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.

Collision Avoidance of Cooperative Dual Redundant Manipulators

Dual redundant manipulators are extremely useful for tasks in dangerous or space environments, but efficient and real time coordinated control is hard to achieve. Collision avoidance between two cooperative manipulators is vital to the successful applications of dual redundant manipulators. Although methods based on the distance function have been demonstrated simple and efficient, different collision avoidance points can usually produce completely different results and even failure. The paper discussed the choices of collision avoidance points and proposed a novel method for the choosing of those points. The method is testified by simulation results of two redundant planar manipulators.

Motion Planning Algorithms of Redundant Manipulators Based on Self-motion Manifolds

The current motion planning approaches for redundant manipulators mainly includes two categories： improved gradient-projection method and some other efficiency numerical methods. The former is excessively sensitive to parameters, which makes adjustment difficult; and the latter treats the motion planning as general task by ignoring the particularity, which has good universal property but reduces the solving speed for on-line real-time planning. In this paper, a novel stepwise solution based on self-motion manifold is proposed for motion planning of redundant manipulators, namely, the chief tasks and secondary tasks are implemented step by step. Firstly, the posture tracking of end-effector is achieved accurately by employing the non-redundant joint. Secondly, the end-effector is set to keep stationary. Finally, self-motion of manipulator is realized via additional work on the gradient of redundant joint displacement. To verify this solution, experiments of round obstacle avoiding are carried out via the planar 3 degree-of-~eedom manipulator. And the experimental results indicate that this motion planning algorithm can effectively achieve obstacle avoiding and posture tracking of the end-effector. Compared with traditional gradient projection method, this approach can accelerate the problem-solving process, and is more applicable to obstacle avoiding and other additional work in displacement level.

Obstacle Avoidance and Multitarget Tracking of a Super Redundant Modular Manipulator Based on Bezier Curve and Particle Swarm Optimization

A super redundant serpentine manipulator has slender structure and multiple degrees of freedom.It can travel through narrow spaces and move in complex spaces.This manipulator is composed of many modules that can form different lengths of robot arms for different application sites.The increase in degrees of freedom causes the inverse kinematics of redundant manipulator to be typical and immensely increases the calculation load in the joint space.This paper presents an integrated optimization method to solve the path planning for obstacle avoidance and discrete trajectory tracking of a super redundant manipulator.In this integrated optimization,path planning is established on a Bezier curve,and particle swarm optimization is adopted to adjust the control points of the Bezier curve with the kinematic constraints of manipulator.A feasible obstacle avoidance path is obtained along with a discrete trajectory tracking by using a follow-the-leader strategy.The relative distance between each two discrete path points is limited to reduce the fitting error of the connecting rigid links to the smooth curve.Simulation results show that this integrated optimization method can rapidly search for the appropriate trajectory to guide the manipulator in obtaining the target while achieving obstacle avoidance and meeting joint constraints.The proposed algorithm is suitable for 3D space obstacle avoidance and multitarget path tracking.

Active Control of Elastodynamic Response of Flexible Redundant Robot Manipulators

This paper presents an analytical investigation into activevibration control of flexible redundant robot manipulators featuringpiezoelectric actuators and strain gage sensors. The state-sp- aceexpression of the discrete time-varying dynamic system is developedfirstly. The LQR optimal control law is presented based upon thediscrete Minimum Principle. Moreover, an approximate method isproposed for estimating the state information of the system. Finally,a planar 3R flexible redundant manipulator is utilized as anillustration example. The simulation results show that the dy- namicperformance of the manipulator has been improved significantly.

Rapid Optimization of Tension Distribution for Cable-Driven Parallel Manipulators with Redundant Cables

The solution of tension distributions is infinite for cable-driven parallel manipulators（CDPMs） with redundant cables. A rapid optimization method for determining the optimal tension distribution is presented. The new optimization method is primarily based on the geometry properties of a polyhedron and convex analysis. The computational efficiency of the optimization method is improved by the designed projection algorithm, and a fast algorithm is proposed to determine which two of the lines are intersected at the optimal point. Moreover, a method for avoiding the operating point on the lower tension limit is developed. Simulation experiments are implemented on a six degree-of-freedom（6-DOF） CDPM with eight cables, and the results indicate that the new method is one order of magnitude faster than the standard simplex method. The optimal distribution of tension distribution is thus rapidly established on real-time by the proposed method.

