Degrees Of Freedom Robot Manipulator Research Articles

A Robotic Platform for 3D Forelimb Rehabilitation with Rats.

In an attempt to promote greater functional recovery after spinal cord injury, researchers have begun exploring combinatorial treatments, such as robotic rehabilitation combined with stem cell transplantation. Since these treatment methods are in their nascent stages, rodent models have been proposed for initial investigations. Robots have been built for locomotion rehabilitation and planar forelimb reach and grasp assessment with rodents; however, a robotic platform suitable for three-dimensional movement rehabilitation of the rodent forelimb has not yet been developed. In this paper, a novel three degree of freedom robotic manipulator for automated forelimb rehabilitation combined with stem cell transplantation after cervical spinal cord injury with rats is proposed. The robot interfaces with a rat in an end-effector manner, measuring and interacting with the forelimb in the 3D Cartesian space. In this work, we trained two rats through behavioral shaping to actively interact with the device during two robot control modes. This work provides preliminary investigations into the feasibility of 3D forelimb rehabilitation with rats, which could be translated as a paradigm for combinatorial treatments after spinal cord injury in a controlled manner.

Path Planning of Complex Pipe Joints Welding with Redundant Robotic Systems

SummaryIn this paper, a path planning algorithm for robotic systems with excess degrees of freedom (DOF) for welding of intersecting pipes is presented. At first step, the procedure of solving the inverse kinematics considering system kinematic redundancy is developed. The robotic system consists of a 6 DOF robotic manipulator installed on a railed base with linear motion. Simultaneously, the main pipe is able to rotate about its longitudinal axis. The system redundancy is employed to improve weld quality. Three different simulation studies are performed to show the effect of the robotic system kinematic redundancy to plan a better path for the welding of intersecting pipes. In the first case, it is assumed that robotic manipulator base and main pipe are fixed, and the path is planned only with manipulator joints motion. In the second case, only the robot base is free to move and the main pipe is fixed, and in the third case, the main pipe is free to rotate together with the base of the manipulator. It is seen that kinematic constraints according to the system’s redundancy will help to plan the most efficient path for the welding of complex pipe joints.

Development and analysis of a five degrees of freedom robotic manipulator serving as a goalkeeper to train the football players

The need of the robotic manipulators in different zones such as medical, industrial, academic and sports are available in the literatures and discussed. In the sports field like cricket, football, tennis, badminton different robotic manipulators have been used to train the players for betterment and to enhance the efficiency of the players. Football is one of the most popular game played internationally. But in the game of football we have limited invention of the robotic manipulator to train the players. Therefore, in this work the study of the development of a robotic manipulator is presented which will serve as a goalkeeper. The studied robotic manipulator has six numbers of link which is connected to the different joints and possessing five degrees of freedom. This robotic manipulator tried to defend the ball to enter the court and the simulation results and its performance have been presented here. The study will mostly be focused on the dynamics of proposed robotic manipulator using “Newton-Euler” method, “Euler-Lagrange” method and “Decoupled Natural Orthogonal Complement” (DeNOC). Due to the complexity and time consuming of Newton-Euler method and Euler-Lagrange method, the recursive Decoupled Natural Orthogonal Complement is used for the dynamic analysis and the comparison between these three methods are presented here. The effectiveness and performance of the proposed robotic manipulator with the help of different complex trajectories is presented in this work. It is found from the analysis that the proposed manipulator can be applied for the training purpose of players.

Tracking control of uncertain time delay systems: An ADRC approach

This article deals with the control of a class of robotic systems with constant input time delay through the Active Disturbance Rejection paradigm, by means of Generalized Proportional Integral observers. The system is represented as a linear perturbed system, whose lumped disturbance input is estimated and then compensated by an Extended State Observer-Based Control, which is implemented on a predictor scheme for the time delay compensation. A complete Lyapunov Krasovskii functional was used to perform the stability analysis, leading to an ultimate bound trajectory tracking error. The proposal is tested and validated on a two degrees of freedom robotic manipulator.

Design of a fractional-order adaptive integral sliding mode controller for the trajectory tracking control of robot manipulators

In this study, trajectory tracking control of six–degrees of freedom robotic manipulator has been performed using the proposed fractional-order adaptive integral sliding mode control scheme. The proposed method is first composed by fractional-order and adaptive integral sliding mode control to achieve the finite-time convergence, chattering-free control inputs, better tracking performance and robustness for the robotic manipulator. Furthermore, an adaptive method has been utilized to evaluate and compensate the uncertain and unknown dynamics of the system without relying on the prior knowledge of the upper bounds. To illustrate the efficiency of the proposed fractional-order adaptive integral sliding mode control method, the real-time experimental studies have been performed for the six–degrees of freedom industrial robot manipulator. The experimental outcomes strongly verified that the proposed controller gives quite well trajectory tracking response and faster convergence compared with the classical integral sliding mode control under the external payload.

