while a spline trajectory, also composed of one hundred workspace points, was used for the second. The optimization algorithms were used for solving of the inverse kinematics of the manipulator in order to successfully move the end-effector to these workspace points. The four algorithms were compared according to the execution time, the end-effector position error and the required number of generations. The results showed that the QPSO could be effectively used for the inverse kinematics solution of the developed manipulator.

Cinemática inversa de robot serial utilizando algoritmo genético basado en MCDS

Los robots manipuladores seriales son herramientas eficaces para realizar tareas repetitivas y de precisión en la industria, siempre que se comprenda la cinemática involucrada en el posicionamiento y orientación del efector final. Este artículo presenta una metodología para resolver el problema cinemático inverso de un robot serial (Melfa RV-2A) utilizando un algoritmo genético (AG) a partir del modelo cinemático directo Screws (MCDS). Para esto, se obtienen los parámetros Screw que modelan el robot, se calcula el espacio de trabajo asociado y se diseña el AG contemplando una función multi-objetivo de alcance de posición y orientación en que se sitúa el efector final, con respecto a una coordenada y orientación de un punto objetivo establecido. La validación del AG se realiza según la aptitud, el tiempo de convergencia y la cantidad de generaciones usadas por la función para alcanzar el objetivo. Por tanto, la implementación de un AG basado en un MCDS es una herramienta prometedora que podría utilizarse para calcular la cinemática inversa de robots seriales. Esta novedosa implementación permite establecer por primera vez la exposición matricial de un sistema cinemático directo para obtener la solución cinemática inversa de un robot serial. En consecuencia, se demuestra que esta es una metodología factible y eficiente para solucionar la cinemática inversa de cualquier tipo de robot manipulador.

Theoretical and experimental investigation of viscoelastic serial robotic manipulators with motors at the joints using Timoshenko beam theory and Gibbs–Appell formulation

In this article, the mathematical modeling of n-viscoelastic-link robotic manipulators based on the Gibbs–Appell formulation and the assumed mode method is developed. The elastic properties of the links are modeled according to the Timoshenko beam theory and its associated mode shapes. Also the dynamic effects of the motors at the joints are fully taken into consideration. In the mathematical modeling, the effects of torsion, extensional deformation, bending in two directions, structural damping, and viscous air as well as the gravity effects have also been considered. A recursive algorithm based on 4 × 4 transformation matrices has been developed to ease the derivation of motion equations. The mismatch between the high-speed vibrations of flexible robotic arms and the low-speed operation of the software and hardware interface in the computer and the experimental setup is a serious obstacle for the measuring and controlling of such systems. So, to verify the simulation results and the results obtained from the experimental test bed, high-speed digital-to-analog converter components on an electronic interface board are used in conjunction with the National Instrument’s LABVIEW software package.

Motion Control Strategies based on PD Control for a Four Degree-of-Freedom Serial Robotic Manipulator to Mimic Human Index Finger Articulations

The present study is based on motion control of an articulated model of a human index finger that has been modeled as a four-degree-of-freedom serial robotic manipulator. Preliminary studies on position and tracking control have been carried out by testing various control strategies based on proportional-derivative (PD) control in a simulation environment wherein the manipulator has been modeled and simulated with a certain input signal and responses to various controllers have been shown. Model free and model based controllers have been designed simulated using MATLAB®/ Simulink®. Strategies like model free PD control have been improved upon by introducing auto-tuning and learning capabilities. A virtual plant modeled using Simmechanics® toolbox has been set up and used for simulation purposes. General Terms Degree of freedom, human hand articulations, serial manipulators

Comparative Study between Two Important Nonlinear Methodologies for Continuum Robot Manipulator Control

This research focuses on the basic concepts of continuum robot manipulator and control methodology. OCTARM Continuum robot manipulator is a 6 DOF serial robot manipulator. From the control point of view, robot manipulator divides into two main parts i.e. kinematics and dynamic parts. The dynamic parameters of this system are highly nonlinear. To control of this system nonlinear control methodology (computed torque controller and sliding mode controller) is introduced. Computed torque controller (CTC) is an influential nonlinear controller to certain systems which it is based on feedback linearization and computes the required arm torques using the nonlinear feedback control law. When all dynamic and physical parameters are known computed torque controller works superbly; practically a large amount of systems have uncertainties and sliding mode controller reduce this kind of limitation. Sliding mode controller (SMC) is a significant nonlinear controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for robot manipulators, because this controller is a robust and stable. Comparative study between computed torque controller and sliding mode controller is introduced in this research.

Selecting Optimal Measurement Poses for Kinematic Calibration of Industrial Robots

The robustness of robot calibration regarding the measurement noise is sensitive to the measurement poses serving as constraints on the parameters to be estimated. This paper presents a pose selection algorithm allowing one to select a given number of optimal poses out of a large set of previously measured poses, which is derived from the DETMAX algorithm with the improvements benefiting from the randomized search technique to avoid local convergence. The benefit of selecting optimal measurement poses is validated through both simulation and experimentation of calibration of a 6-dof serial robot manipulator (Hyundai robot YS100). The results show that the robot calibration with optimal measurement poses yields the global (unbiased) kinematic parameters. Thus, the robot positioning accuracy is enhanced throughout the workspace. Moreover, the experimental results indicate that the number of optimal measurement poses is as important as selecting optimal measurement poses for improving the robot calibration accuracy.

