Object Center Of Mass Research Articles

Angular attitude estimation algorithm using signals of Global Navigation Systems

Navigation apparatus of Global Positioning Systems are wildly used in many applications one of which is attitude determination using global satellite navigation signals, one of which is angular attitude determination. One of effective approach to this task is based on representation an object motion as linear motion along line-of-site and rotation about object center of mass. From this consideration it followed deferent tracking systems on signal parameters that connected with linear motion along line-of-site and on signal parameters that connected with rotation about object center of mass. In the article this approach is developed for synthesis of angular attitude estimation using signals of Global Navigation Systems for two-stage processing in navigation apparatus in coherent mode. Objective. To get more effective algorithm of angular attitude estimation using signals of Global Navigation Systems.

Object-centered sensorimotor bias of torque control in the chronic stage following stroke

When lifting objects whose center of mass (CoM) are not centered below the handle one must compensate for arising external torques already at lift-off to avoid object tilt. Previous studies showed that finger force scaling during object lifting may be impaired at both hands following stroke. However, torque control in object manipulation has not yet been studied in patients with stroke. In this pilot study, thirteen patients with chronic stage left hemispheric stroke (SL), nine patients with right hemispheric stroke (SR) and hand-matched controls had to grasp and lift an object with the fingertips of their ipsilesional hand at a handle while preventing object tilt. Object CoM and therewith the external torque was varied by either relocating a covert weight or the handle. The compensatory torque at lift-off (Tcom) is the sum of the torque resulting from (1) grip force being produced at different vertical finger positions (∆CoP × GF) and (2) different vertical load forces on both sides of the handle (∆Fy × w/2). When having to rely on sensorimotor memories, ∆CoP × GF was elevated when the object CoM was on the ipsilesional-, but decreased when CoM was on the contralesional side in SL, whereas ∆Fy × w/2 was biased in the opposite direction, resulting in normal Tcom. SR patients applied a smaller ∆CoP × GF when the CoM was on the contralesional side. Torques were not altered when geometric cues were available. Our findings provide evidence for an object-centered spatial bias of manual sensorimotor torque control with the ipsilesional hand following stroke reminiscent of premotor neglect. Both intact finger force-to-position coordination and visuomotor control may compensate for the spatial sensorimotor bias in most stroke patients. Future studies will have to confirm the found bias and evaluate the association with premotor neglect.

Center-of-Mass-Based Grasp Pose Adaptation Using 3D Range and Force/Torque Sensing

Lifting objects, whose mass may produce high wrist torques that exceed the hardware strength limits, could lead to unstable grasps or serious robot damage. This work introduces a new Center-of-Mass (CoM)-based grasp pose adaptation method, for picking up objects using a combination of exteroceptive 3D perception and proprioceptive force/torque sensor feedback. The method works in two iterative stages to provide reliable and wrist torque efficient grasps. Initially, a geometric object CoM is estimated from the input range data. In the first stage, a set of hand-size handle grasps are localized on the object and the closest to its CoM is selected for grasping. In the second stage, the object is lifted using a single arm, while the force and torque readings from the sensor on the wrist are monitored. Based on these readings, a displacement to the new CoM estimation is calculated. The object is released and the process is repeated until the wrist torque effort is minimized. The advantage of our method is the blending of both exteroceptive (3D range) and proprioceptive (force/torque) sensing for finding the grasp location that minimizes the wrist effort, potentially improving the reliability of the grasping and the subsequent manipulation task. We experimentally validate the proposed method by executing a number of tests on a set of objects that include handles, using the humanoid robot WALK-MAN.

Control Strategy Based on Swarms Algorithms to Cooperative Payload Transport Using a Non-Holonomic Mobile Robots Group

Cooperative payload transport´s systems commonly use schemes of coordination and control in order to maintain the formation of the robots involved in the transport task. For this purpose the leader follower algorithm or any of its variations is used. However this kind of systems use, in most cases, control schemes that do not consider in their design the influence of payload physical properties such as geometry, weight, position of center of mass and density. In this scenario, the classic coordination schemas as the leader following causes a considerable loss of efficiency. For this reason, in this work a swarm based control strategy is proposed in order to estimate the object center of mass dynamically. In this way, an explicit, non-centralized coordination schema, which is oriented to the development of payload transport task in structured environments. The results obtained in this work are focused on measuring system stability, robot control efforts and trajectory pose errors. Different trajectories were tested, and the results compared with the classic coordination method of leader following.