Synthesis of the Decentralized Control System for Robot-Manipulator with Input Saturations

It is discussed the problem of synthesis of the decentralized adaptive-periodic control system for two degrees of freedom robotic manipulator which have an input limitations. The solution of the problem is based on the use of hyperstability criterion, L-dissipativity conditions and dynamic filter-corrector.

Optimal and Robust Control of Multi DOF Robotic Manipulator: Design and Hardware Realization

ABSTRACTRobots have become an integral part of industrial automation. Their ultimate role and contribution in this sector is essentially a function of the associated control strategy to ensure precision, repeatability, and reliability, particularly in an environment polluted with disturbances and uncertainties. This research aims to present a design of the modern control strategies for a 6 degree of freedom robotic manipulator. Based on derived kinematic and dynamic models of the robot, optimal and robust control strategies are simulated and practically realized on a custom developed pseudo-industrial framework named as AUTonomous Articulated Robotic Educational Platform. Results of the experimental trials in terms of trajectory tracking demonstrate efficiency and usefulness of the presented control approaches.

The imaging algorithm for the ultrasonic testing of metal castings by the application of automated testing systems based on a six degree of freedom robotic manipulators

Complex-shaped surface represents one of the challenges in ultrasonic testing of metal castings. This conditions the growing interest in development and application of the automated testing system based on a six degree of freedom (DOF) robotic manipulators. This is due to their ability to provide ultrasonic scanning of the curved specimens with high speed. Higher reliability of the results can be obtained via implementation of the imaging algorithms based on Synthetic Aperture Focusing Technique (SAFT) in the named systems. This approach allows to obtain high-resolution imagery of the internal structure of controlled objects with reduced level of grain noise, the latter occurs due to the often encountered coarse-grained structure of metal castings.� In this paper, we introduce the novel imaging algorithm for the automated ultrasonic testing system based on a six degree of freedom robotic manipulator. The capabilities of the algorithm were verified by the application of computer simulations in CIVA 2016 software and also via the in situ experiments. In all the cases analyzed the results revealed that the imaging algorithm allows to make precise imagery of the internal structure of the specimens with different curvature. The obtained research results confirmed the suggested algorithm effectiveness, thus making it acceptable for prospective industrial applications.

Adaptive Neural Network Control of a Robotic Manipulator With Time-Varying Output Constraints.

The control problem of an uncertain n -degrees of freedom robotic manipulator subjected to time-varying output constraints is investigated in this paper. We describe the rigid robotic manipulator system as a multi-input and multi-output nonlinear system. We devise a disturbance observer to estimate the unknown disturbance from humans and environment. To solve the uncertain problem, a neural network which utilizes a radial basis function is used to estimate the unknown dynamics of the robotic manipulator. An asymmetric barrier Lyapunov function is employed in the process of control design to avert the contravention of the time-varying output constraints. Simulation results validate the validity of the presented control scheme.

Improvement of a Robotic Manipulator Model Based on Multivariate Residual Modeling

A new method is presented for extending an incomplete mathematical model - in this case a dynamic model of a six degrees of freedom robotic manipulator. A nonlinear multivariate calibration of input-output training data from several typical motion trajectories is carried out with the aim of predicting the model systematic output error at time (t+1) from known input reference up till and including time (t). A new partial least squares regression (PLSR) based method, nominal PLSR with interactions was developed and used to handle, unmodelled nonlinearities. The performance of the new method is compared with least squares (LS). Different cross-validation schemes were compared in order to assess the sampling of the state space based on conventional trajectories. The method developed in the paper can be used as fault monitoring mechanism and early warning system for sensor failure. The results show that the suggested methods improves trajectory tracking performance of the robotic manipulator by extending the initial dynamic model of the manipulator.

Robust impedance control of robot manipulators using differential equations as universal approximator

ABSTRACTThis paper presents a robust impedance controller for robot manipulators using function approximation techniques (FATs). Recently, some FAT-based robust impedance control approaches have been presented using Fourier series expansion or Legendre polynomials for uncertainty estimation. However, the dimensions of regressor matrices in these approaches are relatively large. This problem becomes hypersensitive especially for higher degree of freedom robot manipulators. In this paper, a simpler and less computational FAT-based robust controller is presented without considering discontinuous nonlinearities. It is assumed that the lumped uncertainty can be modelled by a linear differential equation with unknown coefficients. Then, using the Stone–Weierstrass theorem, it is verified that these differential equations are universal approximators. The advantage of the proposed controller in comparison with previous related works is reducing the dimensions of regressor matrices. Simulation results on a Puma560 robot manipulator indicate the efficiency of the proposed method.

