Planning of Dynamic Compensation Manipulator Motions for Stability Enhancement of Mobile Manipulators by Soft Computing

2006 ◽  
Author(s):  
Ali Ghaffari ◽  
Ali Meghdari ◽  
Davood Naderi ◽  
Sohrab Eslami
Keyword(s):  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Pd Controller ◽  
Robot System ◽  
End Effector ◽  
Compensatory Motion ◽  
Stability Issue ◽  
Optimal Values ◽  
The Stability ◽  
Stability Enhancement

Mobile manipulators are developed in order to execute separately in various regions where there is not possibility for human to appear there. Recently, the size of mobile manipulators has been decreased according to their given tasks. For such systems, the stability issue is very important. The robot system should be able to keep itself in an optimal situation. For reaching to this goal, one can use a redundant degree of freedom for the mobile manipulator such that this redundancy makes it possible to recover the system's stability by dynamic compensatory motion of manipulator when the system is unstable. In this paper, we present an algorithm which is fast enough to stabilize the mobile manipulator with the best stability criterion based on a neural network and genetic algorithm which cooperate together. For applying the optimal values as the algorithm outputs to the appropriate joints, a PD controller is used. The significance of this algorithm is provided for a spatial mobile manipulator with a predefined trajectory of the end-effector and the vehicle.

Cooperation and Null-Space Control of Networked Omni-Directional Mobile Manipulators

2020 ◽  
Author(s):  
Michael John Chua ◽  
Yen-Chen Liu
Keyword(s):  
Degrees Of Freedom ◽  
Null Space ◽  
Kinematic Model ◽  
Mobile Manipulator ◽  
Main Task ◽  
Mobile Manipulators ◽  
Robot Arm ◽  
Task Space ◽  
End Effector ◽  
Mobile Base

Abstract This paper presents cooperation and null-space control for networked mobile manipulators with high degrees of freedom (DOFs). First, kinematic model and Euler-Lagrange dynamic model of the mobile manipulator, which has an articulated robot arm mounted on a mobile base with omni-directional wheels, have been presented. Then, the dynamic decoupling has been considered so that the task-space and the null-space can be controlled separately to accomplish different missions. The motion of the end-effector is controlled in the task-space, and the force control is implemented to make sure the cooperation of the mobile manipulators, as well as the transportation tasks. Also, the null-space control for the manipulator has been combined into the decoupling control. For the mobile base, it is controlled in the null-space to track the velocity of the end-effector, avoid other agents, avoid the obstacles, and move in a defined range based on the length of the manipulator without affecting the main task. Numerical simulations have been addressed to demonstrate the proposed methods.

Mission Design of Mobile Manipulators in Cluttered Environments for Service Applications

2020 ◽  
pp. 1358-1376
Author(s):  
Elias K. Xidias ◽  
Philip N. Azariadis ◽  
Nikos A. Aspragathos
Keyword(s):  
Inverse Image ◽  
Mission Design ◽  
Mobile Manipulator ◽  
Indoor Environments ◽  
Mobile Manipulators ◽  
Higher Dimension ◽  
End Effector ◽  
Cluttered Environments ◽  
Cost Simulation ◽  
The Given

The purpose of this paper is to present a mission design approach for a service mobile manipulator which is moving and manipulating objects in partly known indoor environments. The mobile manipulator is requested to pick up and place objects on predefined places (stations). The proposed approach is based on the Bump-Surface concept to represent robot's environment through a single mathematical entity. The solution of the mission design problem is searched on a higher dimension Bump-Surface in such a way that its inverse image into the actual robot environment satisfies the given objectives and constraints. The problem's objectives consist of determining the best feasible paths for both the mobile platform and for the manipulator's end-effector so that all the stations are served at the lowest possible cost. Simulation examples are presented to show the effectiveness of the presented approach.

scholarly journals Planning of Collision-Free Trajectory for Mobile Manipulators

2013 ◽  
Vol 18 (2) ◽  
pp. 475-489
Author(s):  
G. Pająk
Keyword(s):  
Mobile Manipulator ◽  
Reference Trajectory ◽  
Mobile Manipulators ◽  
Redundancy Resolution ◽  
Task Space ◽  
End Effector ◽  
Acceleration Level ◽  
Manipulability Measure ◽  
And Control ◽  
Penalty Function Approach

A method of planning sub-optimal trajectory for a mobile manipulator working in the environment including obstacles is presented. The path of the end-effector is defined as a curve that can be parameterized by any scaling parameter, the reference trajectory of a mobile platform is not needed. Constraints connected with the existence of mechanical limits for a given manipulator configuration, collision avoidance conditions and control constraints are considered. The motion of the mobile manipulator is planned in order to maximize the manipulability measure, thus to avoid manipulator singularities. The method is based on a penalty function approach and a redundancy resolution at the acceleration level. A computer example involving a mobile manipulator consisting of a nonholonomic platform and a SCARA type holonomic manipulator operating in a two-dimensional task space is also presented.