The influence of object shape and center of mass on grasp and gaze.

Recent experiments examining where participants look when grasping an object found that fixations favor the eventual index finger landing position on the object. Even though the act of picking up an object must involve complex high-level computations such as the visual analysis of object contours, surface properties, knowledge of an object’s function and center of mass (COM) location, these investigations have generally used simple symmetrical objects – where COM and horizontal midline overlap. Less research has been aimed at looking at how variations in object properties, such as differences in curvature and changes in COM location, affect visual and motor control. The purpose of this study was to examine grasp and fixation locations when grasping objects whose COM was positioned to the left or right of the objects horizontal midline (Experiment 1) and objects whose COM was moved progressively further from the midline of the objects based on the alteration of the object’s shape (Experiment 2). Results from Experiment 1 showed that object COM position influenced fixation locations and grasp locations differently, with fixations not as tightly linked to index finger grasp locations as was previously reported with symmetrical objects. Fixation positions were also found to be more central on the non-symmetrical objects. This difference in gaze position may provide a more holistic view, which would allow both index finger and thumb positions to be monitored while grasping. Finally, manipulations of COM distance (Experiment 2) exerted marked effects on the visual analysis of the objects when compared to its influence on grasp locations, with fixation locations more sensitive to these manipulations. Together, these findings demonstrate how object features differentially influence gaze vs. grasp positions during object interaction.

CAD-based 3D objects recognition in monocular images for mobile augmented reality

In order to improve registration performance of mobile augmented reality initialization, a new CAD-based recognition method of 3D objects in monocular images is proposed in this paper. Instead of estimating camera pose directly, our method attempts to estimate 3D object pose in the camera coordinate system. The geometric correspondence between the object mass center and its projection on 2D camera image is used to estimate object position. To hypothesize possible azimuths of the object, the 3D CAD model is off-screen rendered with OpenGL ES at different azimuths under an assumed inclination constraint provided by the inertial sensors of mobile devices, and compared with input image by contours matching. Unlike most recognition methods based on machine learning and natural features detection, which require large databases of real images and heavy computational consumption, our method only needs the CAD model of the 3D object in offline stage, and is computationally suitable for mobile devices. This paper describes the details of the method and shows its effectiveness with experiments.

A new observer-based adaptive controller for cooperative handling of an unknown object

SUMMARYThis paper presents a new observer-based adaptive controller for handling an object withunknowngeometry, center of mass, and inertia using a cooperative robotic system. The cooperative robotic system comprises three Cartesian robots, where robots and the grasped object form a closed-loop kinematic chain. The unknown object is approximated by three virtual links of unknown lengths rigidly attached to one another at the object's center of mass (COM). Due to the unknown COM and unknown inertia of the object, the lengths and inertia of these virtual links are unknown, resulting in kinematic and dynamic uncertainties in the control system. A parameter estimator is proposed to estimate the object's COM to compensate for kinematic uncertainties of the system. Moreover, a new dynamic adaptation law is developed to cope with dynamic uncertainties of the object. The dynamic equations of the cooperative system are transformed from joint space into task space. These task space dynamics are transformed into object space by passively decomposing the dynamics into two decoupled systems, i.e.lockedandshapedsystems. An adaptive controller is developed for the locked system, and the shaped system is controlled by a composite controller based on a PD controller plus a stabilizing damping term. The stability of the proposed controllers is shown using the passivity concept and Lyapunov theorem. Simulation results show that the closed-loop position error asymptotically converges to zero. It is also shown that kinematic and dynamic adaptation parameters converge to real and bounded values respectively.

Effects of visual cues of object density on perception and anticipatory control of dexterous manipulation.

