A Decentralized Autonomous Control on Highly Redundant Robot Manipulators

The control method of highly redundant robot manipulators is introduced. A decentralized autonomous control scheme is used to guide the movement of robot manipulators so that the work done by manipulators is minimized. The method of computing pseudoinverse which needs too many complicated calculation can be avoided. Then the calculation and control of robots are simplified. At the same time system robustness/fault tolerance is achieved.

COMPREHENSIVE EVALUATION OF FAULT-TOLERANT PROPERTIES OF REDUNDANT ROBOTS

When a redundant robot performs a fault-tolerant operation for locked joint failures, its fault tolerant properties should include dexterity and sudden change of joint velocity at the moment of locking failed joints and the dexterity during the post-failure. Firstly three fault-tolerant indexes, reduced condition number, sudden change of relative joint velocity and centrality are proposed, which can comprehensively evaluate the kinematical performance of a redundant robot during its entire fault-tolerant operations. Then, the influence of the initial postures of robot＇s end-effector on these fault-tolerant indexes is analyzed with a planar robot and a spatial robot. Simulation results show that for a given task the joint trajectory with the best comprehensive effect of fault tolerance can be determined by optimizing the initial posture of a robot.

Distributed coordinated adaptive tracking in networked redundant robotic systems with a dynamic leader

Distributed coordinated control of networked robotic systems formulated by Lagrange dynamics has recently been a subject of considerable interest within science and technology communities due to its broad engineering applications involving complex and integrated production processes,where high flexibility,manipulability,and maneuverability are desirable characteristics.In this paper,we investigate the distributed coordinated adaptive tracking problem of networked redundant robotic systems with a dynamic leader.We provide an analysis procedure for the controlled synchronization of such systems with uncertain dynamics.We also find that the proposed control strategy does not require computing positional inverse kinematics and does not impose any restriction on the self-motion of the manipulators;therefore,the extra degrees of freedom are applicable for other sophisticated subtasks.Compared with some existing work,a distinctive feature of the designed distributed control algorithm is that only a subset of followers needs to access the position information of the dynamic leader in the task space,where the underlying directed graph has a spanning tree.Subsequently,we present a simulation example to verify the effectiveness of the proposed algorithms.

Real-time dynamic system to path tracking and collision avoidance for redundant robotic arms

An dynamic system for real-time obstacle avoidance path planning of redundant robots is constructed in this paper. Firstly, the inter-frame difference method is used to identify the moving target and to calculate the target area, then on the basis of color features and gradient features extracted from the target area, the feature fusion Cam-Shift mean shift algorithm is used to track target, improving the robustness of the tracking algorithm. Secondly, a parallel two-channel target identification and location method based on binocular vision is proposed, updating the target＇s three-dimensional information in real time. Then, a dynamic collision-free path planning method is implemented： the safety rods are removed through the intersection test, and the minimum distance is derived directly by using the coordinate values of the target in the local coordinate system of the rod. On this basis, the obstacle avoidance gain and escape velocity related to the minimum distance is established, and obstacle avoidance path planning is implemented by using the zero space mapping matrix of redundant robot. Experiments are performed to Study the efficiency of the proposed system.

Intelligent Robust Control of Redundant Smart Robotic Arm Pt I: Soft Computing KB Optimizer - Deep Machine Learning IT

Redundant robotic arm models as a control object discussed.Background of computational intelligence IT on soft computing optimizer of knowledge base in smart robotic manipulators introduced.Soft computing optimizer is the sophisticated computational intelligence toolkit of deep machine learning SW platform with optimal fuzzy neural network structure.The methods for development and design technology of control systems based on soft computing introduced in this Part 1 allow one to implement the principle of design an optimal intelligent control systems with a maximum reliability and controllability level of a complex control object under conditions of uncertainty in the source data,and in the presence of stochastic noises of various physical and statistical characters.The knowledge bases formed with the application of soft computing optimizer produce robust control laws for the schedule of time dependent coefficient gains of conventional PID controllers for a wide range of external perturbations and are maximally insensitive to random variations of the structure of control object.The robustness is achieved by application a vector fitness function for genetic algorithm,whose one component describes the physical principle of minimum production of generalized entropy both in the control object and the control system,and the other components describe conventional control objective functionals such as minimum control error,etc.The application of soft computing technologies(Part I)for the development a robust intelligent control system that solving the problem of precision positioning redundant(3DOF and 7 DOF)manipulators considered.Application of quantum soft computing in robust intelligent control of smart manipulators in Part II described.