A Methodology for tele-operating mobile manipulators with an emphasis on operator ease of use

Robotica ◽  
2012 ◽  
Vol 31 (3) ◽  
pp. 331-344 ◽  
Author(s):  
M. Frejek ◽  
S. B. Nokleby
Keyword(s):  
Degrees Of Freedom ◽  
Ease Of Use ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Test Results ◽  
End Effector ◽  
Optimization Routine ◽  
Singular Configuration ◽  
6 Degrees Of Freedom ◽  
Mobile Base

SUMMARYAn algorithm for the tele-operation of mobile-manipulator systems with a focus on ease of use for the operator is presented. The algorithm allows for unified, intuitive, and coordinated control of mobile manipulators. It consists of three states. In the first state, a single 6-degrees-of-freedom (DOF) joystick is used to control the manipulator's position and orientation. The second state occurs when the manipulator approaches a singular configuration, resulting in the mobile base moving in a manner so as to keep the end-effector travelling in its last direction of motion. This is done through the use of a constrained optimization routine. The third state is entered when the operator returns the joystick to the home position. Both the mobile base and manipulator move with respect to one another keeping the end-effector stationary and placing the manipulator into an ideal configuration. The algorithm has been implemented on an 8-DOF mobile manipulator and the test results show that it is effective at moving the system in an intuitive manner.

Task space control of mobile manipulators

Robotica ◽  
2010 ◽  
Vol 29 (2) ◽  
pp. 221-232 ◽  
Author(s):  
Mirosław Galicki
Keyword(s):  
State Constraints ◽  
Lyapunov Stability Theory ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Minimal Energy ◽  
Task Space ◽  
End Effector ◽  
Task Space Control ◽  
Simulation Results ◽  
Penalty Function Approach

SUMMARYThis study offers the solution of the end-effector trajectory tracking problem subject to state constraints, suitably transformed into control-dependent ones, for mobile manipulators. Based on the Lyapunov stability theory, a class of controllers fulfilling the above constraints and generating the mobile manipulator trajectory with (instantaneous) minimal energy, is proposed. The problem of manipulability enforcement is solved here based on an exterior penalty function approach which results in continuous mobile manipulator controls even near boundaries of state constraints. The numerical simulation results carried out for a mobile manipulator consisting of a non-holonomic unicycle and a holonomic manipulator of two revolute kinematic pairs, operating in a two-dimensional task space, illustrate the performance of the proposed controllers.

scholarly journals Adaptive neural PD controllers for mobile manipulator trajectory tracking

2021 ◽  
Vol 7 ◽  
pp. e393
Author(s):  
Jesus Hernandez-Barragan ◽  
Jorge D. Rios ◽  
Javier Gomez-Avila ◽  
Nancy Arana-Daniel ◽  
Carlos Lopez-Franco ◽  
...  
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Poor Performance ◽  
Industrial Applications ◽  
Mobile Manipulator ◽  
Pid Controllers ◽  
Mobile Manipulators ◽  
Pd Controller ◽  
Adaptive Neuron ◽  
State Error

Artificial intelligence techniques have been used in the industry to control complex systems; among these proposals, adaptive Proportional, Integrative, Derivative (PID) controllers are intelligent versions of the most used controller in the industry. This work presents an adaptive neuron PD controller and a multilayer neural PD controller for position tracking of a mobile manipulator. Both controllers are trained by an extended Kalman filter (EKF) algorithm. Neural networks trained with the EKF algorithm show faster learning speeds and convergence times than the training based on backpropagation. The integrative term in PID controllers eliminates the steady-state error, but it provokes oscillations and overshoot. Moreover, the cumulative error in the integral action may produce windup effects such as high settling time, poor performance, and instability. The proposed neural PD controllers adjust their gains dynamically, which eliminates the steady-state error. Then, the integrative term is not required, and oscillations and overshot are highly reduced. Removing the integral part also eliminates the need for anti-windup methodologies to deal with the windup effects. Mobile manipulators are popular due to their mobile capability combined with a dexterous manipulation capability, which gives them the potential for many industrial applications. Applicability of the proposed adaptive neural controllers is presented by simulating experimental results on a KUKA Youbot mobile manipulator, presenting different tests and comparisons with the conventional PID controller and an existing adaptive neuron PID controller.

