Showing papers on "Kinematics published in 2014"

A Variable Curvature Continuum Kinematics for Kinematic Control of the Bionic Handling Assistant

Abstract: We present a new variable curvature continuum kinematics for multisection continuum robots with arbitrarily shaped backbone curves assembled from sections with three degrees of freedom (DoFs) (spatial bending and extension, no torsion). For these robots, the forward kinematics and the differential forward kinematics are derived. The proposed model approach is capable of reproducing both the constant and variable backbone curvature in a closed form. It describes the deformation of a single section with a finite number of serially connected circular arcs. This yields a section model with piecewise constant and, thus, a variable section curvature. Model accuracy and its suitability for kinematic real-time control applications are demonstrated with simulations and experimental data. To solve the redundant inverse kinematics problem, a local resolution of redundancy at the velocity level through the use of the robot's Jacobian matrix is presented. The Jacobian is derived analytically, including a concept for regularization in singular configurations. Experimental data are recorded with Festo's Bionic Handling Assistant. This continuum robot is chosen for experimental validation, as it consists of a variable backbone curvature because of its conically tapering shape.

Assessment of hand kinematics using inertial and magnetic sensors

Abstract: Assessment of hand kinematics is important when evaluating hand functioning. Major drawbacks of current sensing glove systems are lack of rotational observability in particular directions, labour intensive calibration methods which are sensitive to wear and lack of an absolute hand orientation estimate. We propose an ambulatory system using inertial sensors that can be placed on the hand, fingers and thumb. It allows a full 3D reconstruction of all finger and thumb joints as well as the absolute orientation of the hand. The system was experimentally evaluated for the static accuracy, dynamic range and repeatability. The RMS position norm difference of the fingertip compared to an optical system was 5±0.5 mm (mean ± standard deviation) for flexion-extension and 12.4±3.0 mm for combined flexion-extension abduction-adduction movements of the index finger. The difference between index and thumb tips during a pinching movement was 6.5±2.1 mm. The dynamic range of the sensing system and filter was adequate to reconstruct full 80 degrees movements of the index finger performed at 116 times per minute, which was limited by the range of the gyroscope. Finally, the reliability study showed a mean range difference over five subjects of 1.1±0.4 degrees for a flat hand test and 1.8±0.6 degrees for a plastic mold clenching test, which is smaller than other reported data gloves. Compared to existing data gloves, this research showed that inertial and magnetic sensors are of interest for ambulatory analysis of the human hand and finger kinematics in terms of static accuracy, dynamic range and repeatability. It allows for estimation of multi-degree of freedom joint movements using low-cost sensors.

Comparison of markerless and marker-based motion capture technologies through simultaneous data collection during gait: proof of concept.

Abstract: During the last decade markerless motion capture techniques have gained an increasing interest in the biomechanics community In the clinical field, however, the application of markerless techniques is still debated This is mainly due to a limited number of papers dedicated to the comparison with the state of the art of marker based motion capture, in term of repeatability of the three dimensional joints' kinematics In the present work the application of markerless technique to data acquired with a marker-based system was investigated All videos and external data were recorded with the same motion capture system and included the possibility to use markerless and marker-based methods simultaneously Three dimensional markerless joint kinematics was estimated and compared with the one determined with traditional marker based systems, through the evaluation of root mean square distance between joint rotations In order to compare the performance of markerless and marker-based systems in terms of clinically relevant joint angles estimation, the same anatomical frames of reference were defined for both systems Differences in calibration and synchronization of the cameras were excluded by applying the same wand calibration and lens distortion correction to both techniques Best results were achieved for knee flexion-extension angle, with an average root mean square distance of 1175 deg, corresponding to 1835% of the range of motion Sagittal plane kinematics was estimated better than on the other planes also for hip and ankle (root mean square distance of 1762 deg eg 4466%, and 717 deg eg 3312%), meanwhile estimates for hip joint were the most incorrect This technique enables users of markerless technology to compare differences with marker-based in order to define the degree of applicability of markerless technique