Anticipatory force planning during grasping is based on visual cues about the object’s physical properties and sensorimotor memories of previous actions with grasped objects. Vision can be used to estimate object mass based on the object size to identify and recall sensorimotor memories of previously manipulated objects. It is not known whether subjects can use density cues to identify the object’s center of mass (CM) and create compensatory moments in an anticipatory fashion during initial object lifts to prevent tilt. We asked subjects (n = 8) to estimate CM location of visually symmetric objects of uniform densities (plastic or brass, symmetric CM) and non-uniform densities (mixture of plastic and brass, asymmetric CM). We then asked whether subjects can use density cues to scale fingertip forces when lifting the visually symmetric objects of uniform and non-uniform densities. Subjects were able to accurately estimate an object’s center of mass based on visual density cues. When the mass distribution was uniform, subjects could scale their fingertip forces in an anticipatory fashion based on the estimation. However, despite their ability to explicitly estimate CM location when object density was non-uniform, subjects were unable to scale their fingertip forces to create a compensatory moment and prevent tilt on initial lifts. Hefting object parts in the hand before the experiment did not affect this ability. This suggests a dichotomy between the ability to accurately identify the object’s CM location for objects with non-uniform density cues and the ability to utilize this information to correctly scale their fingertip forces. These results are discussed in the context of possible neural mechanisms underlying sensorimotor integration linking visual cues and anticipatory control of grasping.

Effects of Carpal Tunnel Syndrome on adaptation of multi-digit forces to object mass distribution for whole-hand manipulation

BackgroundCarpal tunnel syndrome (CTS) is a compression neuropathy of the median nerve that results in sensorimotor deficits in the hand. Until recently, the effects of CTS on hand function have been studied using mostly two-digit grip tasks. The purpose of this study was to investigate the coordination of multi-digit forces as a function of object center of mass (CM) during whole-hand grasping.MethodsFourteen CTS patients and age- and gender-matched controls were instructed to grasp, lift, hold, and release a grip device with five digits for seven consecutive lifts while maintaining its vertical orientation. The object CM was changed by adding a mass at different locations at the base of the object. We measured forces and torques exerted by each digit and object kinematics and analyzed modulation of these variables to object CM at object lift onset and during object hold. Our task requires a modulation of digit forces at and after object lift onset to generate a compensatory moment to counteract the external moment caused by the added mass and to minimize object tilt.ResultsWe found that CTS patients learned to generate a compensatory moment and minimized object roll to the same extent as controls. However, controls fully exploited the available degrees of freedom (DoF) in coordinating their multi-digit forces to generate a compensatory moment, i.e., digit normal forces, tangential forces, and the net center of pressure on the finger side of the device at object lift onset and during object hold. In contrast, patients modulated only one of these DoFs (the net center of pressure) to object CM by modulating individual normal forces at object lift onset. During object hold, however, CTS patients were able to modulate digit tangential force distribution to object CM.ConclusionsOur findings suggest that, although CTS did not affect patients’ ability to perform our manipulation task, it interfered with the modulation of specific grasp control variables. This phenomenon might be indicative of a lower degree of flexibility of the sensorimotor system in CTS to adapt to grasp task conditions.

Modeling of 3-D Object Manipulation by Multi-Joint Robot Fingers under Non-Holonomic Constraints and Stable Blind Grasping

This paper derives a mathematical model that expresses motion of a pair of multi-joint robot fingers with hemi-spherical rigid ends grasping and manipulating a 3-D rigid object with parallel flat surfaces. Rolling contacts arising between finger-ends and object surfaces are taken into consideration and modeled as Pfaffian constraints from which constraint forces emerge tangentially to the object surfaces. Another noteworthy difference of modeling of motion of a 3-D object from that of a 2-D object is that the instantaneous axis of rotation of the object is fixed in the 2-D case but that is time-varying in the 3-D case. A further difficulty that has prevented us to model 3-D physical interactions between a pair of fingers and a rigid object lies in the problem of treating spinning motion that may arise around the opposing axis from a contact point between one finger-end with one side of the object to another contact point. This paper shows that, once such spinning motion stops as the object mass center approaches just beneath the opposition axis, then this cease of spinning evokes a further nonholonomic constraint. Hence, the multi-body dynamics of the overall fingers-object system is subject to non-holonomic constraints concerning a 3-D orthogonal matrix expressing three mutually orthogonal unit vectors fixed at the object together with an extra non-holonomic constraint that the instantaneous axis of rotation of the object is always orthogonal to the opposing axis. It is shown that Lagrange's equation of motion of the overall system can be derived without violating the causality that governs the non-holonomic constraints. This immediately suggests possible construction of a numerical simulator of multi-body dynamics that can express motion of the fingers and object physically interactive to each other. By referring to the fact that human grasp an object in the form of precision prehension dynamically and stably by using opposable force between the thumb and another finger (index or middle finger), a simple control signal constructed from finger-thumb opposition and an object-mass estimator is proposed and shown to realize stable grasping in a dynamic sense without using object information or external sensing (this is called “blind grasping”).

