Kinematics/Fuzzy Logic Combined Controller for Formation Control of Mobile Robots

A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the robot.The kinematics controller generates desired linear and angular velocities for follower robots,which make the configuration of follower robots coverage to the desired.The fuzzy logic controller takes dynamics of the leader and followers into consideration,which is built upon Mamdani fuzzy model.The force and torque acting on robots are described as linguistic variables and also 25 if-then rules are designed.In addition,the fuzzy logic controller adopts the Centroid of Area method as defuzzification strategy and makes robots’actual velocities converge to the expected which is generated by the kinematics controller.The innovation of the kinematics and fuzzy logic combined formation controller presented in the paper is that the perfect velocity tracking assumption is removed and realtime performance of the system is improved.Compared with traditional torque-computed controller,the velocity error convergence time in case of the proposed method is shorter than traditional torque-computed controller.The simulation results validate that the proposed controller can drive robot members to form the desired formation and formation tracking errors which can coverage to a neighborhood of the origin.Additionally,the simulations also show that the proposed method has better velocity convergence performance than traditional torque-computed method.

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.

OPTIMAL CONTROL OF REDUNDANT ROBOTS WITH LOCAL DEGREES OF FREEDOM

A kinematically redundant robot, with more degrees of freedom than re-quired to complete a desired task, can be usefu1 because of its inherent kinematics flexibili-ty and dynamic performance. lt is very difficu1t, however, to implement optimal redun-dancy control, while simultaneously taking into account hath kinematics and dynamics.To realize dua1-optimization control, a new redundant robot mechanism with local degreesof freedom is introduced, and its kinematics and dynamics features are investigated. Simu-lation results demonstrate the effectiveness of the proPosed method.

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.

Parameter Identification and Application of Slippage Kinematics for Tracked Mobile Robots

A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning between angular velocity and linear velocity.In the processing of pivot turning,the slippage parameters could be obtained by measuring the end point in a square path.In the process of coupled turning,the slippage parameters could be calculated by measuring the perimeter of a circular path and the linear distance between the start and end points.The identification results showed that slippage parameters were affected by velocity.Therefore,a fuzzy rule base was established with the basis on the identification data,and a fuzzy controller was applied to motion control and dead reckoning.This method effectively compensated for errors resulting in unequal tension between the left and right tracks,structural dimensions and slippage.The results demonstrated that the accuracy of robot positioning and control could be substantially improved on a rigid floor.

Review on Control Strategies for Cable-Driven Parallel Robots with Model Uncertainties

Cable-driven parallel robots(CDPRs)use cables instead of the rigid limbs of traditional parallel robots,thus processing a large potential workspace,easy to assemble and disassemble characteristics,and with applications in numerous fields.However,owing to the influence of cable flexibility and nonlinear friction,model uncertainties are di cult to eliminate from the control design.Hence,in this study,the model uncertainties of CDPRs are first analyzed based on a brief introduction to related research.Control strategies for CDPRs with model uncertainties are then reviewed.The advantages and disadvantages of several control strategies for CDPRS are discussed through traditional control strategies with kinematic and dynamic uncertainties.Compared with these traditional control strategies,deep reinforcement learning and model predictive control have received widespread attention in recent years owing to their model independence and recursive feasibility with constraint limits.A comprehensive review and brief analysis of current advances in these two control strategies for CDPRs with model uncertainties are presented,concluding with discussions regarding development directions.

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.

A modified forward and backward reaching inverse kinematics based incremental control for space manipulators

Forward and backward reaching inverse kinematics(FABRIK)is an efficient two-stage iterative solver for inverse kinematics of spherical-joint manipulator without the calculation of Jacobian matrix.Based on FABRIK,this paper presents an incremental control scheme for a free-floating space manipulator consists of revolute joints and rigid links with the consideration of joint constraints and dynamic coupling effect.Due to the characteristics of FABRIK,it can induce large angular movements on specific joints.Apart from that,FABRIK maps three dimensional(3D)problem into two dimensional(2D)problem by a simple geometric projection.This operation can cause infinite loops in some cases.In order to overcome these issues and apply FABRIK on space manipulators,an increments allocation method is developed to constrain the angular movements as well as to re-orient the end-effector.The manipulator is re-positioned based on the momentum conservation law.Instead of pure target position tracking,the orientation control of the end-effector is also considered.Numerical simulation is performed to testify and demonstrate the effectiveness and reliability of the proposed incremental control approach.

