A new, seven parameter class of micromanipulators is found with decoupled dynamics. The flexibility of the new class is demonstrated by designing a Stewart platform with fully equalized and decoupled dynamics (i.e., all resonant frequencies are equal). Although this has been attempted before by other researchers, it has not been previously accomplished. The ability to design the dynamics so they are amenable to control leads to significant increases in closed loop performance and robustness. The dynamically decoupled and equalized manipulator is compared to an asymmetric manipulator in closed loop. Even though both manipulators control the same payload over the same bandwidth with exactly the same struts, the H∞controller for the equalized manipulator is five times less sensitive to worst case disturbances than the H∞controller for the asymmetric manipulator. Moreover, the decoupling facilitates the design of Nyquist stable compensators which give the decoupled manipulator one hundred times higher performance at low frequencies. This greatly increased performance and robustness requires implementation of only the six compensators along the diagonal of the six degree-of-freedom system, versus implementation of all 36 compensators for the asymmetrical manipulator.

This paper analytically finds a new, significantly more general class of locally decoupled 2p - UPS, parallel manipulators encompassing and expanding several earlier classes. Its closed form solution leads directly to simple analytic formulas for the system eigenvalues in terms of geometric design parameters. To illustrate the power of the theory, the new methods are used to re-design an actual manipulator currently in use on the International Space Station. Unlike the existing manipulator, the new design is dynamically decoupled and isotropic.

New methods are found for arranging force actuators around a rigid body so that the system has locally decoupled and optimal manipulation characteristics. The closed-form solution leads directly to simple analytic formulas for the singular values of the manipulator Jacobian in terms of geometric design parameters. This makes it possible to easily design the local kinematics so that they meet desired specifications. Explicit formulas for designing the wrench/twist capabilities, achieving isotropy, maximizing the volume of achievable motions, and maximizing the minimum singular values are derived. Applications include design of generalized Gough-Stewart platforms (GSPs) and other parallel machines. To illustrate the power of the theory, the new methods are used to redesign an actual manipulator currently in use on the International Space Station (ISS). Unlike the existing manipulator, the new design is kinematically decoupled, isotropic, and fault tolerant - all highly desirable properties, especially in aerospace applications.

This paper develops a new, nearly analytical method for pose estimation. Two steps are required: (1) solution of a least squares matrix problem, followed by projection of the solution onto the nearest scaled subunitary matrix, and (2) solution of a least squares vector problem, followed by projection onto the three dimensional special orthogonal group, SO(3). Although the method can be iterated when necessary, it achieves accuracy to standard stopping criteria with on average only one iteration; thus it can be considered nearly analytical. The method is compared to numerical methods and is shown to be much faster than earlier iterative methods. Both perspective and affine cameras models are treated.

This paper considers the control problem of an eye-in-hand type of parallel robot based precision pointing system (PRBPPS) in which the visual sensor is mounted on the platform of the parallel robot. The aim of the control is to move the platform of the parallel robot such that the image feature points reach the desired locations. An adaptive supervisory fuzzy logic controller (ASFLC) is first designed to compensate for the uncertainties of the parallel robot and uncertainty of the image Jacobian, then a hybrid controller (HC) including the image-based nonlinear controller (IBNC) and the ASFLC is derived by using the Lyapunov direct method to realize the precision position regulation (PPR). The stability of the closed-loop system in the Lyapunov sense is proven theoretically. The simulation results demonstrate that the PRBPPS realizes PPR with very good robustness to parameter uncertainties.

A new design method for optimizing Gough-Stewart platform geometries is proposed in this paper. The prior studies are extended through optimizing both the kinematics and dynamics. Firstly, a new class of weighted orthogonal Gough-Stewart platforms (w-OGSPs) is proposed. Then the concept of simultaneously diagonal OGSPs (sd-OGSPs) is defined. The sd-OGSPs allow the Cartesian second order impedance to be specified, thus obtaining desired local system poles. Design algorithms and simulation results are given

For any manipulator, fault tolerance is a desirable property. This paper shows that for any serial or parallel manipulator functioning about a single point in its workspace, the mean square of the relative manipulabilities over all possible failures, with a given number of links failing at a time, is always constant irrespective of the geometry of the manipulator. In this paper optimal fault tolerant manipulability is defined for parallel manipulators. This concept is applied to orthogonal Gough-Stewart platforms (OGSPs) to identify a class of symmetric OGSPs having optimal fault tolerant manipulability. As an example, an 8-strut OGSP having this property is described