Trajectory tracking with collision avoidance for nonholonomic vehicles with acceleration constraints and limited sensing

Abstract: Nowadays, autonomously operated nonholonomic vehicles are employed in a wide range of applications, ranging from relatively simple household chores (e.g. carpet vacuuming and lawn mowing) to highly sophisticated assignments (e.g. outer space exploration and combat missions). Each application may require different levels of accuracy and capabilities from the vehicles, yet, all expect the same critical outcome: to safely complete the task while avoiding collisions with obstacles and the environment. Herein, we report on a bounded control law for nonholonomic systems of unicycle-type that satisfactorily drive a vehicle along a desired trajectory while guaranteeing a minimum safe distance from another vehicle or obstacle at all times. The control law is comprised of two parts. The first is a trajectory tracking and set-point stabilization control law that accounts for the vehicle's kinematic and dynamic constraints (i.e. restrictions on velocity and acceleration). We show that the bounded tracking control law enforces global asymptotic convergence to the desired trajectory and local exponential stability of the full state vector in the case of set-point stabilization. The second part is a real-time avoidance control law that guarantees collision-free transit for the vehicle in noncooperative and cooperative scenarios independently of bounded uncertainties and errors in the obstacles' detection process. The avoidance control acts locally, meaning that it is only active when an obstacle is close and null when the obstacle is safely away. Moreover, the avoidance control is designed according to the vehicle's acceleration limits to compensate for lags in the vehicle's reaction time. The performance of the synthesized control law is then evaluated and validated via simulation and experimental tests.

Adaptive Control of Robot Manipulators With Uncertain Kinematics and Dynamics

Abstract: In this paper, we investigate the adaptive control problem for robot manipulators with both the uncertain kinematics and dynamics. We propose two adaptive control schemes to realize the objective of task-space trajectory tracking irrespective of the uncertain kinematics and dynamics. The proposed controllers have the desirable separation property, and we also show that the first adaptive controller with appropriate modifications can yield improved performance, without the expense of conservative gain choice. The performance of the proposed controllers is shown by numerical simulations.

Quadrupedal locomotion using hierarchical operational space control

Abstract: This paper presents the application of operational space control based on hierarchical task optimization for quadrupedal locomotion. We show how the behavior of a complex robotic machine can be described by a simple set of least squares problems with different priorities for motion, torque, and force optimization. Using projected dynamics of floating base systems with multiple contact points, the optimization dimensionality can be reduced or decoupled such that the formulation is purely based on the inversion of kinematic system properties. The present controller is extensively tested in various experiments using the fully torque controllable quadrupedal robot StarlETH. The load distribution is optimized for static walking gaits to improve contact stability and/or actuator efficiency under various terrain conditions. This is augmented with simultaneous joint position and torque limitations as well as with an interpolation method to ensure smooth contact transitions. The same control structure is further used to stabilize dynamic trotting gaits under significant external disturbances such as uneven ground or pushes. To the best of our knowledge, this work is the first documentation of static and dynamic locomotion with pure task-space inverse dynamics (no joint position feedback) control.

Kinematics of transition during human accelerated sprinting.

Abstract: This study investigated kinematics of human accelerated sprinting through 50 m and examined whether there is transition and changes in acceleration strategies during the entire acceleration phase. Twelve male sprinters performed a 60-m sprint, during which step-to-step kinematics were captured using 60 infrared cameras. To detect the transition during the acceleration phase, the mean height of the whole-body centre of gravity (CG) during the support phase was adopted as a measure. Detection methods found two transitions during the entire acceleration phase of maximal sprinting, and the acceleration phase could thus be divided into initial, middle, and final sections. Discriminable kinematic changes were found when the sprinters crossed the detected first transition—the foot contacting the ground in front of the CG, the knee-joint starting to flex during the support phase, terminating an increase in step frequency—and second transition—the termination of changes in body postures and the start of a slight decrease in the intensity of hip-joint movements, thus validating the employed methods. In each acceleration section, different contributions of lower-extremity segments to increase in the CG forward velocity—thigh and shank for the initial section, thigh, shank, and foot for the middle section, shank and foot for the final section—were verified, establishing different acceleration strategies during the entire acceleration phase. In conclusion, there are presumably two transitions during human maximal accelerated sprinting that divide the entire acceleration phase into three sections, and different acceleration strategies represented by the contributions of the segments for running speed are employed.

