Showing papers on "Kinematics published in 1999"

Independent learning of internal models for kinematic and dynamic control of reaching.

Abstract: Psychophysical studies of reaching movements suggest that hand kinematics are learned from errors in extent and direction in an extrinsic coordinate system, whereas dynamics are learned from proprioceptive errors in an intrinsic coordinate system. We examined consolidation and interference to determine if these two forms of learning were independent. Learning and consolidation of two novel transformations, a rotated spatial reference frame and altered intersegmental dynamics, did not interfere with each other and consolidated in parallel. Thus separate kinematic and dynamic models were constructed simultaneously based on errors computed in different coordinate frames, and possibly, in different sensory modalities, using separate working-memory systems. These results suggest that computational approaches to motor learning should include two separate performance errors rather than one.

A hierarchical approach to interactive motion editing for human-like figures

Abstract: This paper presents a technique for adapting existing motion of a human-like character to have the desired features that are specified by a set of constraints This problem can be typically formulated as a spacetime constraint problem Our approach combines a hierarchical curve fitting technique with a new inverse kinematics solver Using the kinematics solver, we can adjust the configuration of an articulated figure to meet the constraints in each frame Through the fitting technique, the motion displacement of every joint at each constrained frame is interpolated and thus smoothly propagated to frames We are able to adaptively add motion details to satisfy the constraints within a specified tolerance by adopting a multilevel Bspline representation which also provides a speedup for the interpolation The performance of our system is further enhanced by the new inverse kinematics solver We present a closed-form solution to compute the joint angles of a limb linkage This analytical method greatly reduces the burden of a numerical optimization to find the solutions for full degrees of freedom of a human-like articulated figure We demonstrate that the technique can be used for retargetting a motion to compensate for geometric variations caused by both characters and environments Furthermore, we can also use this technique for directly manipulating a motion clip through a graphical interface CR Categories: I37 [Computer Graphics]: Threedimensional Graphics—Animation; G12 [Numerical Analysis]: Approximation—Spline and piecewise polynomial approximation

Physically based motion transformation

Abstract: We introduce a novel algorithm for transforming character animation sequences that preserves essential physical properties of the motion. By using the spacetime constraints dynamics formulation our algorithm maintains realism of the original motion sequence without sacrificing full user control of the editing process. In contrast to most physically based animation techniques that synthesize motion from scratch, we take the approach of motion transformationas the underlying paradigm for generating computer animations. In doing so, we combine the expressive richness of an input animation sequence with the controllability of spacetime optimization to create a wide range of realistic character animations. The spacetime dynamics formulation also allows editing of intuitive, high-level motion concepts such as the time and placement of footprints, length and mass of various extremities, number of body joints and gravity. Our algorithm is well suited for the reuse of highly-detailed captured motion animations. In addition, we describe a new methodology for mapping a motion between characters with drastically different numbers of degrees of freedom. We use this method to reduce the complexity of the spacetime optimization problems. Furthermore, our approach provides a paradigm for controlling complex dynamic and kinematic systems with simpler ones.

A validated three-dimensional computational model of a human knee joint.

Abstract: This paper presents a three-dimensional finite element tibio-femoral joint model of a human knee that was validated using experimental data. The geometry of the joint model was obtained from magnetic resonance (MR) images of a cadaveric knee specimen. The same specimen was biomechanically tested using a robotic/universal force-moment sensor (UFS) system and knee kinematic data under anterior-posterior tibial loads (up to 100 N) were obtained. In the finite element model (FEM), cartilage was modeled as an elastic material, ligaments were represented as nonlinear elastic springs, and menisci were simulated by equivalent-resistance springs. Reference lengths (zero-load lengths) of the ligaments and stiffness of the meniscus springs were estimated using an optimization procedure that involved the minimization of the differences between the kinematics predicted by the model and those obtained experimentally. The joint kinematics and in-situ forces in the ligaments in response to axial tibial moments of up to 10 Nm were calculated using the model and were compared with published experimental data on knee specimens. It was also demonstrated that the equivalent-resistance springs representing the menisci are important for accurate calculation of knee kinematics. Thus, the methodology developed in this study can be a valuable tool for further analysis of knee joint function and could serve as a step toward the development of more advanced computational knee models.

