Joint Impedance Research Articles

Modeling processed seismic data to improve seismic facies prediction

Interpreters need to screen and select the most geologically robust inversion products from increasingly larger data volumes, particularly in the absence of significant well control. Seismic processing and inversion routines are devised to provide reliable elastic parameters ([Formula: see text] and [Formula: see text]) from which the interpreter can predict the fluid and lithology properties. Seismic data modeling, for example, the Shuey approximations and the convolution inversion models, greatly assist in the parameterization of the processing flows within acceptable uncertainty limits and in establishing a measure of the reliability of the processing. Joint impedance facies inversion (Ji-Fi®) is a new inversion methodology that jointly inverts for acoustic impedance and seismic facies. Seismic facies are separately defined in elastic space ([Formula: see text] and [Formula: see text]), and a dedicated low-frequency model per facies is used. Because Ji-Fi does not need well data from within the area to define the facies or depth trends, wells from outside the area or theoretical constraints may be used. More accurate analyses of the reliability of the inversion products are a key advance because the results of the Ji-Fi lithology prediction may then be quantitatively and independently assessed at well locations. We used a novel visual representation of a confusion matrix to quantitatively assess the sensitivity and uncertainty in the results when compared with facies predicted from the depth trends and well-elastic parameters and the well-log lithologies observed. Thus, using simple models and the Ji-Fi inversion technique, we had an improved, quantified understanding of our data, the processes that had been applied, the parameterization, and the inversion results. Rock physics could further transform the elastic properties to more reservoir-focused parameters: volume of shale and porosity, volumes of facies, reservoir property uncertainties — all information required for interpretation and reservoir modeling.

Toward Balance Recovery With Leg Prostheses Using Neuromuscular Model Control.

Lower limb amputees are at high risk of falling as current prosthetic legs provide only limited functionality for recovering balance after unexpected disturbances. For instance, the most established control method used on powered leg prostheses tracks local joint impedance functions without taking the global function of the leg in balance recovery into account. Here, we explore an alternative control policy for powered transfemoral prostheses that considers the global leg function and is based on a neuromuscular model of human locomotion. We adapt this model to describe and simulate an amputee walking with a powered prosthesis using the proposed control, and evaluate the gait robustness when confronted with rough ground and swing leg disturbances. We then implement and partially evaluate the resulting controller on a leg prosthesis prototype worn by a nonamputee user. In simulation, the proposed prosthesis control leads to gaits that are more robust than those obtained by the impedance control method. The initial hardware experiments with the prosthesis prototype show that the proposed control reproduces normal walking patterns qualitatively and effectively responds to disturbances in early and late swing. However, the response to midswing disturbances neither replicates human responses nor averts falls. The neuromuscular model control is a promising alternative to existing prosthesis controls, although further research will need to improve on the initial implementation and determine how well these results transfer to amputee gait. This paper provides a potential avenue for future development of control policies that help to improve amputee balance recovery.

Intermittent control of unstable multivariate systems.

A sensorimotor architecture inspired from biological, vertebrate control should (i) explain the interface between high dimensional sensory analysis, low dimensional goals and high dimensional motor mechanisms and (ii) provide both stability and flexibility. Our interest concerns whether single-input-single-output intermittent control (SISO_IC) generalized to multivariable intermittent control (MIC) can meet these requirements.We base MIC on the continuous-time observer-predictorstate-feedback architecture. MIC uses event detection. A system matched hold (SMH), using the underlying continuoustime optimal control design, generates multivariate open-loop control signals between samples of the predicted state. Combined, this serial process provides a single-channel of control with optimised sensor fusion and motor synergies. Quadratic programming provides constrained, optimised equilibrium control design to handle unphysical configurations, redundancy and provides minimum, necessary reduction of open loop instability through optimised joint impedance. In this multivariate form, dimensionality is linked to goals rather than neuromuscular or sensory degrees of freedom. The biological and engineering rationale for intermittent rather than continuous multivariate control, is that the generalised hold sustains open loop predictive control while the open loop interval provides time within the feedback loop for online centralised, state dependent optimisation and selection.