Optimal stability of a redundant mobile manipulator via genetic algorithm

Robotica ◽  
2006 ◽  
Vol 24 (6) ◽  
pp. 739-743 ◽  
Author(s):  
Ali Meghdari ◽  
Davood Naderi ◽  
Sohrab Eslami
Keyword(s):  
Genetic Algorithm ◽  
Angular Velocity ◽  
Angular Acceleration ◽  
Mobile Manipulator ◽  
Optimal Position ◽  
Optimal Stability ◽  
Engineering Problems ◽  
Stability Issue ◽  
Genetic Algorithm Approach ◽  
The Stability

Once the path of the vehicle and the desired task of the end-effector are predefined, in order to apply the optimal stability criterion, the manipulator should be redundant. In this paper, the goal is to find the position, angular velocity, and angular acceleration of the redundant link of the manipulator such that the entire system becomes optimally stable. By considering the full dynamic interaction between the manipulator and its vehicle, the stability issue becomes more complex. There are some measures of stability and one of them is the tire's upward force. This measure tries to equalize the upward forces of the tires that lead to optimal stability and better steer-ability. Optimizing the parameters of various engineering problems is a challenging issue. In this research, the optimal position, angular velocity, and angular acceleration of the redundant link are found by the genetic algorithm approach such that the upward forces of vehicle tires are nearly equal. Furthermore, the effectiveness of this procedure is shown by presenting an example.

Extended RMRC and its Application to the Motion of a Mobile Manipulator

2015 ◽  
Vol 12 (02) ◽  
pp. 1550016 ◽  
Author(s):  
Nak Yong Ko
Keyword(s):  
Simple Form ◽  
Rate Control ◽  
Mobile Manipulator ◽  
Robot System ◽  
End Effector ◽  
Joint Motions ◽  
Mobile Base

This paper proposes a method calculating joint velocities of a robot which moves the end effector at desired velocity where some of the joint motions are constrained. It is an extension of the Resolved Motion Rate Control (RMRC) method which has been used in cases where there is no constraint on the motion of the joints. The proposed method is called the extended RMRC (E-RMRC). Though the E-RMRC is expressed in a simple form, application of the E-RMRC to a specific robot system is not straightforward and sometimes calls for elaboration. So, the paper describes the application of the E-RMRC to the motion of a mobile manipulator. The example explains how the proposed method is applied to find the joint rate to move the end effector of the mobile manipulator through a desired trajectory while the trajectory of the mobile base is constrained. The application is tested and verified through simulation and experiments.

Decentralized Dynamic Control of a Nonholonomic Mobile Manipulator Collective: A Simulation Study

2008 ◽  
Author(s):  
Hao Su ◽  
Venkat Krovi
Keyword(s):  
Control Algorithm ◽  
Null Space ◽  
Dynamic Control ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Level Control ◽  
Individual Agent ◽  
End Effector ◽  
High Level ◽  
Task Accomplishment

In this paper, we present a decentralized dynamic control algorithm for a robot collective consisting of multiple nonholonomic wheeled mobile manipulators (NH-WMMs) capable of cooperatively transporting a common payload. In this algorithm, the high level controller deals with motion/force control of the payload, at the same time distributes the motion/force task into individual agents by grasp description matrix. In each individual agent, the low level controller decomposes the system dynamics into decoupled task space (end-effector motions/forces) and a dynamically-consistent null-space (internal motions/forces) component. The agent level control algorithm facilitates the prioritized operational task accomplishment with the end-effector impedance-mode controller and secondary null-space control. The scalability and modularity is guaranteed upon the decentralized control architecture. Numerical simulations are performed for a 2-NH-WMM system carrying a payload (with/without uncertainty) to validate this approach.

scholarly journals An Exponential Varying-Parameter Neural Network for Repetitive Tracking of Mobile Manipulators

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ying Kong ◽  
Qingqing Tang ◽  
Jingsheng Lei ◽  
Ruiyang Zhang
Keyword(s):  
Neural Network ◽  
Trajectory Planning ◽  
Matrix Equation ◽  
Mobile Manipulator ◽  
Mobile Manipulators ◽  
Time Varying ◽  
Repetitive Motion ◽  
End Effector ◽  
The Matrix ◽  
Simulation Results

A novel exponential varying-parameter neural network (EVPNN) is presented and investigated to solve the inverse redundancy scheme of the mobile manipulators via quadratic programming (QP). To suspend the phenomenon of drifting free joints and guarantee high convergent precision of the end effector, the EVPNN model is applied to trajectory planning of mobile manipulators. Firstly, the repetitive motion scheme for mobile manipulators is formulated into a QP index. Secondly, the QP index is transformed into a time-varying matrix equation. Finally, the proposed EVPNN method is used to solve the QP index via the matrix equation. Theoretical analysis and simulations illustrate that the EVPNN solver has an exponential convergent speed and strong robustness in mobile manipulator applications. Comparative simulation results demonstrate that the EVPNN possesses a superior convergent rate and accuracy than the traditional ZNN solver in repetitive trajectory planning with a mobile manipulator.

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