scholarly journals Adaptive 3D Visual Servoing of a Scara Robot Manipulator with Unknown Dynamic and Vision System Parameters

Automation ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 127-140
Author(s):  
Jorge Antonio Sarapura ◽  
Flavio Roberti ◽  
Ricardo Carelli
Keyword(s):  
Visual Servoing ◽  
Degrees Of Freedom ◽  
Moving Objects ◽  
Robot Manipulator ◽  
Vision System ◽  
Robot Dynamics ◽  
Complete Control ◽  
Scara Robot ◽  
Dynamic Controller ◽  
Control Scheme

In the present work, we develop an adaptive dynamic controller based on monocular vision for the tracking of objects with a three-degrees of freedom (DOF) Scara robot manipulator. The main characteristic of the proposed control scheme is that it considers the robot dynamics, the depth of the moving object, and the mounting of the fixed camera to be unknown. The design of the control algorithm is based on an adaptive kinematic visual servo controller whose objective is the tracking of moving objects even with uncertainties in the parameters of the camera and its mounting. The design also includes a dynamic controller in cascade with the former one whose objective is to compensate the dynamics of the manipulator by generating the final control actions to the robot even with uncertainties in the parameters of its dynamic model. Using Lyapunov’s theory, we analyze the two proposed adaptive controllers for stability properties, and, through simulations, the performance of the complete control scheme is shown.

Optimal Error-Clamping Design for Position-Based Visual Servoing of a 2-DOF Model Helicopter

2011 ◽  
Author(s):  
M. Alizadeh ◽  
C. Ratanasawanya ◽  
M. Mehrandezh ◽  
R. Paranjape
Keyword(s):  
Visual Servoing ◽  
Degrees Of Freedom ◽  
Vision System ◽  
Physical Space ◽  
Linear Quadratic Regulator ◽  
Image Plane ◽  
Reference Trajectory ◽  
Linear Quadratic ◽  
Feed Forward ◽  
Model Helicopter

A vision-based servoing technique is proposed for a 2 degrees-of-freedom (dof) model helicopter equipped with a monocular vision system. In general, these techniques can be categorized as image- and position-based, where the task error is defined in the image plane in the former and in the physical space in the latter. The 2-dof model helicopter requires a configuration-dependent feed-forward control to compensate for gravitational forces when servoing on a ground target. Therefore, a position-based visual servoing deems more appropriate for precision control. Image information collected from a ground object, with known geometry a priori, is used to calculate the desired pose of the camera and correspondingly the desired joint angles of the model helicopter. To assure a smooth servoing, the task error is parameterized, using the information obtained from the linearaized image Jacobian, and time scaled to form a moving reference trajectory. At the higher level, a Linear Quadratic Regulator (LQR), augmented with a feed-forward term and an integrator, is used to track this trajectory. The discretization of the reference trajectory is achieved by an error-clamping strategy for optimal performance. The proposed technique was tested on a 2-dof model helicopter capable of pitch and yaw maneuvers carrying a light-weight off-the-shelf video camera. The test results show that the optimized controller can servo the model helicopter to a hovering pose for an image acquisition rate of as low as 2 frames per second.

Application of non-linear H∞ control to the Tetrabot robot manipulator

1998 ◽  
Vol 212 (6) ◽  
pp. 459-465 ◽  
Author(s):  
I Postlethwaite ◽  
A Bartoszewicz
Keyword(s):  
Degrees Of Freedom ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
External Disturbances ◽  
Six Degrees Of Freedom ◽  
Control Scheme ◽  
Non Linear ◽  
Modelling Uncertainties ◽  
Real Robot ◽  
Robotic Application

In this paper, an application of a non-linear H∞ control law for an industrial robot manipulator is presented. Control of the manipulator motion is formulated into a non-linear H∞ optimization problem, namely optimal tracking performance in the presence of modelling uncertainties and external disturbances. Analytical solutions for this problem are implemented on a real robot. The robot under consideration is the six-degrees-of-freedom GEC Tetrabot. Investigations are made into the selection of weights for the H∞ controller and it is shown how different selections of weights affect the Tetrabot performance. The authors believe this to be the first robotic application of nonlinear H∞ control. Comparisons of the proposed control strategy with conventional proportional-derivative and proportional-integral-derivative controllers show favourable performance of the Tetrabot under the new non-linear H∞ control scheme.

scholarly journals Robotic Measurement and Control for Chiropractic Research

2006 ◽  
Vol 3 (1) ◽  
pp. 43-48 ◽  
Author(s):  
P. Goldsmith ◽  
S. Wynd ◽  
G. Kawchuk
Keyword(s):  
Robot Manipulator ◽  
Vision System ◽  
Parallel Robot ◽  
Calibration Procedure ◽  
Positional Accuracy ◽  
Experimental Procedure ◽  
Control Scheme ◽  
And Control ◽  
Measurement And Control ◽  
Chiropractic Research