This paper develops new, analytical methods to find a large class of orthogonal Gough-Stewart platforms (OGSPs) having desired properties at their home position. In contrast, prior methods have been computationally intensive, relying on numerical search techniques. By exploiting symmetry, 27 equations are reduced to only two. The new techniques are directly applicable to clean-sheet design of micro-manipulators, vibration isolators, and Cartesian stiffness matrices. In addition, straightforward methods for retro-fitting existing OGSPs are illustrated. Because the new theory greatly simplifies OGSP formulas about a single point, it is expected that these results will also prove to be very useful when numerically designing gross motion platforms

When a parallel manipulator suffers from failures, its performance can be significantly affected. Thus, fault tolerance is essential for task-critical applications or applications in which maintenance is hard to implement. In this paper, we consider three types of common strut failures corresponding to stuck joints, unactuated actuators, or the complete loss of struts, respectively. The impacts of different failures on the kinematics of a manipulator are examined, and the task space redundancy and kinematic redundancies are used to help overcome these failures. In addition, local measures of fault tolerance and their properties are analyzed. These measures can be helpful in architecture design and path planning

This paper develops new, analytical methods to find a large class of Orthogonal Gough-Stewart Platforms (OGSPs) having desired manipulabilities at a single point. In contrast, prior methods have been computationally intensive, relying on numerical search techniques. The new techniques are directly applicable to clean sheet design of micro-manipulators, vibration isolators, and Cartesian stiffness matrices. In addition, straightforward methods for retro-fitting existing OGSPs are illustrated. The approach relies on symmetrically repeating a strut at least three times.

This paper develops methods for generating classes of orthogonal Gough-Stewart platforms (OGSPs). First, a new, two-parameter class of six-strut OGSPs which leads to isotropic manipulators are found. Next, this class is extended to include redundant Gough-Stewart platforms (GSPs). For an even number of struts, the same algorithm used to generate the six-strut case can be employed. For an odd number of struts, similar essential concepts are used to derive seven-strut and nine-strut OGSPs. Maximization of fault tolerance is implemented for a nine-strut isotropic OGSP. By exploiting invariant properties of the inverse Jacobian, new methods for favorably altering the center of gravity, strut attachment surface, and strut spatial distribution are developed.

Optimal geometric design is of key importance to the performance of a manipulator. First, this paper extends the work in Y. Yi, et al., (2004) to generate a class of isotropic Gough-Stewart platforms (GSPs) with an odd number of struts. Then, it develops methods for finding a highly fault tolerant GSP from that class. Two optimization criteria are considered, isotropy and fault tolerance. To meet the mission critical needs imposed by laser weapons applications, nine-strut isotropic GSPs that retain kinematic stability despite the loss of any three struts are found. First, we develop methods for generating a five parameter class of isotropic nine-strut GSPs. Next, new measures of fault tolerance are introduced and used to optimize the free parameter space. The optimized design is much more fault tolerant than the GSP currently baselined for the airborne laser.

This paper develops methods for generating classes of orthogonal Gough-Stewart platforms (OGSPs). First, a new, two-parameter class of six-strut OGSPs is found. For an even number of struts, the same essential concepts used to generate the six-strut case can be employed to generate OGSPs with eight struts, ten struts, etc. Next, by exploiting invariant properties of the inverse Jacobian, new methods for favorably altering the center of gravity, strut attachment surface, and strut spatial distribution are developed. As an illustrative example, these methods are applied to the design of the attachment of vibration isolation and precision pointing system for the space based laser.

In many applications, the manipulations require only part of the degrees of freedom (DOFs) of the end-effector, or some DOFs are more important than the rest. We name these applications prioritized manipulations. The end-effector's DOFs are divided into those which are critical and must be controlled as precisely as possible, and those which have loose specifications, so their tracking performance can be traded off to achieve other needs. In this paper, for the class of general constrained rigid multibody systems (including passive joints and multiple closed kinematic loops), we derive a formulation for partitioning the task space into major and secondary task directions, and finding the velocity and static force mappings that precisely accomplish the major task and optimize some secondary goals such as reliability enhancement, obstacle and singularity avoidance, fault tolerance, or joint limit avoidance. The major task and secondary goals need to be specified in term of velocities/forces. In addition, a framework is developed to handle two kinds of common actuator failures, torque failure and position failure, by reconfiguring the differential kinematics and static force models. The techniques are tested on a 6-DOF parallel robot. Experimental results illustrate that the approach is practical and yields good performance.

Development of methods to design optimal Gough-Stewart platform geometries capable of meeting desired specifications is of high interest. Computationally intensive methods have been used to treat this problem in various settings. This paper uses analytic methods to characterize all orthogonal Gough-Stewart platforms (OGSPs) and to study their properties over a small workspace. This characterization is used to design optimal OGSPs for precision applications that achieve a desired hyperellipsoid of velocities. Some examples demonstrating the versatility of this theory are discussed.