Two optimization algorithms for solving robotics inverse kinematics with redundancy

The kinematic redundancy in a robot leads to an infinite number of solutions for inverse kinematics, which implies the possibility to select a 'best' solution according to an optimization criterion. In this paper, two optimization objective functions are proposed, aiming at either minimizing extra degrees of freedom (DOFs) or minimizing the total potential energy of a multilink redundant robot. Physical constraints of either equality or inequality types are taken into consideration in the objective functions. Since the closed-form solutions do not exist in general for highly nonlinear and constrained optimization problems, we adopt and develop two numerical methods, which are verified to be effective and precise in solving the two optimization problems associated with the redundant inverse kinematics. We first verify that the well established trajectory following method can precisely solve the two optimization problems, but is computation intensive. To reduce the computation time, a sequential approach that combines the sequential quadratic programming and iterative Newton-Raphson algorithm is developed. A 4-DOF Fujitsu Hoap-1 humanoid robot arm is used as a prototype to validate the effectiveness of the proposed optimization solutions.

Comparison of internal force antagonism between redundant cable-driven parallel robots and redundant rigid parallel robots

The internal force antagonism(IFA)problem is one of the most important issues limiting the applications and popularization of redundant parallel robots in industry.Redundant cable-driven parallel robots(RCDPRs)and redundant rigid parallel robots(RRPRs)behave very differently in this problem.To clarify the essence of IFA,this study first analyzes the causes and influencing factors of IFA.Next,an evaluation index for IFA is proposed,and its calculating algorithm is developed.Then,three graphical analysis methods based on this index are proposed.Finally,the performance of RCDPRs and RRPRs in IFA under three configurations are analyzed.Results show that RRPRs produce IFA in nearly all the areas of the workspace,whereas RCDPRs produce IFA in only some areas of the workspace,and the IFA in RCDPRs is milder than that RRPRs.Thus,RCDPRs more fault-tolerant and easier to control and thus more conducive for industrial application and popularization than RRPRs.Furthermore,the proposed analysis methods can be used for the configuration optimization design of RCDPRs.

Hybrid task priority-based motion control of a redundant free-floating space robot

This paper presents a novel hybrid task priority-based motion planning algorithm of a space robot. The satellite attitude control task is defined as the primary task, while the leastsquares-based non-strict task priority solution of the end-effector plus the multi-constraint task is viewed as the secondary task. Furthermore, a null-space task compensation strategy in the joint space is proposed to derive the combination of non-strict and strict task-priority motion planning,and this novel combination is termed hybrid task priority control. Thus, the secondary task is implemented in the primary task＇s null-space. Besides, the transition of the state of multiple constraints between activeness and inactiveness will only influence the end-effector task without any effect on the primary task. A set of numerical experiments made in a real-time simulation system under Linux/RTAI shows the validity and feasibility of the proposed methodology.

A New Solution to the Inverse Position Analysis of the Redundant Serial Robot

A new solution to the inverse position analysis of the redundant serial robot is presented.The inverse position analysis problem of the redundant serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least square problem with the analytic form of a new Jacobi matrix.In this way,the inverse solution of the redundant serial robot can be searched out quickly under the desired precision when the positions of the three non-collinear end effector points are given.The inverse position analysis of the 7R redundant serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm.

Reaction Torque Control of Redundant Free-floating Space Robot

This paper presents the reaction torque based satellite base reactionless control or base disturbance minimization of a redundant free-floating space robot. This subject is of vital importance in the study of the free-floating space robot because the base disturbance minimization will result in less energy consumption and prolonged control application. The analytical formulation of the reaction torque is derived in this article, and the reaction torque control can achieve reactionless control and satellite base disturbance minimization. Furthermore, we derive the reaction torque based control of the space robot for base disturbance minimization from both the non-strict task priority and strict task priority control strategy. The dynamics singularity in the proposed algorithm is avoided in this paper. Besides, a real time simulation system of the space robot under Linux/real time application interface（RTAI） is developed to verify and test the feasibility and reliability of the method. The experimental results demonstrate the feasibility of online reaction torque control of the redundant free-floating space robot.