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.

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.

Bio-inspired Backstepping Adaptive Sliding Mode Control for Parallel Mechanism with Actuation Redundancy

This paper presents a bio-inspired backstepping adaptive sliding mode control strategy for a novel 3 degree of freedom(3-DOF) parallel mechanism with actuation redundancy. Based on the kinematic model and the dynamic model, a sliding mode controller is designed to assure the tracking performance, and an adaptive law is introduced to approximate the system uncertainty including parameters variation, external disturbances and un-modeled part. Furthermore, a bio-inspired model is introduced to solve the inherent chattering problem of sliding mode control and provide a chattering free control. The simulation and experimental results testify that the proposed bio-inspired backstepping adaptive sliding mode control can achieve better performance(the tracking accuracy,robustness, response speed, etc.) than the conventional slide mode control.

Kinematic Control of Wheeled Snake-Like Mobile Robot

From a bionics viewpoint , this paper proposes a mechanical model of a wheeled snake like mobile mechanism. On the hypothesis of the existing non holonomic constraints on the robot kinematics, we set up the relationship among the kinetic control parameters in the snake like movement using Lie group and Lie algebra of the principle fiber bundle and provide some theoretical control methods to realize the snake like locomotion.

On set-point tracking control of dexterous robot hand

A model-free set-point tracking control approach of multi-fingered robot hand is presented.The set-point tracking controller,which has the structural form of PD controller,is composed with a combination of feedforward term,feedback term and saturation control term.The controller does not require the explicit use of dynamic modeling parameters.Experiments performed on the HIT/DLR hand demonstrate the effectiveness of the proposed approach in performance improvement and real-time application.

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.

Introduction to the special issue on Advances in intelligent nonlinear control for robotic systems

In the last two decades, robotic systems have achieved wide applications in every aspect of human society, including industrial manufacturing, automotive production, medical devices, and social lives. With the

A 3D Spectroscopic Vision-based Control Technique for Bilateral Systems

Visual servoing is an active and popular area of research among roboticists.Eventhough visual servoing techniques enhance the perfomance,the associated systems still use traditional methods for their input control.Many research activities and applications have been carried out to implement effective and precise controlling of bilateral systems.This paper presents a 3D spresctroscope-based control technique for bilateral systems.The effectiveness of the available master side designs are evaluated against gesture-based techniques.Joystick control,Electromyography(EMG),Voice control,Haptic control,Exoskeleton control,Gesture and Brain Control Interface(BCI)are identified in the litreature as available bilateral inputs.In the present technnique,Leap Motion Controller(LMC)has been introduced(LMC)to extract the human hand gestures and their parameters.Then these parameters are convereted into respective joint sapce angles using the presented mathematical model.The mathematical models for fingertip mapping,inverse kinematics,dynamics and trajectory generation are implemented and studied.Wolfman Mathematica 10 and MATLAB simulation framework are used to validate the mathematical models,simulations and developed control algorithms.The developed system has sucesfully imitated the fingertip motion.In particular,the system has been able to imitate the figretip motion with a deviation of 6.7%in X axis,5.5%in Y axis and7.9%in Z axis with respect to the expected position.

