Joint sensor fault detection for fault tolerant parallel manipulators

Parallel manipulators with redundant joint displacement sensing can be exploited to develop fault tolerant implementations. This is possible since fundamental problems of the associated kinematics can still be solved after the elimination of faulty sensor readings. The ability of detecting faulty sensor readings is a requirement of any fault tolerant implementation scheme. A sensor fault detection method is presented for redundantly sensed parallel manipulators. A broad class of three‐branch manipulators is considered where each branch consists of three main‐arm joints and supports a common payload through respective passive spherical joints. The detection method is based on the comparison of forward displacement solutions for different cases of joint sensor readings. The existence of common solutions based on the branches–sensors considered, is used to effectively identify the existence of a failed sensor. Once a faulty sensor is identified, continued (fault tolerant) operation is possible using a forward displacement solution based on the readings of the accurate sensors. The detection method is implemented in a computer simulation of a calibrated three‐branch parallel manipulator. © 2000 John Wiley & Sons, Inc.     

Forward displacement analysis and uncertainty configurations of parallel manipulators with a redundant branch

The effect of adding a redundant branch in terms of reduction of the number of assembly modes and elimination of potential uncertainty configuration types is investigated for a class of parallel manipulators. Considered is a broad class that includes all three-branch manipulators where each branch is comprised of a serial arrangement of three main-arm joints supporting a common payload platform through a passive spherical branch end joint-group. The addition of a redundant branch effectively yields a four-branch manipulator class. Considered in particular is a 3–4 form of the manipulator where two branch ends meet at one point on the mobile platform. Symmetric main-arm joint sensing and actuation (two sensed/acutated main-arm joints per branch) is utilized. Synthetic geometry is used to study the number of assembly configurations of the resulting 3–4 four-branch parallel manipulators. It is presented that the number of assembly modes of three-branch parallel manipulators with passive spherical branch end joints can be reduced by utilizing a redundant branch. It is shown that there exist up to eight and up to four assembly modes when all unsensed joints are revolute and when all unsensed joints are prismatic, respectively. Combinations of unsensed prismatic and revolute joints are also investigated. It is determined that there are up to eight and up to four assembly modes when the unsensed main-arm joint of one of the concurrent branches is prismatic and when the unsensed joints of both concurrent branches are prismatic joints, respectively. Resolving the potential assembly modes require only the consideration of, at highest, second-order single-variable polynomials. In addition, kinematic design considerations allowing reduction of feasible assembly modes are discussed. The investigation of potential uncertainty configuration types is based on examining degeneracies of the screw systems formed by wrenches associated with the forces that the actuated-joints can apply. All linear dependency cases that could potentially cause uncertainties for the class of four-branch manipulators are identified. It is shown that while significantly reducing potential uncertainty configuration types, the addition of a redundant branch number cannot eliminate all potential dependency (uncertainty) cases completely. For the remaining potential uncertainty configuration types, the characteristics of the corresponding unconstrained instantaneous degrees of freedom are discussed. © 1996 John Wiley & Sons, Inc.     

An inverse kinematic solution for kinematically redundant robot manipulators

An inverse kinematic analysis addresses the problem of computing the sequence of joint motion from the Cartesian motion of an interested member, most often the end effector. Although the rates and accelerations are related linearly through the Jacobian, the positions go through a highly nonlinear transformation from one space to another. Hence, the closed-form solution has been obtained only for rather simple manipulator configurations where joints intersect or where consecutive axes are parallel or perpendicular. For the case of redundant manipulators, the number of joint variables generally exceeds that of the constraints, so that in this case the problem is further complicated due to an infinite number of solutions. Previous approaches have been directed to minimize a criterion function, taking into account additional constraints, which often implies a time-consuming optimization process. In this article, a different approach is taken to these problems. A Newton-Raphson numerical procedure has been developed based on a composite Jacobian which now includes rows for all members under constraint. This procedure may be applied to solve the inverse kinematic problem for a manipulator of any mechanical configuration without having to derive beforehand a closed-form solution. The technique is applicable to redundant manipulators since additional constraints on other members as well as on the end effector may be imposed. Finally, this approach has been applied to a seven degree-of-freedom manipulator, and its ability to avoid obstacles is demonstrated.     