Control of multidigit grasping in Parkinson's disease: effect of object property predictability

We examined the extent to which subjects with Parkinson's disease (PD) modulate normal fingertip forces during five-digit grasping based on the object's center of mass (CM). We also tested the effect of trial-to-trial predictability of CM location on the distribution of all fingertip forces relative to thumb force. Ten right-handed subjects with PD (OFF and ON medication) and 10 healthy age-matched control subjects participated. Subjects lifted a manipulandum that measured normal forces exerted by each digit. The CM location was changed from trial-to-trial either in an unpredictable (random) or predictable (blocked) order. Discriminant analysis and information theory were used to quantify the extent to which force-sharing patterns could be discriminated as a function of CM location. All subjects modulated fingertip normal forces as a function of CM location regardless of its predictability, although larger forces were employed when its location was unpredictable. However, in controls, normal force modulation of individual fingers to the object's CM location occurred over a greater range of forces when the CM location was predictable than when it was unpredictable. In contrast, subjects with PD exhibited a similar force modulation to CM location regardless of its predictability. There was a clearer discrimination of force-sharing patterns when the CM location was predictable for controls but not for subjects with PD OFF medication. Medication improved the time course of normal force modulation to CM location. These results indicate that subjects with PD maintained the ability to modulate individual fingertip forces to the object's physical properties. Nevertheless, subjects with PD did not benefit from the a priori knowledge of object CM location to the same extent as controls. These findings support the notion that PD affects the ability to use anticipatory control mechanisms.

Dynamic force/torque balance of 2D polygonal objects by a pair of rolling contacts and sensory‐motor coordination

AbstractIt is well known that three frictionless fingers suffice to immobilize any 2D object with triangular shape but four fingers are necessary for a parallelepiped. However, it has been recently shown that only two fingers are enough to realize secure grasp of a rigid object with parallel flat surfaces in a dynamic sense if finger ends have a hemispherical shape with appropriate radius and thereby rollings are induced between finger ends and object surfaces. This paper focuses on the two problems: (1) dynamic force/torque balance of 2D polygonal objects under the effect of gravity force by means of a pair of rolling contacts and (2) concurrent realization of dynamically secure grasp and orientation control of 2D polygonal objects by using a pair of multi‐fingered hands with hemispherical ends and sensory feedback signals without knowing object kinematics and mass center. It is shown that the force/torque balance can be attained by controlling both the contact positions and inducing adequate forces in both normal and tangential directions at each of contact points indirectly through finger joints without knowing object mass center and other kinematic parameters. © 2003 Wiley Periodicals, Inc.

Dexterous manipulation of an object by means of multi‐DOF robotic fingers with soft tips

AbstractThis article analyzes the dynamics of motion of various setups of two multiple degree‐of‐freedom (DOF) fingers that have soft tips, in fine manipulation of an object, and shows performances of their motions via computer simulation. A mathematical model of these dynamics is described as a system of nonlinear differential equations expressing motion of the overall fingers‐object system together with algebraic constraints due to tight area contacts between the finger‐tips and surfaces of the object. First, problems of (1) dynamic, stable grasping and (2) regulation of the object rotational angle by means of a setup of dual two‐DOF fingers, are treated. Second, the problem of regulating the position of the object mass center by means of a pair of two‐DOF and three‐DOF fingers is considered. Third, a set of dual three‐DOF fingers is treated, in order to let it perform a sophisticated task, which is specified by a periodic pattern of the object posture and a constant internal force. In any case, there exist sensory‐motor coordinations, which are described by analytic feedback connections from sensing to actions at finger joints. In the cases of setpoint control problems, convergences of motion to secure grasping together with the specified object rotational angle and/or the specified object mass center position, are proved theoretically. A constraint stabilization method (CSM) is used for solving numerically the differential algebraic equations to show performances of the proposed sensory‐feedback schemes. © 2002 Wiley Periodicals, Inc.