Complementary Observer for Body Segments Motion Capturing by Inertial and Magnetic Sensors

Abstract: This paper presents a viable quaternion-based complementary observer (CO) that is designed for rigid body attitude estimation. We claim that this approach is an alternative one to overcome the limitations of the extended Kalman filter. The CO processes data from a small inertial/magnetic sensor module containing triaxial angular rate sensors, accelerometers, and magnetometers, without resorting to GPS data. The proposed algorithm incorporates a motion kinematic model and adopts a two-layer filter architecture. In the latter, the Levenberg Marquardt algorithm preprocesses acceleration and local magnetic field measurements, to produce what will be called the system's output. The system's output together with the angular rate measurements will become measurement signals for the CO. In this way, the overall CO design is greatly simplified. The efficiency of the CO is experimentally investigated through an industrial robot and a commercial IMU during human segment motion exercises. These results are promising for human motion applications, in particular future ambulatory monitoring.

Review on Kinematics Calibration Technology of Serial Robots

Abstract: Robot kinematics calibration is of great significance for improving robot absolute pose accuracy, which can be divided into modelbased and non-parametric kinematics calibration. For model-based kinematics calibration, kinematics calibration modeling, pose measurement of end-effector, kinematics parameters calibration and error compensation are systematically analyzed. And with the increasing demand for autonomy, the autonomous kinematics calibration is introduced. On the other hand, research status of nonparametric kinematics calibration is elaborated, the advantages and disadvantage of which are discussed respectively. On the basis, comprehensive and organized description and summarization of the three kinds of calibrations are given. Overall, aiming at robot kinematics calibration, existing achievements are summarized, a typical calibration process is carried out and calibration precautions are detailed, then calibration results of various methods are compared and analyzed. Finally, existing problems in kinematics calibration are analyzed and development prospects are presented.

Fast interpolation and time-optimization with contact

Abstract: This paper presents a method for generating dynamically feasible, keyframe-interpolating motions for robots undergoing contact, such as in legged locomotion and manipulation. The first stage generates a twice-differentiable interpolating path that obeys kinematic contact constraints up to a user-specified tolerance. The second stage optimizes speeds along the path to minimize time while satisfying dynamic constraints. The method supports velocity, acceleration, and torque constraints, and polyhedral contact friction constraints at an arbitrary number of contact points. The method is numerically stable, and empirical running time is weakly linear in the number of degrees of freedom and polynomial in the time-domain grid resolution. Experiments demonstrate that full-body motions for robots with 100 degrees of freedom and dozens of contact points are calculated in seconds.

Li-function activated ZNN with finite-time convergence applied to redundant-manipulator kinematic control via time-varying Jacobian matrix pseudoinversion

Abstract: HighlightsThe LFAZNN model is developed for time-varying Jacobian matrix pseudoinversion.This paper presents the theoretical result about the LFAZNN finite-time convergence.This paper further shows the LFAZNN application to robots' kinematic control.Simulation results demonstrate well the effectiveness of the LFAZNN model. This paper presents and investigates the application of Zhang neural network (ZNN) activated by Li function to kinematic control of redundant robot manipulators via time-varying Jacobian matrix pseudoinversion. That is, by using Li activation function and by computing the time-varying pseudoinverse of the Jacobian matrix (of the robot manipulator), the resultant ZNN model is applied to redundant-manipulator kinematic control. Note that there are nine novelties and differences of ZNN from the conventional gradient neural network in the research methodology. More importantly, such a Li-function activated ZNN (LFAZNN) model has the property of finite-time convergence (showing its feasibility to redundant-manipulator kinematic control). Simulation results based on a four-link planar robot manipulator and a PA10 robot manipulator further demonstrate the effectiveness of the presented LFAZNN model, as well as show the LFAZNN application prospect.