Forward kinematics of walking machines with pantograph legs based on selections of independent joints

This article studies the forward kinematics of walking machines with pantograph legs. The walking machine is supported by three legs and each leg has 3 degrees of freedom (dof). Because the body has 6 dof motion, only 6 joint variables among the 9 are independent. Thus, there are 84 possible ways to select the 6 independent joint variables. It is shown that the complexity of the forward position solutions is very much dependent on the selection of independent joints. In the category of 3:2:1 (the 3 numbers denote the number of independent joints at each of the supporting legs), all 54 combinations give closed-form solutions. Among the 27 combinations of category 2:2:2, 10 possess closed-form solutions, 16 yield to higher-order polynomials, and 1 gives no solutions. The 3 combinations of category 3:3:0 give no solutions. The results are useful to control and simulation of walking machines and other parallel systems consisting of pantograph subchains such as parallel manipulators, multifingered hands, and multiply coordinated manipulators. © 1992 John Wiley & Sons, Inc.     

Robot arm reaching through neural inversions and reinforcement learning

We present a neural method that computes the inverse kinematics of any kind of robot manipulators, both redundant and non-redundant. Inverse kinematics solutions are obtained through the inversion of a neural network that has been previously trained to approximate the manipulator forward kinematics. The inversion provides difference vectors in the joint space from difference vectors in the workspace. Our differential inverse kinematics (DIV) approach can be viewed as a neural network implementation of the Jacobian transpose method for arm kinematic control that does not require previous knowledge of the arm forward kinematics. Redundancy can be exploited to obtain a special inverse kinematic solution that meets a particular constraint (e.g. joint limit avoidance) by inverting an additional neural network The usefulness of our DIV approach is further illustrated with sensor-based multilink manipulators that learn collision-free reaching motions in unknown environments. For this task, the neural controller has two modules: a reinforcement-based action generator (AG) and a DIV module that computes goal vectors in the joint space. The actions given by the AG are interpreted with regard to those goal vectors.     

A more general closed-form solution to the inverse kinematics of mechanical arms

This paper presents solutions to a number of different classes of robot manipulators obtained by locking the redundant joints in a redundant arm. This effort is part of the study of the flexibility offered by the introduction of additional degrees of freedom in mechanical arms. When the extra joints are randomly locked at arbitrary angles, the resultant will be non-redundant arms of various structure for each class of which kinematic solutions are required. The solutions thus cover a whole range of existing and future arm kinematics.     

Clamping weighted least-norm method for the manipulator kinematic control with constraints

One of the main challenges for kinematic control of manipulators is how to effectively address various constraints, such as obstacle avoidances. Most constraints can be converted into a virtual joint-limit problem by the general weighted least-norm method reported recently. However, a chattering of weighted factors might occur in the presence of disturbances. In this paper, in order to improve the robustness to disturbances, a clamping term forcing joints away from their limits is added to the solution of inverse kinematics, termed as the clamping weighted least-norm method. It is proved that the joint-limit constraint is always guaranteed. The proposed method is applicable to both non-redundant and redundant manipulators; the accuracy of main task is sacrificed only when there is confliction between main task and joint-limit constraint. Experiments on the seven-degree-of-freedom redundant manipulator illustrate the good performance for avoiding joint limits while tracking a given trajectory.     

Motion planning for mobile manipulators with a non-holonomic constraint using the FSP (full space parameterization) method

The efficient utilization of the motion capabilities of mobile manipulators, i.e., manipulators mounted on mobile platforms, requires the resolution of the kinematically redundant system formed by the addition of the degrees of freedom (DOF) of the platform to those of the manipulator. At the velocity level, the linearized Jacobian equation for such a redundant system represents an underspecified system of algebraic equations, which can be subject to a varying set of contraints such as a non-holonomic constraint on the platform motion, obstacles in the workspace, and various limits on the joint motions. A method, which we named the Full Space Parameterization (FSP), has recently been developed to resolve such underspecified systems with constraints that may vary in time and in number during a single trajectory. In this article, we first review the principles of the FSP and give analytical solutions for constrained motion cases with a general optimization criterion for resolving the redundancy. We then focus on the solutions to (1) the problem introduced by the combined use of prismatic and revolute joints (a common occurrence in practical mobile manipulators), which makes the dimensions of the joint displacement vector components non-homogeneous, and (2) the treatment of a non-holonomic constraint on the platform motion. Sample implementations on several large-payload mobile manipulators with up to 11 DOF are discussed. Comparative trajectories involving combined motions of the platform and manipulator for problems with obstacle and joint limit constraints, and with non-holonomic contraints on the platform motions, are presented to illustrate the use and efficiency of the FSP approach in complex motion planning problems. © 1996 John Wiley & Sons, Inc.     