Towards versatile legged robots through active impedance control

Robots with legs and arms have the potential to support humans in dangerous, dull or dirty tasks. A major motivation behind research on such robots is their potential versatility. However, these robots come at a high price in mechanical and control complexity. Hence, until they can demonstrate a clear advantage over their simpler counterparts, robots with arms and legs will not fulfill their true potential. In this paper, we discuss the opportunities for versatile robots that arise by actively controlling the mechanical impedance of joints and particularly legs. In contrast to passive elements such as springs, active impedance is achieved by torque-controlled joints allowing real-time adjustment of stiffness and damping. Adjustable stiffness and damping in real-time is a fundamental building block towards versatility. Experiments with our 80 kg hydraulic quadruped robot HyQ demonstrate that active impedance alone (i.e. no springs in the structure) can successfully emulate passively compliant elements during highly dynamic locomotion tasks (running, jumping and hopping); and that no springs are needed to protect the actuation system. Here we present results of a flying trot, also referred to as a running trot. To the best of the authors’ knowledge this is the first time a flying trot has been successfully implemented on a robot without passive elements such as springs. A critical discussion on the pros and cons of active impedance concludes the paper. This article is an extension of our previous work presented at the International Symposium on Robotics Research (ISRR) 2013.

1P2-B03 ヒューマノイドロボットの重心インピーダンス行列

This paper proposes a novel concept called COG impedance matrix of a humanoid robot, which provides an explicit relationship with the joint impedance or joint PD controller. Using the COG impedance matrix, we can calculate the macroscopic feedback gain which approximates the joint impedance, and compute the maximal output admissible (MOA) set for falling detection. First-lag-order COP dynamics is also proposed to compensate the nonlinearity in the whole body dynamics.

An intermittent control model of flexible human gait using a stable manifold of saddle-type unstable limit cycle dynamics.

Stability of human gait is the ability to maintain upright posture during walking against external perturbations. It is a complex process determined by a number of cross-related factors, including gait trajectory, joint impedance and neural control strategies. Here, we consider a control strategy that can achieve stable steady-state periodic gait while maintaining joint flexibility with the lowest possible joint impedance. To this end, we carried out a simulation study of a heel-toe footed biped model with hip, knee and ankle joints and a heavy head-arms-trunk element, working in the sagittal plane. For simplicity, the model assumes a periodic desired joint angle trajectory and joint torques generated by a set of feed-forward and proportional-derivative feedback controllers, whereby the joint impedance is parametrized by the feedback gains. We could show that a desired steady-state gait accompanied by the desired joint angle trajectory can be established as a stable limit cycle (LC) for the feedback controller with an appropriate set of large feedback gains. Moreover, as the feedback gains are decreased for lowering the joint stiffness, stability of the LC is lost only in a few dimensions, while leaving the remaining large number of dimensions quite stable: this means that the LC becomes saddle-type, with a low-dimensional unstable manifold and a high-dimensional stable manifold. Remarkably, the unstable manifold remains of low dimensionality even when the feedback gains are decreased far below the instability point. We then developed an intermittent neural feedback controller that is activated only for short periods of time at an optimal phase of each gait stride. We characterized the robustness of this design by showing that it can better stabilize the unstable LC with small feedback gains, leading to a flexible gait, and in particular we demonstrated that such an intermittent controller performs better if it drives the state point to the stable manifold, rather than directly to the LC. The proposed intermittent control strategy might have a high affinity for the inverted pendulum analogy of biped gait, providing a dynamic view of how the step-to-step transition from one pendular stance to the next can be achieved stably in a robust manner by a well-timed neural intervention that exploits the stable modes embedded in the unstable dynamics.

Coordination of intrinsic and extrinsic foot muscles during walking.

The human foot undergoes complex deformations during walking due to passive tissues and active muscles. However, based on prior recordings it is unclear if muscles that contribute to flexion/extension of the metatarsophalangeal (MTP) joints are activated synchronously to modulate joint impedance, or sequentially to perform distinct biomechanical functions. We investigated the coordination of MTP flexors and extensors with respect to each other, and to other ankle-foot muscles. We analyzed surface electromyographic (EMG) recordings of intrinsic and extrinsic foot muscles for healthy individuals during level treadmill walking, and also during sideways and tiptoe gaits. We computed stride-averaged EMG envelopes and used the timing of peak muscle activity to assess synchronous vs. sequential coordination. We found that peak MTP flexor activity occurred significantly before peak MTP extensor activity during walking (P < 0.001). The period around stance-to-swing transition could be roughly characterized by sequential peak muscle activity from the ankle plantarflexors, MTP flexors, MTP extensors, and then ankle dorsiflexors. We found that foot muscles that activated synchronously during forward walking tended to dissociate during other locomotor tasks. For instance, extensor hallucis brevis and extensor digitorum brevis muscle activation peaks decoupled during sideways gait. The sequential peak activity of MTP flexors followed by MTP extensors suggests that their biomechanical contributions may be largely separable from each other and from other extrinsic foot muscles during walking. Meanwhile, the task-specific coordination of the foot muscles during other modes of locomotion indicates a high-level of specificity in their function and control.