Type Synthesis of 3-DOF RPR-Equivalent Parallel Mechanisms

Abstract: The moving platform of an RPR-equivalent parallel mechanism (PM) can undergo a 3-degree-of-freedom (DOF) motion that is the product of a rotation followed by a translation and another rotation. A 5-DOF hybrid parallel manipulator can be developed by adding an x-y gantry or an RR serial mechanism to an RPR-equivalent PM, which is suitable for manipulations requiring high rigidity and accuracy with good dexterity along surfaces of the 3-D space. This paper investigates the type synthesis of the RPR-equivalent PM. First, the RPR motion is briefly discussed. Then, the kinematic bonds of limb chains and their mechanical generators are presented. Structural conditions for constructing an RPR-equivalent PM are presented. Furthermore, the RPR-equivalent PMs are classified into several categories, depending on the DOF of its limb chains. Numerous new architectures of the RPR-equivalent PMs are synthesized.

Model-based Prediction of Skid-steer Robot Kinematics Using Online Estimation of Track Instantaneous Centers of Rotation

Abstract: This paper presents a kinematic extended Kalman filter EKF designed to estimate the location of track instantaneous centers of rotation ICRs and aid in model-based motion prediction of skid-steer robots. Utilizing an ICR-based kinematic model has resulted in impressive odometry estimates for skid-steer movement in previous works, but estimation of ICR locations was performed offline on recorded data. The EKF presented here utilizes a kinematic model of skid-steer motion based on ICR locations. The ICR locations are learned by the filter through the inclusion of position and heading measurements. A background on ICR kinematics is presented, followed by the development of the ICR EKF. Simulation results are presented to aid in the analysis of noise and bias susceptibility. The experimental platforms and sensors are described, followed by the results of filter implementation. Extensive field testing was conducted on two skid-steer robots, one with tracks and another with wheels. ICR odometry using learned ICR locations predicts robot position with a mean error of -0.42i¾?m over 40.5i¾?m of travel during one tracked vehicle test. A test consisting of driving both vehicles approximately 1,000i¾?m shows clustering of ICR estimates for the duration of the run, suggesting that ICR locations do not vary significantly when a vehicle is operated with low dynamics.

Ability of Sagittal Kinematic Variables to Estimate Ground Reaction Forces and Joint Kinetics in Running

Abstract: Study Design Controlled laboratory study, cross-sectional design. Objective To determine if sagittal kinematic variables can be used to estimate select running kinetics. Background Excessive loading during running has been implicated in a variety of injuries, yet this information is typically not assessed during a standard clinical examination. Developing a clinically feasible strategy to estimate ground reaction forces and joint kinetics may improve the ability to identify those at an increased risk of injury. Methods Three-dimensional kinematics and ground reaction forces of 45 participants were recorded during treadmill running at self-selected speed. Kinematic variables used to estimate specific kinetic metrics included vertical excursion of the center of mass, foot inclination angle at initial contact, horizontal distance between the center of mass and heel at initial contact, knee flexion angle at initial contact, and peak knee flexion angle during stance. Linear mixed-effects models were fitted to ...

Human-robot interaction: kinematics and muscle activity inside a powered compliant knee exoskeleton.