Research on Trajectory Tracking Method of Redundant Manipulator Based on PSO Algorithm Optimization

Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize,the trajectory tracking method of redundant manipulator based on PSO algorithm optimization is studied.The kinematic diagram of redundant manipulator is created,to derive the equation of motion trajectory of redundant manipulator end.Pseudo inverse Jacobi matrix is used to solve the problem of manipulator redundancy.Based on the tracking ellipse of redundant manipulator,the tracking shape of redundant manipulator is determined with the overall tracking index as the second index,and the optimization method of tracking index is proposed.The redundant manipulator contour is located by active contour model,on this basis,combined with particle swarm optimization algorithm,the point coordinates on the circumference with the relevant joint point as the center and joint length as the radius are selected as the algorithm particles for iteration,and the optimal tracking results of the overall redundant manipulator trajectory are obtained.The experimental results show that under the proposed method,the tracking error of the redundant manipulator is low,and the error jump range is small.It shows that this method has high tracking accuracy and reliability.

SOLVING INVERSE KINEMATICS OF REDUNDANT MANIPULATOR BASED ON NEURAL NETWORK

For the redundant manipulators, neural network is used to tackle the velocityinverse kinematics of robot manipulators. The neural networks utilized are multi-layeredperceptions with a back-propagation training algorithm. The weight table is used to save the weightssolving the inverse kinematics based on the different optimization performance criteria.Simulations verity the effectiveness of using neural network.

Adaptive Control of Flexible Redundant Manipulators Using Neural Networks

An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors. A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator. The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced. The neuro-identifier and the neuro-controller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC. By adjusting the neuro-identifier and the neuro-controller alternatively, the manipulator was controlled on line for achieving the desired dynamic performance. Finally, a planar 3R redundant manipulator with one smart link was utilized as an illustrative example. The simulation results proved the validity of the control strategy.

Fault tolerant motion planning based on joint torque limit for redundant manipulators

First, two fault tolerant planning algorithms with avoidance of joint static torque limit or joint dynamic torque limit are proposed respectively. The former is suitable for the low-speed manipulators, and the latter is suitable for the high-speed manipulators. These algorithms not only can insure manipulation tasks to lie within the fault tolerant workspace but also can avoid joint torque limit, and hence can insure a redundant manipulator to be. fault tolerant in both kinematical sense and dynamic sense. Then, the simulation examples for a planar 3R manipulator demonstrate the validity of these algorithms.

Implementation and Kinematic Control of a Hyper-redundant Mobile Manipulator System

Redundant or hyper-redundant mobile manipulator can give lots of assistance to astronauts in space station. The design and implementation of a hyper-redundant mobile manipulator system are described, which is composed of an 8 DOF module robot and a 1 DOF motorized rail. Inverse kinematic resolution of the system is discussed and one simplified control method based on joint limit avoidance and configuration optimization is proposed. Simulation and experimental results are presented.

Obstacle Avoidance Method for a Redundant Manipulator Based on a Configuration Plane

This paper presents a novel approach of obstacle avoidance for redundant manipulators, which is challenging with the considerations of the building of universal kinematics, the formation of dynamics, and the generation of trajectories. A universal approach to deal with obstacle avoidance for the redundant manipulator, that is based on the configuration plane, is presented. The paper also examines common serial robot configurations and introduces a method for classification, partitioning, simplification, and forms of expression used in the workspace to define the configuration plane. This relatively new method is combined with a weighted space vector method to match the configuration plane and solve the inverse kinematics problem. The proposed planner is demonstrated with examples, in which the proposed planner is shown to be capable of providing a smoother trajectory.

COMPLEX NUMBER MODE APPROACH FOR REDUCING VIBRATION OF STRUCTURAL FLEXIBLE REDUNDANT ROBOT MANIPULATORS

A complex number mode analysis approach is proposed for vibration reducing of structural flexible redundant manipulators by utilizing self motion. In the proposed approach, the self motion is evaluated to nullify the modal exciting force of flexural motion, and the approach can be freely used when the degree of freedom of flexural motion is much greater than the available degree of reundancy. The availability and effectiveness of the proposed approach are demonstrated through numerical simulation with a four link spatial robotic manipulator possessing an end flexible link.

Motion planning for redundant prismatic-jointed manipulators in the free-floating mode

This paper investigates the motion planning of redundant free-floating manipulators with seven prismatic joints. On the earth, prismatic-jointed manipulators could only position their end-effectors in a desired way. However, in space, the end-effectors of free-floating manipulators can achieve both the desired orientation and desired position due to the dynamical coupling between manipulator and satellite movement, which is formally expressed by linear and angular momentum conservation laws. In this study, a tractable algorithm particle swarm optimization combined with differential evolution （PSODE） is provided to deal with the motion planning of redundant free-floating prismatic-jointed manipulators, which could avoid the pseudo inverse of the Jacobian matrix. The polynomial functions, as argument in sine functions are used to specify the joint paths. The co- efficients of the polynomials are optimized to achieve the desired end-effector orientation and position, and simulta- neously minimize the unit-mass-kinetic energy using the redundancy. Relevant simulations prove that this method pro- vides satisfactory smooth paths for redundant free-floating prismatic-jointed manipulators. This study could help to recognize the advantages of redundant prismatic-jointed space manipulators.