In a number of contexts relevant to control problems, including estimation of robot dynamics, covariance, and smart structure mass and stiffness matrices, we need to solve an over-determined set of linear equations AX /spl ap/ B with the constraint that the matrix X be symmetric and positive definite. In the classical least squares method, the measurements of A are assumed to be free of error. Hence, all errors are confined to B. Thus, the "optimal" solution is given by minimizing /spl par/AX - B/spl par//sub F//sup 2/. However, this assumption is often impractical. Sampling errors, modeling errors, and, sometimes, human errors bring inaccuracies to A as well. We introduce a different optimization criterion, based on area, which takes the errors in both A and B into consideration. The analytic expression of the global optimizer is derived. The algorithm is applied to identify the joint space mass-inertia matrix of a Gough-Stewart platform. Experimental results indicate that the new approach is practical, and improves performance.

By exploiting properties of the joint space mass-inertia matrix of flexure jointed hexapods, a decoupling method is proposed. The decoupling method, through a static input-output mapping, transforms the highly coupled 6 input 6 output dynamics into 6 independent single-input single-output (SISO) channels. Controls for these SISO channels are far simpler than their multiple-input multiple-output counterparts. Prior decoupling control algorithms imposed severe constraints on the allowable geometry, workspace, and payload. The paper derives a new algorithm which removes these constraints, thus greatly expanding the applications. Based on the new decoupling algorithm, an identification algorithm is introduced to identify the joint space mass-inertia matrix using payload accelerations and base forces. This algorithm can be used for precision payload calibration, this improving performance and removing the labor required to design the control for different payloads. The new decoupling algorithm is experimentally compared to earlier techniques. These experimental results indicate that the new approach is practical and improves performance.

By combining static input-output decoupling transformations with hexapod geometric design, the highly coupled dynamics of a flexure jointed hexapod can be decoupled. Several algorithms have been proposed which result in different sets of decoupled inputs and outputs, and which can use a variety of feedback measurements (position, velocity, acceleration, or force in either joint or Cartesian spaces). Three hexapod configurations satisfying the geometry requirements have been proposed. Experimental results indicate that the approach is practical and yields superior performance.

Given an explicit task to be executed, an intelligent machine must be able to select a plan containing control and sensing strategies such that a desired set of specifications are reliably satisfied. This issue is addressed through a technique termed reliable control and sensor fusion. An approach to reliability analysis is proposed based on the use of entropy which is invariant with respect to homogeneous coordinate frame transformations. This yields an easily calculated set of entropy constraints that must be met to ensure reliable operation. An example problem illustrates the technique and presents general results for visual positioning.>

Technology for actively supporting groups of collaborating users is being applied to many kinds of cooperative work activities. The following topics are addressed: (1) the authors' definition of groupware, (2) a conceptual framework in which to examine research issues, and (3) high-level groupware research issues within this framework. One potentially fertile area of application for such technologies is the problem of software process management. Software process means one of the teamwork, cooperation, coordination, and communication activities that occur within and across groups and organizations of persons throughout the life of software projects, including processes that occur under the broad categories of proposal writing, software engineering, development, and maintenance. This application domain contains a number of research issues and technology problems in such areas as communication, distribution, concurrence control, and human-computer interface design. The research areas needed for groupware to facilitate software processes are described.>

By using concepts from information theory and reliability theory, new techniques are proposed for finding the reliability corresponding to alternative subsets of control and sensing strategies such that a desired set of specifications can be satisfied. The analysis is straightforward provided that a set of Gaussian random state variables is available. An example problem illustrates the technique and provides general reliability results for visual serving with a computed torque control algorithm.>

Robotic tasks in space require manipulation of massive objects capable of attaining large momentum. The momentum can pose hazardous conditions and introduce destabilizing effects on a space platform. Consequently, a technique for limiting the momentum applied to objects under manipulation subject to arbitrary velocity input commands is proposed. The algorithm does not require mass position or inertia information about the object, and it takes actuator limitations into account in forming the momentum limits. To evaluate the probability that a velocity trajectory will fall within the momentum bounds, reliability theory is employed. This enables autonomously generated trajectories to be validated for compliance with momentum limits.>

Given an explicit task to be executed, an intelligent machine must be able to find the probability of success, or reliability, of alternative control and sensing strategies. By using concepts for information theory and reliability theory, new techniques for finding the reliability corresponding to alternative subsets of control and sensing strategies are proposed such that a desired set of specifications can be satisfied. The analysis is straightforward, provided that a set of Gaussian random state variables is available. An example problem illustrates the technique, and general reliability results are presented for visual servoing with a computed torque-control algorithm. Moreover, the example illustrates the principle of increasing precision with decreasing intelligence at the execution level of an intelligent machine.>