The precision and programmability of robotic manipulators makes them suitable for biomechanics research, particularly when an experimental procedure must be accurately repeated multiple times. This paper describes a robotic system used to investigate biomechanical mechanisms of stroke in humans. A parallel robot manipulator is used to reproduce chiropractic manipulations on animal subjects using a 3-D vision system. An algorithm for calibrating the system is proposed and tested on the robot. An iterative learning control scheme is then introduced to improve positional accuracy. Experimental results demonstrate that the calibration procedure and learning scheme are both effective.

scholarly journals Neural Networks-based Adaptive State Feedback Control of Robot Manipulators

2007 ◽  
Vol 2 (4) ◽  
pp. 328 ◽  
Author(s):  
Ghania Debbache ◽  
Abdelhak Bennia ◽  
Noureddine Goléa
Keyword(s):  
Neural Networks ◽  
State Feedback ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
External Disturbance ◽  
Nonlinear Function ◽  
State Feedback Control ◽  
Robot Dynamics ◽  
Robust Controller ◽  
Control Scheme

This paper proposes an adaptive control suitable for motion control of robot manipulators with structured and unstructured uncertainties. In order to design an adaptive robust controller, with the ability to compensate these uncertainties, we use neural networks (NN) that have the capability to approximate any nonlinear function over a compact space. In the proposed control scheme, we need not derive the linear formulation of robot dynamic equation and tune the parameters. To reduce the NNs complexity, we consider the properties of robot dynamics and the decomposition of the uncertainties terms. The proposed controller is robust against uncertainties and external disturbance. The validity of the control scheme is demonstrated by computer simulations on a two-link robot manipulator.

Robust position-force control of robot manipulator in contact with linear dynamic environment

Robotica ◽  
2005 ◽  
Vol 23 (6) ◽  
pp. 799-803 ◽  
Author(s):  
Branko Karan
Keyword(s):  
Robot Manipulator ◽  
Dynamic Environment ◽  
Interaction Force ◽  
Robot Dynamics ◽  
Boundary Values ◽  
Interaction Forces ◽  
Simultaneous Control ◽  
Control Scheme ◽  
Constant Coefficients ◽  
Environment Parameters

The paper presents a control scheme for simultaneous control of position and force of robot manipulator in contact with an elastodynamic environment. The control makes the assumption that interaction force between the robot and environment is adequately modeled by a second-order linear model with constant coefficients, and its implementation requires the knowledge of only boundary values of the environment parameters. It is shown that, provided that robot dynamics is exactly modeled, the scheme ensures asymptotic convergence of errors along nominal trajectories characterized by constant prescribed interaction forces and constant prescribed velocities along the contact surface.

scholarly journals Nonlinear pd controllers with gravity compensation for robot manipulators

2014 ◽  
Vol 14 (1) ◽  
pp. 141-150 ◽  
Author(s):  
Jianfeng Huang ◽  
Chengying Yang ◽  
Jun Ye
Keyword(s):  
Degrees Of Freedom ◽  
Position Control ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Nonlinear Function ◽  
Step Response ◽  
Robot Dynamics ◽  
Gravity Compensation ◽  
Pd Controller ◽  
Globally Asymptotically Stable

Abstract A Nonlinear Proportional-Derivative (NPD) controller with gravity compensation is proposed and applied to robot manipulators in this paper. The proportional and derivative gains are changed by the nonlinear function of errors in the NPD controller. The closed-loop system, composed of nonlinear robot dynamics and NPD controllers, is globally asymptotically stable in position control of robot manipulators. The comparison of the simulation experiments in the position control (the step response) of a robot manipulator with two degrees of freedom is also presented to illustrate that the NPD controller is superior to the conventional PD controller in a position control system. The experimental results show that the NPD controller can obtain a faster response velocity and higher position accuracy than the conventional PD controller in the position control of robot manipulators because the proportional and derivative gains of the NPD controller can be changed by the nonlinear function of errors. The NPD controller provides a novel approach for robot control systems.

scholarly journals Forward Models Applied in Visual Servoing for a Reaching Task in the iCub Humanoid Robot

2009 ◽  
Vol 6 (3-4) ◽  
pp. 345-354 ◽  
Author(s):  
Daniel Fernando Tello Gamarra ◽  
Lord Kenneth Pinpin ◽  
Cecilia Laschi ◽  
Paolo Dario
Keyword(s):  
Visual Servoing ◽  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Vision System ◽  
Forward Model ◽  
Initial Image ◽  
Reaching Task ◽  
New Information ◽  
Image Jacobian ◽  
Simulation Results