Construction and kinematic performance analysis of a suspension support for wind tunnel tests of spinning projectiles based on wire-driven parallel robot with kinematic redundancy

This paper presents a novel suspension support tailored for wind tunnel tests of spinning projectiles based on Wire-Driven Parallel Robot(WDPR),uniquely characterized by an SPM(Spinning Projectile Model)-centered mobile platform.First,an SPM-centered mobile platform,featuring two redundant and another unconstrained Degree of Freedom(DOF),and its suspension support mechanism are designed together,collectively constructing a WDPR endowed with kinematic redundancy.Afterward,the kinematics of the mechanism,boundary equations for the redundant DOFs,and relevant kinematic performance indices are then proposed and formulated.The results from both prototype experiments and numerical assessments are presented.The capability of the support mechanism to replicate the complex coupled motions of the SPM is verified by the experimental results,while the proposed kinematics and boundary equations are also validated.Furthermore,it is revealed by numerical assessments that the redundant DOFs of the mobile platform exert a minimal impact on the kinematic performance of the suspension support.Finally,the optimal global attitude performance is obtained when these DOFs are set to zero if they are restricted to constants.However,local attitude performance can be further improved by the variable values.

A Hyper-redundant Elephant’s Trunk Robot with an Open Structure:Design,Kinematics,Control and Prototype

As for the complex operational tasks in the unstructured environment with narrow workspace and numerous obstacles,the traditional robots cannot accomplish these mentioned complex operational tasks and meet the dexterity demands.The hyper-redundant bionic robots can complete complex tasks in the unstructured environments by simulating the motion characteristics of the elephant’s trunk and octopus tentacles.Compared with traditional robots,the hyper-redundant bionic robots can accomplish complex tasks because of their flexible structure.A hyper-redundant elephant’s trunk robot(HRETR)with an open structure is developed in this paper.The content includes mechanical structure design,kinematic analysis,virtual prototype simulation,control system design,and prototype building.This design is inspired by the flexible motion of an elephant’s trunk,which is expansible and is composed of six unit modules,namely,3UPS-PS parallel in series.First,the mechanical design of the HRETR is completed according to the motion characteristics of an elephant’s trunk and based on the principle of mechanical bionic design.After that,the backbone mode method is used to establish the kinematic model of the robot.The simulation software SolidWorks and ADAMS are combined to analyze the kinematic characteristics when the trajectory of the end moving platform of the robot is assigned.With the help of ANSYS,the static stiffness of each component and the whole robot is analyzed.On this basis,the materials of the weak parts of the mechanical structure and the hardware are selected reasonably.Next,the extensible structures of software and hardware control system are constructed according to the modular and hierarchical design criteria.Finally,the prototype is built and its performance is tested.The proposed research provides a method for the design and development for the hyper-redundant bionic robot.

Robust model predictive tracking control for the wheeled mobile robot with boundary uncertain based on linear matrix inequalities

In this study,a robust model predictive controller is designed for the trajectory tracking problem of non-holonomic constrained wheeled mobile robot based on an elliptic invariant set approach.The controller is based on a time-varying error model of robot kinematics and uses linear matrix inequalities to solve the robust tracking problem taking uncertainties into account.The uncertainties are modelled by linear fractional transform form to contain both parameter perturbations and external disturbances.The control strategy consists of a feedforward term that drives the centre of the ellipse to the reference point and a feedback term that converges the uncertain system state error to the equilibrium point.The strategy stabilises the nominal system and ensures that all states of the uncertain system remain within the ellipsoid at each step,thus achieving robust stability of the uncertain system.Finally,the robustness of the algorithm and its resistance to disturbances are verified by simulation and experiment.

冗余机器人的笛卡儿空间螺旋线性插值轨迹规划

通过分析对偶四元数与刚体运动、螺旋运动之间的关系并结合指数积公式,得到基于对偶四元数的末端位姿变换算子;根据牛顿拉夫森法,将对偶四元数用于求解冗余机器人的逆运动学数值解;根据对偶四元数的线性插值特点提出一种基于螺旋线性插值的轨迹规划方法。两种冗余机器人验证了提出的轨迹规划方法能实现笛卡儿空间平滑运动和速度可控,且在求解运动学数值解时,使用对偶四元数比齐次矩阵具有更好的稳定性和更高的解算速度。