Cartesian path generation of robot manipulators using continuous genetic algorithms

In this paper, the authors describe a novel technique based on continuous genetic algorithms (CGAs) to solve the path generation problem for robot manipulators. We consider the following scenario: given the desired Cartesian path of the end-effector of the manipulator in a free-of-obstacles workspace, off-line smooth geometric paths in the joint space of the manipulator are obtained. The inverse kinematics problem is formulated as an optimization problem based on the concept of the minimization of the accumulative path deviation and is then solved using CGAs where smooth curves are used for representing the required geometric paths in the joint space through out the evolution process. In general, CGA uses smooth operators and avoids sharp jumps in the parameter values. This novel approach possesses several distinct advantages: first, it can be applied to any general serial manipulator with positional degrees of freedom that might not have any derived closed-form solution for its inverse kinematics. Second, to the authors’ knowledge, it is the first singularity-free path generation algorithm that can be applied at the path update rate of the manipulator. Third, extremely high accuracy can be achieved along the generated path almost similar to analytical solutions, if available. Fourth, the proposed approach can be adopted to any general serial manipulator including both nonredundant and redundant systems. Fifth, when applied on parallel computers, the real time implementation is possible due to the implicit parallel nature of genetic algorithms. The generality and efficiency of the proposed algorithm are demonstrated through simulations that include 2R and 3R planar manipulators, PUMA manipulator, and a general 6R serial manipulator.     

Analytical Inverse Kinematic Computation for 7-DOF Redundant Manipulators With Joint Limits and Its Application to Redundancy Resolution

This paper proposes an analytical methodology of inverse kinematic computation for 7 DOF redundant manipulators with joint limits. Specifically, the paper focuses on how to obtain all feasible inverse kinematic solutions in the global configuration space where joint movable ranges are limited. First, a closed-form inverse kinematic solution is derived based on a parameterization method. Second, how the joint limits affect the feasibility of the inverse solution is investigated to develop an analytical method for computing feasible solutions under the joint limits. Third, how to apply the method to the redundancy resolution problem is discussed and analytical methods to avoid joint limits are developed in the position domain. Lastly, the validity of the methods is verified by kinematic simulations.      

Kinematics of a class of parallel manipulators which generates structures with three limbs

In this paper, the forward position analysis (FPA) of a class of parallel manipulators which can be modeled as structures with three limbs when the active joint rates, namely the generalized coordinates, are locked, is carried out using mixed and analytic procedures. The first option is a novel procedure which combines a numerical method and the closed-form solution of the geometry of a tetrahedron, that allows to find all the possible solutions for the FPA when specific requirements are satisfied. The second option is an analytic procedure capable of reducing a nonlinear system of three equations in three unknowns into a univariate 16th order polynomial equation, which evidently leads to a multiple solution. The introduction of linear equations, proposed in this contribution, obtained from the particular topology of these mechanisms simplifies considerably the FPA. In order to complement the kinematic analyses, the acceleration analysis of an exemplary parallel manipulator is approached by means of standard screw theory. Of course, as an intermediate step, this contribution also provides the velocity analysis of the chosen parallel manipulator. Finally, two numerical examples are provided.     

Parallel manipulator kinematics learning using holographic neural network models

The forward kinematic problem of parallel manipulators is resolved using a holographic neural paradigm. In a holographic neural model, stimulus–response (input–output) associations are transformed from the domain of real numbers to the domain of complex vectors. An element of information within the holographic neural paradigm has a semantic content represented by phase information and a confidence level assigned in the magnitude of the complex scalar. Networks are trained on a database generated from the closed-form inverse kinematic solutions. After the learning phase, the networks are tested on trajectories which were not part of the training data. The simulation results, given for a planar three-degree-of-freedom parallel manipulator with revolute joints and for a spherical three-degree-of-freedom parallel manipulator, show that holographic neural network models are feasible to solve the forward kinematic problem of parallel manipulators.     

Comparison of abdominal‐wall stretching between basic and enhanced laparoscopic instruments

In laparoscopic surgery, access to the patient's abdomen is gained by using an instrument, consisting of a 300–400 mm long stem with attached tool, inserted through a cannula mounted in the patient's abdominal wall. Sliding of the stem relative to the cannula and rotation of the stem about its longitudinal axis are the only motions not constrained by the abdominal wall. These limited‐motion capabilities necessitate abdominal‐wall stretching for full‐spatial tool displacements. Abdominal‐wall stretching is potentially damaging to the patient and fatiguing to the surgeon. Minimization of stretching is shown to be possible by the addition of a single revolute joint to the basic instrument. The motions allowed by the stem and cannula, the additional joint, and the abdominal wall result in a kinematically redundant system; i.e., an infinite number of joint displacements exist to achieve a desired tool position and orientation (desired tool pose). An optimization technique is applied to determine the minimum stretching for desired tool poses. Elimination of stretching is shown to be possible by the addition of two revolute joints to the basic instrument. Displacement models for the basic and enhanced instruments are found using concepts of manipulator kinematics. Forward and inverse displacement solutions for the instruments are found. The inverse displacement solutions are used to compare the amount of stretching required by each instrument. The stretching is highest for the basic instrument. The instrument with one additional joint produces stretching that is always less than or equal to that of the basic instrument. The instrument with two additional joints eliminates the need for stretching. © 2001 John Wiley & Sons, Inc.     