The Tricept robot: Inverse kinematics, manipulability analysis and closed-loop direct kinematics algorithm

Abstract: This paper is aimed at presenting a study on the kinematics of the Tricept robot, which comprises a three-degree-of-freedom (dof) parallel structure having a radial link of variable length. The robot workspace is characterized and the inverse kinematics equation is obtained by using spherical coordinates. The inverse differential kinematics and statics are derived in terms of both an analytical and a geometric Jacobian, and a manipulability analysis along the various workspace directions is developed using the concept of force and velocity ellipsoids. A Jacobian-based Closed-Loop Direct Kinematics (CLDK) algorithm is presented to solve the direct kinematics problem along a given trajectory. Simulation results are illustrated for an industrial robot of the Tricept family.

Automatic Joint Parameter Estimation from Magnetic Motion Capture Data

Abstract: This paper describes a technique for using magnetic motion capture data to determine the joint parameters of an articulated hierarchy. This technique makes it possible to determine limb lengths, joint locations, and sensor placement for a human subject without external measurements. Instead, the joint parameters are inferred with high accuracy from the motion data acquired during the capture session. The parameters are computed by performing a linear least squares fit of a rotary joint model to the input data. A hierarchical structure for the articulated model can also be determined in situations where the topology of the model is not known. Once the system topology and joint parameters have been recovered, the resulting model can be used to perform forward and inverse kinematic procedures. We present the results of using the algorithm on human motion capture data, as well as validation results obtained with data from a simulation and a wooden linkage of known dimensions.

Singularity Analysis of Closed Kinematic Chains

Abstract: This paper presents a coordinate-invariant differential geometric analysis of kinematic singularities for closed kinematic chains containing both active and passive joints. Using the geometric framework developed in Park and Kim (1996) for closed chain manipulability analysis, we classify closed chain singularities into three basic types: (i) those corresponding to singular points of the joint configuration space (configuration space singularities), (ii) those induced by the choice of actuated joints (actuator singularities), and (iii) those configurations in which the end-effector loses one or more degrees of freedom of available motion (end-effector singularities). The proposed geometric classification provides a high-level taxonomy for mechanism singularities that is independent of the choice of local coordinates used to describe the kinematics, and includes mechanisms that have more actuators than kinematic degrees of freedom.

Comparison of variability of initial kinematics and endpoints of reaching movements

Abstract: The accuracy of reaching movements to memorized visual target locations is presumed to be determined largely by central planning processes before movement onset. If so, then the initial kinematics of a pointing movement should predict its endpoint. Our study examined this hypothesis by testing the correlation between peak acceleration, peak velocity, and movement amplitude and the correspondence between the respective spatial positions of these kinematic landmarks. Subjects made planar horizontal reaching movements to targets located at five different distances and along five radially arrayed directions without visual feedback during the movements.The spatial dispersion of the positions of peak acceleration, peak velocity, and endpoint all tended to form ellipses oriented along the movement trajectory. However, whereas the peaks of acceleration and velocity scaled strongly with movement amplitude for all of the movements made at the five target distances in any one direction, the correlations with movement amplitude were more modest for trajectories aimed at each target separately. Furthermore, the spatial variability in direction and extent of the distribution of positions of peak acceleration and peak velocity did not scale differently with target distance, whereas they did for endpoint distributions. Therefore, certain features of the final kinematics are evident in the early kinematics of the movements as predicted by the hypothesis that they reflect planning processes. However, endpoint distributions were not completely predetermined by the Initial kinematics. In contrast, multivariate analysis suggests that adjustments to movement duration help compensate for the variability of the initial kinematics to achieve desired movement amplitude. These compensatory adjustments do not contradict the general conclusion that the systematic patterns in the spatial variability observed in this study reflect planning processes. On the contrary, and consistent with that conclusion, our results provide further evidence that direction and extent of reaching movements are planned and determined in parallel over time.

Composition and decomposition of internal models in motor learning under altered kinematic and dynamic environments.