Abstract: Until today it is not entirely clear how humans interact with automated gait rehabilitation devices and how we can, based on that interaction, maximize the effectiveness of these exoskeletons. The goal of this study was to gain knowledge on the human-robot interaction, in terms of kinematics and muscle activity, between a healthy human motor system and a powered knee exoskeleton (i.e., KNEXO). Therefore, temporal and spatial gait parameters, human joint kinematics, exoskeleton kinetics and muscle activity during four different walking trials in 10 healthy male subjects were studied. Healthy subjects can walk with KNEXO in patient-in-charge mode with some slight constraints in kinematics and muscle activity primarily due to inertia of the device. Yet, during robot-in-charge walking the muscular constraints are reversed by adding positive power to the leg swing, compensating in part this inertia. Next to that, KNEXO accurately records and replays the right knee kinematics meaning that subject-specific trajectories can be implemented as a target trajectory during assisted walking. No significant differences in the human response to the interaction with KNEXO in low and high compliant assistance could be pointed out. This is in contradiction with our hypothesis that muscle activity would decrease with increasing assistance. It seems that the differences between the parameter settings of low and high compliant control might not be sufficient to observe clear effects in healthy subjects. Moreover, we should take into account that KNEXO is a unilateral, 1 degree-of-freedom device.

Towards Biomimetic Virtual Constraint Control of a Powered Prosthetic Leg

Abstract: This brief presents a novel control strategy for a powered prosthetic ankle based on a biomimetic virtual constraint. We first derive a kinematic constraint for the “effective shape” of the human ankle-foot complex during locomotion. This shape characterizes ankle motion as a function of the center of pressure (COP)-the point on the foot sole where the resultant ground reaction force is imparted. Since the COP moves monotonically from heel to toe during steady walking, we adopt the COP as a mechanical representation of the gait cycle phase in an autonomous feedback controller. We show that our kinematic constraint can be enforced as a virtual constraint by an output linearizing controller that uses only feedback available to sensors onboard a prosthetic leg. Using simulations of a passive walking model with feet, we show that this novel controller enforces exactly the desired effective shape, whereas a standard impedance (i.e., proportional-derivative) controller cannot. This brief provides a single, biomimetic control law for the entire single-support period during robot-assisted locomotion.

Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression

Abstract: Precise control of industrial automation systems with non-linear kinematics due to joint elasticity, variation in cable tensioning, or backlash is challenging; especially in systems that can only be controlled through an interface with an imprecise internal kinematic model. Cable-driven Robotic Surgical Assistants (RSAs) are one example of such an automation system, as they are designed for master-slave teleoperation. We consider the problem of learning a function to modify commands to the inaccurate control interface such that executing the modified command on the system results in a desired state. To achieve this, we must learn a mapping that accounts for the non-linearities in the kinematic chain that are not accounted for by the system's internal model. Gaussian Process Regression (GPR) is a data-driven technique that can estimate this non-linear correction in a task-specific region of state space, but it is sensitive to corruption of training examples due to partial occlusion or lighting changes. In this paper, we extend the use of GPR to learn a non-linear correction for cable-driven surgical robots by using i) velocity as a feature in the regression and ii) removing corrupted training observations based on rotation limits and the magnitude of velocity. We evaluate this approach on the Raven II Surgical Robot on the task of grasping foam “damaged tissue” fragments, using the PhaseSpace LED-based motion capture system to track the Raven end-effector. Our main result is a reduction in the norm of the mean position error from 2.6 cm to 0.2 cm and the norm of the mean angular error from 20.6 degrees to 2.8 degrees when correcting commands for a set of held-out trajectories. We also use the learned mapping to achieve a 3.8× speedup over past results on the task of autonomous surgical debridement. Further information on this research, including data, code, photos, and video, is available at http: //rll.berkeley.edu/surgical.

Kinematics modeling and experimental verification of baxter robot

Abstract: The Baxter® humanoid robot made by Rethink Robotics™ offers users an affordable platform with guaranteed safety for both academic and industrial applications. The platform provides the users a good opportunity to carry out research on dual-arm robot manipulation and vision based control. For simulation of the Baxter® robot, a proper kinematic and dynamic model should be built. The Baxter robot uses URDF file to describe the robot kinematics, i.e., the relationship between adjacent joint and link. Consider the large difference between the structure of URDF and the conventional Denavit-Hartenburg(DH) notations which are widely used in robotics literature, we perform rigorous theoretic analysis of kinematics of Baxter® robot including all limbs. A kinematics model has been built following DH convention, and has been implemented in the MATLAB Robotics Toolbox. Extensive comparison between simulation and experimental results has verified the validity of the kinematic model.