Design optimization method for 7 DOF robot manipulator using performance indices

This paper proposes an optimal design method for the design parameters that affect the performance of 7 degrees of freedom (DOF) serial manipulators. The proposed method optimizes the manipulator parameters by using performance indices related to the distribution of inertia, while considering the workspaces and dexterity that correspond to the kinematic performance, and the energy that corresponds to the dynamic performance. The Structural Length Index (SLI) and Global Conditioning Index (GCI), which are kinematic performance indices, and the Modified Dynamic Conditioning Index (MDCI), which is a dynamic performance index, were used as objective functions. After deriving the parameters that affect manipulator performance through these performance indices, a Genetic Algorithm was used for the optimization. This method should be helpful in theoretically designing those parameters that have been created by relying on experience, thus far, in the initial conceptual design stage in 7 DOF manipulator designs.

Precision contouring control of five degree of freedom robot manipulators with uncertainty

In this article, we apply a result in equivalent errors to a contouring control problem of five degree of freedom robot manipulators. The proposed technique, fuzzy Proportional Integral Derivative (PID) with the robust extended Kalman filter, is employed to stabilize the dynamic of equivalent errors of robot manipulators. The shape of membership functions and rules of fuzzy PID controller are tuned following operating conditions that make the control performance to improve significantly. A desired path in terms of the position of the end-effector of the robot manipulators is described in generalized coordinates defined by the dynamic of equivalent. The simulation and experimental results demonstrate the excellent performance of the proposed technique.

Accuracy analysis of geometrical and numerical approaches for two degrees of freedom robot manipulator

Analysis of algorithms to determine the accuracy of aiming direction using two inverse kinematic approaches i.e. geometric and numeric has been done. The best method needs to be specified to precisely and accurately control the aiming direction of a two degrees of freedom (TDOF) manipulator. The manipulator degrees of freedom are azimuth (Az) and elevation (El) angles. A program has been made using C language to implement the algorithm. Analysis of the two algorithms was done using statistical approach and circular error probable (CEP). The research proves that accuracy percentage of numerical method is better than geometrical method, those are 98.63% and 98.55%, respectively. Based on the experiment results, the numerical approach is the right algorithm to be applied in the TDOF robot manipulator.

Performance Analysis of An Experimental Micro Flexible Manufacturing System (FMS)

Due to advanced technology, it is very important the performance of FMS for sensivity, production quality, repeatability and energy consumptions. Flexible manufacturing systems (FMSs) are the most automated and technologically sophisticated of the machine cell types used to implement cellular manufacturing. An FMS usually has multiple automated stations and is capable of variable routings among stations, while its flexibility allows it to operate as a mixed model system. The FMS concept integrates many of the advanced technologies that we met in previous units, including flexible automation, CNC machines, distributed computer control, and automated material handling and storage.
 In this experimental investigation, vibration and accelerations analysis of an experimental FMS with 5 degrees of freedom robot manipulator are presented. Firstly, experimental measurement of accelerations and vibrations are trained with a vibration measurement system and sensors. However, the process of production of part is a cycle of exact production time.

Development of an embedded control system by means of dsPIC applied in a 4 DOF robot

In this paper the design and implementation of an embedded control system, using DSCs (Digital Signal Controller) devices of dsPIC type, applied on a four DOF (Degrees Of Freedom) robotic manipulator OWI-535 model is presented. The mathematical model of manipulator is elaborated obtaining joint trajectories to achieve the tracking of a test Cartesian trajectory. A control structure based on a Master/Slave configuration, between two dsPIC30F4013 through SPI (Serial Peripheral Interface) protocol is developed. In such a system, algorithms are implemented: PID (Proportional Integral Derivative) with anti-windup and, generation PWM (Pulse-Width Modulation) and data acquisition, in the DSCs master and slave, respectively. The results are exposed by comparative curves between the desired and real joint trajectories and joint error graphs, generated from real data of the implementation.