Abstract: The learning process of reaching movements was examined under novel environments whose kinematic and dynamic properties were altered. We used a kinematic transformation (visuomotor rotation), a dynamic transformation (viscous curl field), and a combination of these transformations. When the subjects learned the combined transformation, reaching errors were smaller if the subject first learned the separate kinematic and dynamic transformations. Reaching errors under the kinematic (but not the dynamic) transformation were smaller if subjects first learned the combined transformation. These results suggest that the brain learns multiple internal models to compensate for each transformation and has some ability to combine and decompose these internal models as called for by the occasion.

A model-based method for the reconstruction of total knee replacement kinematics

Abstract: A better knowledge of the kinematics behavior of total knee replacement (TKR) during activity still remains a crucial issue to validate innovative prosthesis designs and different surgical strategies. Tools for more accurate measurement of in vivo kinematics of knee prosthesis components are therefore fundamental to improve the clinical outcome of knee replacement. In the present study, a novel model-based method for the estimation of the three-dimensional (3-D) position and orientation (pose) of both the femoral and tibial knee prosthesis components during activity is presented. The knowledge of the 3-D geometry of the components and a single plane projection view in a fluoroscopic image are sufficient to reconstruct the absolute and relative pose of the components in space. The technique is based on the best alignment of the component designs with the corresponding projection on the image plane. The image generation process is modeled and an iterative procedure localizes the spatial pose of the object by minimizing the Euclidean distance of the projection rays from the object surface. Computer simulation and static/dynamic in vitro tests using real knee prosthesis show that the accuracy with which relative orientation and position of the components can be estimated is better than 1.5/spl deg/ and 1.5 mm, respectively. In vivo tests demonstrate that the method is well suited for kinematics analysis on TKR patients and that good quality images can be obtained with a carefully positioning of the fluoroscope and an appropriate dosage. With respect to previously adopted template matching techniques, the present method overcomes the complete segmentation of the components on the projected image and also features the simultaneous evaluation of all the six degrees of freedom (DOF) of the object. The expected small difference between successive poses in in vivo sequences strongly reduces the frequency of false poses and both the operator and computation time.

A Divide-and-Conquer Articulated-Body Algorithm for Parallel O(log(n)) Calculation of Rigid-Body Dynamics. Part 1: Basic Algorithm

Abstract: This paper presents a recursive, divide-and-conquer algorithm for calculating the forward dynamics of a robot mechanism, or general rigid-body system, on a parallel computer. It features O(log(n)) time complexity on O(n) processors and is the fastest available algorithm for a computer with a large number of processors and low communications costs. It is an exact, noniterative algorithm and is applicable to mechanisms with any joint type and any topology, including branches and kinematic loops. The algorithm works by recursive application of a formula that constructs the articulatedbody equations of motion of an assembly from those of its constituent parts. The inputs to this formula are the equations of motion of two independent subassemblies, plus a description of how they are to be connected, and the output is the equation of motion of the assembly. Starting with a collection of unconnected rigid bodies, the equations of motion of any rigid-body system can be constructed by repeated application of this ...

An Energy Formulation for Parametric Size and Shape Optimization of Compliant Mechanisms

Abstract: Compliant mechanisms are jointless mechanical devices that take advantage of elastic deformation to achieve a force or motion transformation. An important step toward automated design of compliant mechanisms has been the development of topology optimization techniques. The next logical step is to incorporate size and shape optimization to perform dimensional synthesis of the mechanism while simultaneously considering practical design specifications such as kinematic and stress constraints. An improved objective formulation based on maximizing the energy throughput of a linear static compliant mechanism is developed considering specific force and displacement operational requirements. Parametric finite element beam models are used to perform the size and shape optimization. This technique allows stress constraints to limit the maximum stress in the mechanism. In addition, constraints which restrict the kinematics of the mechanism are successfully applied to the optimization problem. Resulting optimized mechanisms exhibit efficient mechanical transmission and meet kinematic and stress requirements. Several examples are given to demonstrate the effectiveness of the optimization procedure.

The dynamics of goal-directed rhythmical aiming.