Complex Differential Evolution Algorithm for Inverse Kinematics of Spatial 6R Robot Manipulators

A 6-DOF Stautli industrial robot manipulator of TX60 type is regarded as the research object, and then nonlinear equations are constructed to solve its inverse positional problems by means of kinematics analysis. Taking the minimizing pose error of the end-effector as the objective function, this study transforms the nonlinear equations into an unconstrained optimization model and employs a differential evolution(DE) algorithm to solve this problem. To overcome the defects of the simple DE algorithm that is difficult to keep balance between the convergence accuracy and the calculation reliability, an adaptive division complex DE(ADCDE) algorithm is presented to enhance its optimizing performance. This proposed algorithm divides adaptively the population into exploitation and exploration subgroups, furthermore, the former and latter apply the DE/best/2/bin strategy and the complex operator to generate mutation individuals, respectively. With a study case for engineering application, the ADCDE algorithm is implemented to find the inverse positional solutions of a serial robot manipulator. Simulation results indicate that the presented algorithm outperforms the compared algorithms in term of computational precision and reliability, and the inverse solutions with high precision and all possible ones can be obtained by this algorithm with light calculation cost. Moreover, these results also verify the effectiveness and feasibility of this approach.

On the Manipulability of Velocity-constrained Serial Robotic Manipulators

This paper presents a performance metric for the manipulability of constrained serial manipulators. The manipulability measure and manipulability ellipsoid are found from the manipulability Jacobian, which is easily found for serial manipulators as the standard Jacobian matrix, or for parallel manipulators as the Jacobian that gives the mapping from the active joint velocities to the end-effector velocities. For serial manipulators with constraints on the kinematic chain, however, this measure is not straightforwardly found because the manipulability Jacobian cannot be found in the same way as for the cases above. In this paper we propose to use the Constrained Jacobian Matrix, i.e., an analytical mapping between the end-effector and joint velocities that also takes the chain constraints into account. This analytical representation of the Constrained Jacobian Matrix allows us to find a performance metric describing the manipulability of a serial manipulator with chain constraints in the same way as for non-constrained kinematic chains and parallel manipulators. The approach allows us to compare the manipulability of the end effector of non-constrained serial manipulators and constrained serial manipulators and we study the important case of robotics-assisted minimally invasive surgery where the arm is constrained at the entry point.

Solution of Inverse Kinematics for 6R Robot Manipulators With Offset Wrist Based on Geometric Algebra

In this paper, we present an efficient method based on geometric algebra for computing the solutions to the inverse kinematics problem (IKP) of the 6R robot manipulators with offset wrist. Due to the fact that there exist some difficulties to solve the inverse kinematics problem when the kinematics equations are complex, highly nonlinear, coupled and multiple solutions in terms of these robot manipulators stated mathematically, we apply the theory of Geometric Algebra to the kinematic modeling of 6R robot manipulators simply and generate closed-form kinematics equations, reformulate the problem as a generalized eigenvalue problem with symbolic elimination technique, and then yield 16 solutions. Finally, a spray painting robot, which conforms to the type of robot manipulators, is used as an example of implementation for the effectiveness and real-time of this method. The experimental results show that this method has a large advantage over the classical methods on geometric intuition, computation and real-time, and can be directly extended to all serial robot manipulators and completely automatized, which provides a new tool on the analysis and application of general robot manipulators.

Task-based design optimization of serial robot manipulators

In this article a direct search non-gradient design optimization method is proposed to determine the optimal task time and optimal parameters of serial robot manipulators. The design variables are treated as continuous variables associated with the motion trajectory profile and robot's link lengths and masses. The method adopted in this study can be applied to any serial redundant or non-redundant manipulator that has rigid links and known kinematic and dynamic models with free motions or motions along specified paths. Trajectory can be planned in Cartesian or joint space under kinodynamic constraints. The cost function to be minimized is weighted terms of task time and joint torques quadratic average. Examples on 3-R planar and spatial serial robot manipulators are given to illustrate the method where the kinematic and dynamic models and the optimization method are developed in MATLAB®.

A comparison of Jacobian-based methods of inverse kinematics for serial robot manipulators

The objective of this paper is to present and make a comparative study of several inverse kinematics methods for serial manipulators, based on the Jacobian matrix. Besides the well-known Jacobian transpose and Jacobian pseudo-inverse methods, three others, borrowed from numerical analysis, are presented. Among them, two approximation methods avoid the explicit manipulability matrix inversion, while the third one is a slightly modified version of the Levenberg-Marquardt method (mLM). Their comparison is based on the evaluation of a short distance approaching the goal point and on their computational complexity. As the reference method, the Jacobian pseudo-inverse is utilized. Simulation results reveal that the modified Levenberg-Marquardt method is promising, while the first order approximation method is reliable and requires mild computational costs. Some hints are formulated concerning the application of Jacobian-based methods in practice.