Localization and velocity tracking of human via 3 IMU sensors

Abstract: In sports training and exercises like walking and jogging, the velocity and position of the exercise people is very crucial for motion evaluation. A simple wearable system and corresponding method for velocity monitoring using minimal sensors can be very useful for daily use. In this work, a velocity tracking and localization method using only three IMU sensors is introduced. The three sensors are located at the right shank, right thigh and the pelvis to measure the kinematics of the lower limbs. In the method, a reference root point on the pelvis is chosen to represent the velocity and location of the person. Through acceleration fine tuning algorithm, the acceleration data is refined and combined with the velocity calculated from body kinematics to get a drift-free and accurate 3D velocity result. The location of the person is tracked based on this velocity estimation and the limb kinematic subsequently. The benchmark study with the commercial optical reference shows that the error in velocity tracking is within 0.1 m/s and localization accuracy is within 2% in both normal walking, jogging and jumping. Due to the conveniences of the small-size wearable IMU sensors, this proposed velocity tracking and localization method is very useful in everyday exercises both indoor and outdoor.

Robust stabilization for a class of dynamic feedback uncertain nonholonomic mobile robots with input saturation

Abstract: In this paper, the robust stabilization problem is addressed for a class of dynamic feedback uncertain nonholonomic mobile robots with input saturation Firstly, a continuous, time varying, saturated controller is presented for the kinematic system of the robots Secondly, for the dynamic feedback system, a special derivable, saturated kinematic controller with slope restrictions is selected as a virtual control law that can be tracked by the real generalized velocity in a finite time, furthermore, the dynamic input signals are continuous and saturated at any time The systematic strategy combines the theory of finite-time stability with the virtual-controller-tracked method Finally, the simulation results show the effectiveness of the proposed controller design approach

Design of a Novel 4-DOF Wrist-Type Surgical Instrument With Enhanced Rigidity and Dexterity

Abstract: This paper presents a new type of 4-degree-of-freedom (DOF) robotic surgical instrument for a minimally invasive surgical robot system. The forceps wrist mechanism was designed here on the basis of the 3-DOF parallel structure with three prismatic-spherical-revolute kinematic chains. The pitch and yaw motions of the moving platform generated the wrist rotational motions of the forceps. The axial translation of the parallel mechanism was converted into the forceps grasp motion by an inversion of the slider-crank mechanism. Furthermore, for a more dexterous movement of the forceps, a full revolution of the forceps for the axial rotation is also possible with the instrument. While the proposed instrument realized all the required DOFs of a forceps, the parallel structure of the wrist and the driving mechanism that was designed using only rod elements made the proposed instrument more reliable and rigid than other wire-driven instruments. The kinematic constraints and inverse kinematics of the proposed instrument were derived. Furthermore, the screw-based Jacobian was formulated geometrically, and the static force relation and the linear constraints on a twist were derived. Finally, a prototype of the proposed instrument with a diameter of 8 mm was introduced, and the performance of the prototype was verified through several experiments.

Optimizing curvature sensor placement for fast, accurate shape sensing of continuum robots

Abstract: Robot control requires the rapid computation of robot shape, which for continuum robots typically involves solving complex mechanics-based models. Furthermore, shape computation based on kinematic input variables can be inaccurate due to parameter errors and model simplification. An alternate approach is to compute the shape in real-time from a set of sensors positioned along the length of the robot that provide measurements of local curvature, e.g., optical fiber Bragg gratings. This paper proposes a general framework for selecting the number and placement of such sensors with respect to arclength so as to compute the forward kinematic solution accurately and quickly. The approach is based on defining numerically-efficient shape reconstruction models parameterized by sensor number and location. Optimization techniques are used to find the sensor locations that minimize shape and tip error between a reconstruction model and a mechanics-based model. As a specific example, several reconstruction models are proposed and compared for concentric tube robots. These results indicate that the choice of reconstruction model as well as sensor placement can have a substantial effect on robot shape estimation.