Abstract: Based on the kinematics of goal-directed aiming movements in a reciprocal Fitts' task, a minimal limit cycle model is proposed that is capable of producing the behavior observed at levels of task difficulty ranging from 3 to 7. From graphical and statistical analyses of the phase planes, Hooke's planes and velocity profiles, we concluded that the minimal terms to be included in the model were (i) a nonlinear damping in the form of a self-sustaining, velocity-driven Rayleigh oscillator and (ii) a nonlinear stiffness in the form of a softening spring Duffing term. The model reproduced the kinematic patterns experimentally observed in rhythmical precision aiming, accounting for 95% of the variance. The coefficients in the model changed in a systematic way when distance and precision constraints were varied, and the meaning of these changes is discussed in the framework of the dynamical patterns approach.

Feedback control for robotic manipulator with an uncertain Jacobian matrix

Abstract: In most applications of robots, a desired path for the end-effector is usually specified in task space such as Cartesian space. One way to move the robot along this path is to solve the inverse kinematics problem to generate the desired angles in joint space. However, it is a very time consuming task to solve the inverse kinematics problem. Furthermore, in the presence of uncertainty in kinematics, it is impossible to derive the desired joint angle from the desired end-effector path and the Jacobian matrix of the mapping from joint space to task space. In this article, a feedback control law using an uncertain Jacobian matrix is proposed for setpoint control of robots. Sufficient conditions for the bound of the estimated Jacobian matrix and stability conditions for the feedback gains are presented to guarantee the stability and passivity of the robots. A gravity regressor with an uncertain Jacobian matrix is also proposed for gravitational force compensation when the gravitational force is uncertain. Simulation results are presented to illustrate the performance of the proposed controllers. ©1999 John Wiley & Sons, Inc.

Molecular Gas Kinematics in Barred Spiral Galaxies

Abstract: To quantify the effect that bar-driven mass inflow can have on the evolution of a galaxy requires an understanding of the dynamics of the inflowing gas. In this paper we study the kinematics of the dense molecular gas in a set of seven barred spiral galaxies to determine which dynamical effects dominate. The kinematics are derived from observations of the CO J = (1-0) line made with the Berkeley-Illinois-Maryland Association (BIMA) millimeter array. We compare the observed kinematics with those predicted by ideal gas hydrodynamic and ballistic-cloud-based models of gas flow in a barred potential. The hydrodynamic model is in good qualitative agreement with both the current observations of the dense gas and previous observations of the kinematics of the ionized gas. The observed kinematics indicate that the gas abruptly changes direction upon entering the dust lanes to flow directly down the dust lanes along the leading edge of the bar until the dust lanes approach the nuclear ring. Near the location where the dust lanes intersect the nuclear ring, we see two velocity components: a low-velocity component, corresponding to gas on circular orbits, and a higher velocity component, which can be attributed to the fraction of gas flowing down the bar dust lane that sprays past the contact point toward the other half of the bar. The ballistic-cloud-based model of the ISM is not consistent with the observed kinematics. The kinematics in the dust lanes require large velocity gradients that cannot be reproduced by an ISM composed of ballistic clouds with long mean free paths. Therefore, even the dense ISM responds to hydrodynamic forces.

Capturing articulated human hand motion: a divide-and-conquer approach

Abstract: The use of the human hand as a natural interface device serves as a motivating force for research in the modeling, analysis and capture of the motion of an articulated hand. Model-based hand motion capture can be formulated as a large nonlinear programming problem, but this approach is plagued by local minima. An alternative way is to use analysis-by-synthesis by searching a huge space, but the results are rough and the computation expensive. In this paper, articulated hand motion is decoupled, a new two-step iterative model-based algorithm is proposed to capture articulated human hand motion, and a proof of convergence of this iterative algorithm is also given. In our proposed work, the decoupled global hand motion and local finger motion are parameterized by the 3D hand pose and the state of the hand respectively. Hand pose determination is formulated as a least-median-of-squares (LMS) problem rather than the nonrobust least-squares (LS) problem, so that 3D hand pose can be reliably calculated even if there are outliers. Local finger motion is formulated as an inverse kinematics problem. A genetic algorithm-based method is proposed to find a sub-optimal solution of the inverse kinematics effectively. Our algorithm and the LS-based algorithm are compared in several experiments. Both algorithms converge when local finger motion between consecutive frames is small. When large finger motion is present, the LS-based method fails, but our algorithm can still estimate the global and local finger motion well.