Force synergies for multifingered grasping: effect of predictability in object center of mass and handedness.

To grasp with five digits of the hand requires an efficient parceling of contact forces in order to maintain static equilibrium as an object is lifted and held. In a previous study, subjects were asked to reach, grasp and lift a five-digit grip apparatus whose center of mass (CM) location was changed for each block of trials. Despite a modulation of force sharing patterns among the digits as a function of center of mass location, consistent in-phase and out-of-phase relationships between normal forces were found in the frequency domain. In the present study, we have used the same task to assess the effect of (a) predictability of an object's CM location (random vs blocked presentation) and (b) handedness (dominant vs non-dominant hand). Contrary to our original expectations, we found a similar modulation of normal forces to CM location during the hold phase across all conditions. Specifically, the force sharing pattern, i.e., the rank order of force contributed by each digit, emerged very early in the grasp sequence, remaining relatively stable throughout the duration of the lift and hold. Nevertheless, the extent to which force sharing patterns could be discriminated as a function of CM location was lower in the random than in the blocked conditions. Lastly, normal forces exerted by pairs of digits tended to be synchronized, both in-phase (thumb and fingers) and out-of-phase (pairs of digits) across a large proportion of the functional frequency range (up to 10 Hz) in all conditions. The composite of these findings suggests that the central nervous system uses stereotyped control strategies for coordinating multiple grip forces during grasping. Specific aspects of these schemes appear to be affected by predictability of object CM location, but not by hand dominance.

Specificity of Internal Representations Underlying Grasping

The present study examines anticipatory control of fingertip forces during grasping based on the center of mass (CM) of a manipulated object. Subjects lifted an object using a precision grip while the fingertip forces and the angle about the vertical axis (roll) were measured. The object's CM could be shifted to the left or right of the object's center parallel to the grip axis without changing it's visual appearance. Subjects performed 20 lifts with the CM in the center, left, and right side of the object, respectively. Subjects were instructed to lift the object while preventing it from tilting. Within three to five lifts, subjects were able to asymmetrically partition the load force development before lift-off such that it was higher in the digit opposing the CM. This anticipatory load force partitioning prevented the object from rolling sideways at lift-off. To determine whether the internal representation underlying the anticipatory control is specific to the effectors used to form it, subjects performed five lifts with the right hand with the CM on one side. Following these lifts, they rotated the object 180 degrees around the vertical axis and performed one lift with the same hand or they translated the object to the left side of the body (with or without rotating it) and performed one lift with the left hand. Despite subjects' explicit knowledge of the new weight distribution, they were unable to appropriately scale the load forces at each digit, resulting in a subsequent large roll of the object. The findings suggest that within a few lifts subjects achieve a stable internal representation which accounts for the object's CM and is used to scale the fingertip forces in advance. They also suggest that this representation, which is used for anticipatory control of fingertip forces, is specific to the effectors used to form it. We propose that multiple internal representations may be used during the anticipatory control of grasping.

Anticipating load torques produced by voluntary movements.

The stability of an object held between the finger and thumb depends on friction developed by grip force, normal to the contact surfaces, to overcome tangential load force. Previous research has shown that in lifting an object, grip force rises with the increase in gravitational load force as the hand takes the weight and that in moving an object, grip force is adjusted to meet movement-induced inertial load force. Those results demonstrated the anticipatory nature of coordination of grip force with load force. Whether grip force anticipates load torque was studied in this research. When participants were constrained to use grasp points where the grasp axis was manifestly distant from object center of mass, it was found that they made grip force adjustments in anticipation of load torques that tended to destabilize an object as a result of lifting or moving it. These adjustments imply use of information about object center of mass in movement planning.