Posterior Tibial Slope Angle Correlates With Peak Sagittal and Frontal Plane Knee Joint Loading During Robotic Simulations of Athletic Tasks

Background: Tibial slope angle is a nonmodifiable risk factor for anterior cruciate ligament (ACL) injury. However, the mechanical role of varying tibial slopes during athletic tasks has yet to be clinically quantified. Purpose: To examine the influence of posterior tibial slope on knee joint loading during controlled, in vitro simulation of the knee joint articulations during athletic tasks. Study Design: Descriptive laboratory study. Methods: A 6 degree of freedom robotic manipulator positionally maneuvered cadaveric knee joints from 12 unique specimens with varying tibial slopes (range, −7.7° to 7.7°) through drop vertical jump and sidestep cutting tasks that were derived from 3-dimensional in vivo motion recordings. Internal knee joint torques and forces were recorded throughout simulation and were linearly correlated with tibial slope. Results: The mean (±SD) posterior tibial slope angle was 2.2° ± 4.3° in the lateral compartment and 2.3° ± 3.3° in the medial compartment. For simulated drop vertical jumps, lateral compartment tibial slope angle expressed moderate, direct correlations with peak internally generated knee adduction (r = 0.60-0.65), flexion (r = 0.64-0.66), lateral (r = 0.57-0.69), and external rotation torques (r = 0.47-0.72) as well as inverse correlations with peak abduction (r = −0.42 to −0.61) and internal rotation torques (r = −0.39 to −0.79). Only frontal plane torques were correlated during sidestep cutting simulations. For simulated drop vertical jumps, medial compartment tibial slope angle expressed moderate, direct correlations with peak internally generated knee flexion torque (r = 0.64-0.69) and lateral knee force (r = 0.55-0.74) as well as inverse correlations with peak external torque (r = −0.34 to −0.67) and medial knee force (r = −0.58 to −0.59). These moderate correlations were also present during simulated sidestep cutting. Conclusion: The investigation supported the theory that increased posterior tibial slope would lead to greater magnitude knee joint moments, specifically, internally generated knee adduction and flexion torques. Clinical Relevance: The knee torques that positively correlated with increased tibial slope angle in this investigation are associated with heightened risk of ACL injury. Therefore, the present data indicated that a higher posterior tibial slope is correlated to increased knee loads that are associated with heightened risk of ACL injury.

Autonomous robotic capture of non-cooperative target by adaptive extended Kalman filter based visual servo

This paper presents a real-time, vision-based algorithm for the pose and motion estimation of non-cooperative targets and its application in visual servo robotic manipulator to perform autonomous capture. A hybrid approach of adaptive extended Kalman filter and photogrammetry is developed for the real-time pose and motion estimation of non-cooperative targets. Based on the pose and motion estimates, the desired pose and trajectory of end-effector is defined and the corresponding desired joint angles of the robotic manipulator are derived by inverse kinematics. A close-loop visual servo control scheme is then developed for the robotic manipulator to track, approach and capture the target. Validating experiments are designed and performed on a custom-built six degrees of freedom robotic manipulator with an eye-in-hand configuration. The experimental results demonstrate the feasibility, effectiveness and robustness of the proposed adaptive extended Kalman filter enabled pose and motion estimation and visual servo strategy.

Globalized Dual Heuristic Dynamic Programming in Control of Robotic Manipulator

The article focuses on the implementation of the globalized dual-heuristic dynamic programming algorithm in the discrete tracking control system of the three degrees of freedom robotic manipulator. The globalized dual-heuristic dynamic programming algorithm is included in the approximate dynamic programming algorithms family, that bases on the Bellman’s dynamic programming idea. These algorithms generally consist of the actor and the critic structures realized in a form of artificial neural networks. Moreover, the control system includes the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis, which was realized using the Lyapunov stability theorem. The control system works on-line and the neural networks’ weight adaptation process is realized in every iteration step. A series of computer simulations was realized in Matlab/Simulink software to confirm performance of the control system.

Control Algorithms for Robot Manipulator

The subject of this work is to develop a control system for the two degree of freedom robot manipulator. Manipulators play an increasingly important role not only in flexible automation production systems but also in medicine and rehabilitation process [3]. High-speed and high-precision trajectory tracking are indispensable capabilities for versatile applications of manipulators. Even in well-known industrial applications manipulators are characterized by structural and / or unstructured uncertainty. Through structural uncertainty we miss a situation in which we have a dynamic model of the object, but because of the uncertainty unknown parameters such as load, inaccuracies in constant torque actuators etc. to create a properly working control system is a difficult issue. In contrast, unstructured uncertainty is related to the unknown of the dynamic model, which may be due to many reasons such as the presence of high-frequency modes of the manipulator, neglected time-delays, nonlinear friction etc. In this case, when the dynamic model of the system is not known a priori (or not available), the system must first be identified, then the control law is developed based on the estimated model [5, [6[7].These problems cause that it is very difficult to find good control system but simple. In this case, the different algorithms for control system of the manipulator was proposed. The first classical PD controller was tested. Next the system design for PD controller with compensation of gravitational forces.