Static modeling and control of redundant manipulators

This paper develops unified static models for control of a redundant manipulator. We introduce the Premultiplier Diagram to describe the static behavior of a redundant manipulator. This diagram provides insight into the algebra and physics related to redundant manipulators. We derive redundancy expressions for the joint displacement, joint torque and joint stiffness matrix. These redundancy expressions are composed of a particular (net) part and a homogeneous (null) part. Based on the orthogonality property between the net and the null components, we propose an extension of the stiffness control scheme for redundant manipulators. We also show how the decomposed and decoupled static behavior of redundant manipulators can be used to derive an optimal control strategy.     

平面三自由度并联冗余机器人的位置分析

由于机构的结构复杂 ,对并联机器人进行位置分析 ,尤其是并联冗余机器人 ,要比串联机器人复杂得多 .本文提出一种新的平面三自由度并联冗余机器人位置分析方法 ,运用这种方法进行了位置正解和位置反解分析 .对于位置正解 ,其中方程的解最多为 4 ,说明这种平面并联机构可以有 4种不同的位姿 .对于位置反解 ,可以有16组解 .最后用数值实例进行了验证 ,给出了计算结果 .本文所提出的方法也为求解其它并联冗余机器人提供了新的途径     

A multi-objective approach for the motion planning of redundant manipulators

Kinematic redundancy occurs when a manipulator possesses more degrees of freedom than those required to execute a given task. Several kinematic techniques for redundant manipulators control the gripper through the pseudo-inverse of the Jacobian, but lead to a kind of chaotic inner motion with unpredictable arm configurations. Such algorithms are not easy to adapt to optimization schemes and, moreover, often there are multiple optimization objectives that can conflict between them. Unlike single optimization, where one attempts to find the best solution, in multi-objective optimization there is no single solution that is optimum with respect to all indices. Therefore, trajectory planning of redundant robots remains an important area of research and more efficient optimization algorithms are needed. This paper presents a new technique to solve the inverse kinematics of redundant manipulators, using a multi-objective genetic algorithm. This scheme combines the closed-loop pseudo-inverse method with a multi-objective genetic algorithm to control the joint positions. Simulations for manipulators with three or four rotational joints, considering the optimization of two objectives in a workspace without and with obstacles are developed. The results reveal that it is possible to choose several solutions from the Pareto optimal front according to the importance of each individual objective.     

A direct algorithm for continuous path control of manipulators

This paper presents an algorithm for positioning and orientation of the hand for a redundant or non-redundant manipulator along a continuous path in space. This algorithm minimizes the distance between the actual position of the tip of the end-effector and the desired path. The algorithm does not use the Jacobian matrix for the inverse kinematics of the robot. It takes full advantage of the resolution of the joint drives, avoids singularity problems, and can be used for both redundant manipulators. The algorithm can be used in any situation where continuus motion of the end-effector is required in an open loop mode.     

Motion Planning for Redundant Manipulators Using a Floating Point Genetic Algorithm

This paper deals with the trajectory planning problem for redundant manipulators. A genetic algorithm (GA) using a floating point representation is proposed to search for the optimal end-effector trajectory for a redundant manipulator. An evaluation function is defined based on multiple criteria, including the total displacement of the end-effector, the total angular displacement of all the joints, as well as the uniformity of Cartesian and joint space velocities. These criteria result in minimized, smooth end-effector motions. Simulations are carried out for path planning in free space and in a workspace with obstacles. Results demonstrate the effectiveness and capability of the proposed method in generating optimized collision-free trajectories.     

机器人的鲁棒预测控制

本文提出基于误差预测的机器人鲁棒控制器。考虑到机器人的动力学建模误差影响其控制性能,本文建立机器人的误差模型,给出预测建模误差对运动轨迹偏差的作用的有效方法,并提出建模误差的鲁棒性补偿。本文分别在关节空间和直角空间针对冗余机器人和非冗余机器人提出鲁棒预测控制器设计,其有效性由仿真例子检验。