Do arm postures vary with the speed of reaching

Abstract: Do arm postures vary with the speed of reaching? For reaching movements in one plane, the hand has been observed to follow a similar path regardless of speed. Recent work on the control of more complex reaching movements raises the question of whether a similar "speed invariance" also holds for the additional degrees of freedom. Therefore we examined human arm movements involving initial and final hand locations distributed throughout the three-dimensional (3D) workspace of the arm. Despite this added complexity, arm kinematics (summarized by the spatial orientation of the "plane of the arm" and the 3D curvature of the hand path) changed very little for movements performed over a wide range of speeds. If the total force (dynamic + quasistatic) had been optimized by the control system (e.g., as in a minimization of the change in joint torques or the change in muscular forces), the optimal solution would change with speed; slow movements would reflect the minimal antigravity torques, whereas fast movements would be more strongly influenced by dynamic factors. The speed-invariant postures observed in this study are instead consistent with a hypothesized optimization of only the dynamic forces.

Tracking and Modifying Upper-body Human Motion Data with Dynamic Simulation

Abstract: Character animations produced with motion capture data have many of the stylistic details seen in human motion while those generated with simulation are physically realistic for the dynamic parameters of the character. We combine these two approaches by tracking and modifying human motion capture data using dynamic simulation and constraints. The tracking system generates motion that is appropriate for the graphical character while maintaining characteristics of the original human motion. The system imposes contact and task constraints to add dynamic impacts for interactions with the environment and to modify motions at the behavior level. The system is able to edit motion data to account for changes in the character and the environment as well as create smooth transitions between motion capture sequences. We demonstrate the power of combining these two approaches by tracking data for a variety of upper-body motions and by animating models with differing kinematic and dynamic parameters.

A Lagrangian network for kinematic control of redundant robot manipulators

Abstract: A recurrent neural network, called the Lagrangian network, is presented for the kinematic control of redundant robot manipulators. The optimal redundancy resolution is determined by the Lagrangian network through real-time solution to the inverse kinematics problem formulated as a quadratic optimization problem. While the signal for a desired velocity of the end-effector is fed into the inputs of the Lagrangian network, it generates the joint velocity vector of the manipulator in its outputs along with the associated Lagrange multipliers. The proposed Lagrangian network is shown to be capable of asymptotic tracking for the motion control of kinematically redundant manipulators.

The kinematic roadmap: a motion planning based global approach for inverse kinematics of redundant robots

Abstract: This paper proposes a novel and global approach to solving the point-to-point inverse kinematics problem for highly redundant manipulators. Given an initial configuration of the robot, the problem is to find a reachable configuration that corresponds to a desired position and orientation of the end-effector. Central to our approach is the novel notion of kinematic roadmap for a manipulator. The kinematic roadmap captures the connectivity of the connected component of the free configuration space of the manipulator in a finite graph like structure. The point-to-point inverse kinematics problem is then solved using this roadmap. We provide completeness results for our algorithm. Our implementation of SEARCH is an efficient closed form solution, albeit local, to inverse kinematics that exploits the serial kinematic structure of serial manipulator arms. Initial experiments with a 7-DOF manipulator have been extremely successful.

Kinematic time-invariant control of a 2D nonholonomic vehicle

Abstract: A closed loop, time-invariant and globally stable control law for a bicycle-like kinematic model is proposed. The resulting paths are smooth and the curvature bounded on the whole state space trajectories. As linear velocity can be kept arbitrary small, thus avoiding large lateral accelerations and actuator saturation problems, it is suggested that the proposed law may be also adopted for the planar control of autonomous underwater vehicles. The target configuration is always approached on a straight line and the vehicle is requested to move in only one specified forward direction thus avoiding cusps in the paths and satisfying a major requirement for the implementation of such strategy on many real systems.