Joint Impedance and Facies Inversion – Seismic inversion redefined

In this paper we will first review the industry-standard simultaneous inversion method (which derives continuous impedances) and subsequently identify some pitfalls. We will then introduce our new Joint Impedance and Facies Inversion technology (which we call Ji-Fi for short in this paper), which overcomes these pitfalls by recasting the seismic inverse problem as mixed discrete/continuous. Having so captured the correct physics, we apply this first on a wedge model, followed by a case study, before drawing some conclusions. Note that in this paper, it is assumed that the seismic to be inverted is an ensemble of true amplitude partial angle stacks with corresponding wavelets derived from well ties.

Development and experimental evaluation of multi-fingered robot hand with adaptive impedance control for unknown environment grasping

SUMMARYThis paper presents adaptive impedance controllers with adaptive sliding mode friction compensation for anthropomorphic artificial hand. A five-fingered anthropomorphic artificial hand with multi-sensory and Field-Programmable Gate Arra (FPGA)-based control hardware and software architecture is designed to fulfill the requirements of the grasping force controller. In order to improve the force-tracking precision, the indirect adaptive algorithm was applied to estimate the parameters of the environment. The generalized momentum-based disturbance observer was applied to estimate the contact force from the torque sensor. Based on the sensors of the finger, an adaptive sliding mode friction compensation algorithm was utilized to improve the accuracy of the position control. The performances of the force-tracking impedance controller and position-based joint impedance control for the five-fingered anthropomorphic artificial hand are analyzed and compared in this paper. Furthermore, the performances of the force-tracking impedance controller with environmental parameters adaptive estimation and without environmental parameters estimation are analyzed and compared. Experimental results prove that accurate force-tracking and stable torque/force response under uncertain environments of unknown stiffness and position can be achieved with the proposed adaptive force-tracking impedance controller with friction compensation on five-finger artificial hand.

Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks.

This paper investigates optimal feet forces' distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamics of quadruped robots and derive a reduced-order dynamical model of motion/force. Consider an external wrench on quadruped robots; the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to deal with the optimized objective function formulated as to minimize this quadratic objective function subjected to linear equality and inequality constraints. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on an adaptive neural network to compensate for the perturbations in the environment and approximate feedforward force and impedance of the leg joints. The proposed control can confront the uncertainties including approximation error and external perturbation. The verification of the proposed control is conducted using a simulation.

Estimation of intrinsic joint impedance using quasi-static passive and dynamic methods in individuals with and without Cerebral Palsy.

Modeling the passive behavior of the knee in subjects with spasticity involves the applied external torques (e.g. gravitational torque), the intrinsic moments due to tissue properties, as well as active, neurally defined moments resulting from the hypersensitivity of reflexes introduced by disability. In order to provide estimates of the necessary intrinsic terms in the equation of motion, the push-pull and Wartenberg Pendulum Knee Drop (PKD) tests were administered. Four subjects without disability and two subjects with Cerebral Palsy (CP) were evaluated for their active and intrinsic knee stiffness parameters. Separation of these two terms requires an additional stiffness term be added to the traditional equation of motion. This holds true for subjects with and without neurological disability. Very interestingly, the optimized non-disabled PKD produced lumped stiffness (K) that is similar to the push-pull passive stiffness (KI) for both populations. On the other hand the optimized K value in the PKD test for subjects with disability was approximately 19 times larger than the KI value found graphically from the push-pull test. This leads us to the conclusion that we can partition our lumped K as the sum of a neurally generated stiffness (Ka) and KI to complete the trajectory model. Therefore, this study shows that spasticity is a velocity dependent, that would not appear in disabled individuals unless the examined limb has a non-zero velocity.

Contributions of knee swing initiation and ankle plantar flexion to the walking mechanics of amputees using a powered prosthesis.

Recently developed powered prostheses are capable of producing near-physiological joint torque at the knee and/or ankle joints. Based on previous studies of biological joint impedance and the mechanics of able-bodied gait, an impedance-based controller has been developed for a powered knee and ankle prosthesis that integrates knee swing initiation and powered plantar flexion in late stance with increasing ankle stiffness throughout stance. In this study, five prosthesis configuration conditions were tested to investigate the individual contributions of each sub-strategy to the overall walking mechanics of four unilateral transfemoral amputees as they completed a clinical 10-m walk test using a powered knee and ankle prosthesis. The baseline condition featured constant ankle stiffness and no swing initiation or powered plantar flexion. The four remaining conditions featured knee swing initiation alone (SI) or in combination with powered plantar flexion (SI+PF), increasing ankle stiffness (SI+IK), or both (SI+PF+IK). Self-selected walking speed did not significantly change between conditions, although subjects tended to walk the slowest in the baseline condition compared to conditions with swing initiation. The addition of powered plantar flexion resulted in significantly higher ankle power generation in late stance irrespective of ankle stiffness. The inclusion of swing initiation resulted in a significantly more flexed knee at toe off and a significantly higher average extensor knee torque following toe off. Identifying individual contributions of intrinsic control strategies to prosthesis biomechanics could help inform the refinement of impedance-based prosthesis controllers and simplify future designs of prostheses and lower-limb assistive devices alike.