This paper details the application of a forward model to improve a reaching task. The reaching task must be accomplished by a humanoid robot with 53 degrees of freedom (d.o.f.) and a stereo-vision system. We have explored via simulations a new way of constructing and utilizing a forward model that encodes eye–hand relationships. We constructed a forward model using the data obtained from only a single reaching attempt. ANFIS neural networks are used to construct the forward model, but the forward model is updated online with new information that comes from each reaching attempt. Using the obtained forward model, an initial image Jacobian is estimated and is used with a visual servoing controller. Simulation results demonstrate that errors are lower when the initial image Jacobian is derived from the forward model. This paper is one of the few attempts at applying visual servoing in a complete humanoid robot.

scholarly journals Using FPGA Design and HIL Algorithm Simulation to Control Visual Servoing

2018 ◽  
Vol 6 (2) ◽  
pp. 111
Author(s):  
Lway Faisal Abdulrazak ◽  
Zaid A. Aljawary
Keyword(s):  
Object Tracking ◽  
Visual Servoing ◽  
Degrees Of Freedom ◽  
Optimal Solution ◽  
Robot Dynamics ◽  
Fpga Design ◽  
Joint Torques ◽  
Array Technology ◽  
Gate Array ◽  
Set Up

<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">This is a novel research paper provides an optimal solution for object tracking using visual servoing control system with programmable gate array technology to realize the visual controller. The controller takes in account the robot dynamics to generate the joint torques directly for performing the tasks related to object tracking using visual servoing. Also, the notion of dynamic perceptibility provides the capability of the designed system to track desired objects employing direct visual servoing technique. This idea is assimilated in the suggested controller and realized in the programmable gate array. Additionally, this paper grants an ideal control framework for direct visual servoing robots that incorporates dynamic perceptibility features. With the aim of evaluating the proposed FPGA based architecture, the control algorithm is applied to Hardware-in-the-loop simulation (HIL) set up of three degrees of freedom rigid robotic manipulator with three links. Furthermore, different investigations are performed to demonstrate the behavior of the proposed system when a trajectory adjacent to a singularity is attained.</span>

scholarly journals Optimal Image-Based Guidance of Mobile Manipulators using Direct Visual Servoing

Electronics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 374 ◽  
Author(s):  
Álvaro Belmonte ◽  
José Ramón ◽  
Jorge Pomares ◽  
Gabriel Garcia ◽  
Carlos Jara
Keyword(s):  
Visual Servoing ◽  
Degrees Of Freedom ◽  
Mobile Manipulator ◽  
Robot Dynamics ◽  
Mobile Manipulators ◽  
Control Force ◽  
Robot Arm ◽  
Dynamical Behaviors ◽  
Control Framework ◽  
Image Trajectories

This paper presents a direct image-based controller to perform the guidance of a mobile manipulator using image-based control. An eye-in-hand camera is employed to perform the guidance of a mobile differential platform with a seven degrees-of-freedom robot arm. The presented approach is based on an optimal control framework and it is employed to control mobile manipulators during the tracking of image trajectories taking into account robot dynamics. The direct approach allows us to take both the manipulator and base dynamics into account. The proposed image-based controllers consider the optimization of the motor signals sent to the mobile manipulator during the tracking of image trajectories by minimizing the control force and torque. As the results show, the proposed direct visual servoing system uses the eye-in-hand camera images for concurrently controlling both the base platform and robot arm. The use of the optimal framework allows us to derive different visual controllers with different dynamical behaviors during the tracking of image trajectories.

scholarly journals Robust Control of Robot Manipulator based on QFT and H∞

2022 ◽  
Vol 16 ◽  
pp. 17-22
Author(s):  
J. J. Carreño ◽  
R. Villamizar
Keyword(s):  
Pid Controller ◽  
Degrees Of Freedom ◽  
Robot Manipulator ◽  
Parametric Uncertainty ◽  
Robot Dynamics ◽  
Robust Controllers ◽  
Control Techniques ◽  
Behavioral Indices ◽  
6 Degrees Of Freedom ◽  
Control Methodology

Robust controllers have been developed by both control techniques QFT and H∞ applied in the waist, shoulder and elbow of a manipulator of 6 degrees of freedom. The design is based on the identification of a linear model of the robot dynamics which represents the non-linearity of the system using parametric uncertainty. QFT control methodology is used to tune the robust PID-controller and pre-filters of the system, and H∞ controllers are obtained by designing the weighting functions and using the MATLAB hinfopt tool. Finally the performance of robust controllers is compared designed based on the calculation and analysis of some behavioral indices.

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