Multiple mobile-obstacle avoidance algorithm for redundant manipulator

In order to overcome the shortcomings of the previous obstacle avoidance algorithms,an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed.The minimum prediction distance between obstacles and a manipulator was obtained according to the states of obstacles and transformed to escape velocity of the corresponding link of the manipulator.The escape velocity was introduced to the gradient projection method to obtain the joint velocity of the manipulator so as to complete the obstacle avoidance trajectory planning.A7-DOF manipulator was used in the simulation,and the results verified the effectiveness of the algorithm.

PARAMETRIC IDENTIFICATION OF PARALLEL MANIPULATOR WITH REDUNDANCY DRIVEN BY PNEUMATIC MUSCLES

A new parameter estimation algorithm is proposed for parametric identification of a parallel manipulator driven by pneumatic muscles with redundancy. Due to the special physical properties of the parallel manipulator studied, the regression model for parametric identification is characterized by multieollinearity, which will result in unreliable and inaccurate parameter estimations with large eovarianee if the conventional parameter estimation algorithm based on single error minimizing criterion is used. To improve the quality of parameter estimation and achieve high precise posture trajectory tracking control of the parallel manipulator, a new parameter estimation algorithm based on composite error minimizing criterion is developed in need of theoretical contractive forces of pneumatic muscles. The experimental results indicate that the proposed algorithm integrated with adaptive robust control could provide reliable parametric identification and greatly enhance the control accuracy in the trajectory tracking control of the parallel manipulator, and that the variation of known theoretical contractive forces of pneumatic muscles has slight influence on the control performance.

Smart Material Based Complex Mode Active Control of Flexible Manipulators with Kinematic Redundancy

An active control methodology is presented for suppressing the vibratoryresponse of flexible redundant manipulators with bonded piezoceramic actuators and strain gagesensors. Firstly, the dynamic equation of the manipulator is decoupled by means of the complex modetheory and the state-space expression of the controlled system is developed. Secondly, a continuouslinear quadratic regulator (LQR) state feedback controller is designed based on the minimumprinciple. Thirdly, a full-order Luenberger state observer featuring an assigned degree of stabilityis determined via the duality between control and estimation. Finally, a numerical simulation iscarried out on a planar 3R flexible redundant manipulator. The simulation results reveal that thedynamic performance of the system is improved rapidly and significantly.

Kinematics of a Trinal-Branch Space Robotic Manipulator with Redundancy

This paper presents a trinal-branch space robotic manipulator with redundancy, due to hash application environments, such as in the station. One end-effector of the manipulator can be attached to the base, and other two be controlled to accomplish tasks. The manipulator permits operation of science payload, during periods when astronauts may not be present. In order to provide theoretic basis for kinematics optimization, dynamics optimization and fault-tolerant control, its inverse kinematics is analyzed by using screw theory, and its unified formulation is established. Base on closed-form resolution of spherical wrist, a simplified inverse kinematics is proposed. Computer simulation results demonstrate the validity of the proposed inverse kinematics.

Self-adapting control parameters modifieddifferential evolution for trajectoryplanning of manipulators

Control parameters of original differential evolution （DE） are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE for different optiinization problems. According to the relative position of two different individual vectors selected to generate a difference vector in the searching place, a self-adapting strategy for the scale factor F of the difference vector is proposed. In terms of the convergence status of the target vector in the current population, a self-adapting crossover probability constant CR strategy is proposed. Therefore, good target vectors have a lower CFI while worse target vectors have a large CFI. At the same time, the mutation operator is modified to improve the convergence speed. The performance of these proposed approaches are studied with the use of some benchmark problems and applied to the trajectory planning of a three-joint redundant manipulator. Finally, the experiment results show that the proposed approaches can greatly improve robustness and convergence speed.

Inverse Kinematics Analysis of a 7-DOF Space Manipulator for Trajectory Design

To solve the inverse kinematics problem for redundant degrees of freedom（DOFs）manipulators has been and still continues to be quite challenging in the field of robotics.Aiming at trajectory planning for a 7-DOF space manipulator system,joint rotation trajectories are obtained from predetermined motion trajectories and poses of the end effector in Cartesian space based on the proposed generalized inverse kinematics method.A minimum norm method is employed to choose the best trajectory among available trajectories.Numerical simulations with the7-DOF manipulator show that the proposed method can achieve the planned trajectory and pose under the circumstances of minimum angular velocities.Moreover,trajectory results from the proposed kinematics model and inverse kinematics method has the advantages of simple modelling,low computation cost,easy to solve and plan trajectory conveniently.The smooth and continuous joint rotation functions obtained from the proposed method are suitable for practical engineering applications.