Estimation of Human Ankle Impedance During the Stance Phase of Walking

Human joint impedance is the dynamic relationship between the differential change in the position of a perturbed joint and the corresponding response torque; it is a fundamental property that governs how humans interact with their environments. It is critical to characterize ankle impedance during the stance phase of walking to elucidate how ankle impedance is regulated during locomotion, as well as provide the foundation for future development of natural, biomimetic powered prostheses and their control systems. In this study, ankle impedance was estimated using a model consisting of stiffness, damping and inertia. Ankle torque was well described by the model, accounting for 98 ±1.2% of the variance. When averaged across subjects, the stiffness component of impedance was found to increase linearly from 1.5 to 6.5 Nm/rad/kg between 20% and 70% of stance phase. The damping component was found to be statistically greater than zero only for the estimate at 70% of stance phase, with a value of 0.03 Nms/rad/kg. The slope of the ankle's torque-angle curve-known as the quasi-stiffness-was not statistically different from the ankle stiffness values, and showed remarkable similarity. Finally, using the estimated impedance, the specifications for a biomimetic powered ankle prosthesis were introduced that would accurately emulate human ankle impedance during locomotion.

Multi-fingered Coordinated Control for Dexterous Robotic Hand

Based on the force-closure and force-balance conditions, the grasping force optimization of precision grasp can be converted to a nonlinear programming problem. In order to solve the nonlinear programming, complex procedure is usually needed for the traditional methods. So a method implemented by the fmincon function based on sequential quadratic programming in Matlab optimization tool box is proposed. For power grasp, a simple but autonomous method is proposed. The joint impedance force control algorithm is adopted to limit the contact force to the maximum in the method. In order to validate the proposed methods, the simulation system of multi-fingered coordinated control is built in Simulink environment. The system is based on the control module generated in ADAMS software. The simulation results demonstrate that the target object can be stably grasped by the dexterous robotic hand whether the tasks are precision grasp or power grasp.

EXPERIMENTAL ANALYSIS ON SPATIAL AND CARTESIAN IMPEDANCE CONTROL FOR THE DEXTEROUS DLR/HIT II HAND

This paper presents an experimental study on impedance control in both Cartesian and object level with adaptive friction compensation for dexterous robot hand based on joint torque feedback. To adaptively decrease the effects of high friction caused by complex transmission systems and joint coupling, a friction observer is proposed based on the extended Kalman filter (EKF) in this paper. A Cartesian impedance controller is implemented on a multi-fingered dexterous robot hand with identical fingers, based on the modelling of each modular finger. In addition, a flexible n-fingered object frame is proposed in this paper, applicable to any finger configuration with three or more fingers (n ≥ 3). This enables the design of a 6-DoF spatial impedance controller. Stability of the closedloop system with friction observer is analysed. A position error of less than 0.16 ◦ is achieved using joint impedance control with adaptive friction compensation, which shows significant improvement in performance, as compared to 1.5 ◦ without compensation, and 0.5 ◦ with fixed-parameters friction compensation. Experimental results confirm the improvement in performance for the robot hand with Cartesian impedance control and adaptive joint friction compensation, demonstrating the effectiveness of spatial impedance controller with the proposed object frame and estimation strategy.

Perturbation Amplitude Affects Linearly Estimated Neuromechanical Wrist Joint Properties

System identification techniques have been used to separate intrinsic muscular and reflexive contributions to joint impedance, which is an essential step in the proper choice of patient specific treatment. These techniques are, however, only well developed for linear systems. Assuming linearity prescribes the neuromuscular system to be perturbed only around predefined operating points. In this study, we test the validity of a commonly used linear model by analyzing the effects of flexion-extension displacement amplitude (2(°), 4(°), and 8(°)) on damping, stiffness, and reflex gain of the wrist joint, at different background torque levels (0, 1, and 2 N · m). With displacement amplitude, intrinsic damping increased, while intrinsic stiffness and reflex gains decreased. These changes were dependent on the level of wrist torque. The dependency of the neuromuscular system properties on even small variations in angular displacement is evident and has to be accounted for when comparing different studies and clinical interpretations using linear identification techniques. Knowledge of the behavior of the neuromuscular system around operating points is an essential step toward the development of nonlinear models that allow for discrimination between patients and controls in a larger range of loading conditions.

Development of a Mechatronic Platform and Validation of Methods for Estimating Ankle Stiffness During the Stance Phase of Walking

The mechanical properties of human joints (i.e., impedance) are constantly modulated to precisely govern human interaction with the environment. The estimation of these properties requires the displacement of the joint from its intended motion and a subsequent analysis to determine the relationship between the imposed perturbation and the resultant joint torque. There has been much investigation into the estimation of upper-extremity joint impedance during dynamic activities, yet the estimation of ankle impedance during walking has remained a challenge. This estimation is important for understanding how the mechanical properties of the human ankle are modulated during locomotion, and how those properties can be replicated in artificial prostheses designed to restore natural movement control. Here, we introduce a mechatronic platform designed to address the challenge of estimating the stiffness component of ankle impedance during walking, where stiffness denotes the static component of impedance. The system consists of a single degree of freedom mechatronic platform that is capable of perturbing the ankle during the stance phase of walking and measuring the response torque. Additionally, we estimate the platform's intrinsic inertial impedance using parallel linear filters and present a set of methods for estimating the impedance of the ankle from walking data. The methods were validated by comparing the experimentally determined estimates for the stiffness of a prosthetic foot to those measured from an independent testing machine. The parallel filters accurately estimated the mechatronic platform's inertial impedance, accounting for 96% of the variance, when averaged across channels and trials. Furthermore, our measurement system was found to yield reliable estimates of stiffness, which had an average error of only 5.4% (standard deviation: 0.7%) when measured at three time points within the stance phase of locomotion, and compared to the independently determined stiffness values of the prosthetic foot. The mechatronic system and methods proposed in this study are capable of accurately estimating ankle stiffness during the foot-flat region of stance phase. Future work will focus on the implementation of this validated system in estimating human ankle impedance during the stance phase of walking.

Dynamical Balance Optimization and Control of Quadruped Robots Under Perturbing External Force

This paper investigates the optimal feet forces distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamic model of quadruped robots and derive a reduced order dynamical model of motion/force. Consider an external wrench on quadruped robots, the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to minimize the optimized objective function with linear equality and inequality constraints, and hybrid motion/force control based on adaptive neural network is used to compensate for the external perturbation in the environment and approximate feedforward force and impedance of the leg joints on line. The verification of the proposed control is conducted using the extensive simulations.

Transient Thermal Impedance Measurements on Low-Temperature-Sintered Nanoscale Silver Joints

A measurement system for thermal impedance (Zth) was developed to evaluate the transient thermal performance of sintered nanoscale silver joints. Five different temperature profiles for low-temperature sintering were evaluated by Zth measurements of the joints. The thermal impedance of the sintered samples was altered by the different sintering conditions. Samples that underwent heating profiles with a separate drying stage offered lower thermal impedance than those sintered directly. Exerting pressure of more than 1 MPa during sintering insignificantly improved the thermal impedance. Besides, the impedance could be lowered by extending the holding time of the drying stage and applying pressure as low as 1 MPa during sintering. Characterization of microstructures of the sintered layers was performed by scanning electron microscopy (SEM). With more cracks present, the thermal impedance of the chip joints increased. The presence of cracks was possibly attributed to fast drying or the lack of a drying step.

Estimates of Acausal Joint Impedance Models

Estimates of joint or limb impedance are commonly used in the study of how the nervous system controls posture and movement, and how that control is altered by injury to the neural or musculoskeletal systems. Impedance characterizes the dynamic relationship between an imposed perturbation of joint position and the torques generated in response. While there are many practical reasons for estimating impedance rather than its inverse, admittance, it is an acausal representation of the limb mechanics that can lead to difficulties in interpretation or use. The purpose of this study was to explore the acausal nature of nonparametric estimates of joint impedance representations to determine how they are influenced by common experimental and computational choices. This was accomplished by deriving discrete-time realizations of first- and second-order derivatives to illustrate two key difficulties in the physical interpretation of impedance impulse response functions. These illustrations were provided using both simulated and experimental data. It was found that the shape of the impedance impulse response depends critically on the selected sampling rate, and on the bandwidth and noise characteristics of the position perturbation used during the estimation process. These results provide important guidelines for designing experiments in which nonparametric estimates of impedance will be obtained, especially when those estimates are to be used in a multistep identification process.