Kinematic Level Research Articles

Estimation of skeletal kinematics in freely moving rodents

Forming a complete picture of the relationship between neural activity and skeletal kinematics requires quantification of skeletal joint biomechanics during free behavior; however, without detailed knowledge of the underlying skeletal motion, inferring limb kinematics using surface-tracking approaches is difficult, especially for animals where the relationship between the surface and underlying skeleton changes during motion. Here we developed a videography-based method enabling detailed three-dimensional kinematic quantification of an anatomically defined skeleton in untethered freely behaving rats and mice. This skeleton-based model was constrained using anatomical principles and joint motion limits and provided skeletal pose estimates for a range of body sizes, even when limbs were occluded. Model-inferred limb positions and joint kinematics during gait and gap-crossing behaviors were verified by direct measurement of either limb placement or limb kinematics using inertial measurement units. Together we show that complex decision-making behaviors can be accurately reconstructed at the level of skeletal kinematics using our anatomically constrained model.

Dual-User Haptic Teleoperation of Complementary Motions of a Redundant Wheeled Mobile Manipulator Considering Task Priority

With the increasing applications of wheeled mobile manipulators (WMMs), consisting of a mobile platform (MP) and a manipulator, in diverse fields, new challenges have arisen in achieving multiple tasks such as obstacle avoidance in a constrained environment during the end-effector (EE) operation. A WMM is usually redundant due to the combination of the MP and the manipulator, making multitask control possible via employing its null space. Dual-user/two-handed teleoperation of a WMM is desirable for tasks where it is important to simultaneously control the poses of both the MP and the EE. The existing teleoperation approaches for WMMs are mostly executed at the kinematic level, without considering the nonlinear rigid-body dynamics of the WMMs. In this article, a task-priority-based dual-user teleoperation framework for a WMM is implemented to perform tasks in a constrained environment. It can simultaneously manipulate the MP and the EE, the overground obstacles are avoided by telecontrolling the MP using the WMM’s null space. Any residual redundancy can be further employed for other tasks such as singularity avoidance. The stability of the entire teleoperation design is rigorously proved even with arbitrary time delays. Experiments with a dual-user teleoperation system, consisting of two local robots and an omnidirectional WMM, are conducted to verify the proposed approach’s feasibility and effectiveness.

Simultaneous Calibration of Multiple Revolute Joints for Articulated Vision Systems via SE(3) Kinematic Bundle Adjustment

We propose a vision-based approach to calibrate kinematic structure of low degree-of-freedom (DoF) articulated systems. Standard hand-eye calibration yields excellent eye-to-hand relations by explicitly estimating end-effector mounted camera poses from the Perspective-n-Point (PnP) problem of a single calibration rig. However, these methods struggle when the ideal kinematic model is unknown or inaccurate, which are typical in customized serial chains such as articulated vision systems. Inspired by bundle adjustment in structure-from-motion methods, we proposed an approach, dubbed KBA, to simultaneously localize multiple joint axes at the kinematic level instead of in the 3D space. To achieve this, we design a robust multi-checkerboard detector to enlarge the kinematic coverage of end-effector samples, which are usually limited by sensor field of view. The overall optimization problem is formulated and solved using Lie group SE(3)—suitable for integration into simultaneous localization and mapping systems. In addition to simulated scenes, the experimental results with articulated monocular (AMV) and binocular vision (ABV) confirm that the proposed method not only is applicable to real serial kinematic chains but also enables challenging 3D vision tasks such as stereo reconstruction in motion.

Distributed Cooperative Surrounding Control for Mobile Robots With Uncertainties and Aperiodic Sampling

In this paper, we present a distributed cooperative surrounding control for mobile robots with uncertainties and aperiodic sampling. At the kinematic level, a cooperative circumnavigation guidance law with the capability of spatial-temporal decoupling, employing a line-of-sight (LOS) principle to accomplish closed orbit following and a path parameter synchronization to assign the desired speed, is devised to generate reference velocity and angular rate. At the kinetic level, to reduce the transmission burden in sensor-to-controller channel and compensate for the total uncertainties existing in velocity channels, aperiodic sampling based extended state observers (AS-ESOs), are developed to provide precise disturbance estimates with guaranteed convergence, while a nonnegative threshold-based event-triggering condition with a straightforward tuning procedure is designed to schedule the communication frequency without inducing Zeno behaviors. Then a robust anti-disturbance kinetic control protocol is synthesized that renders an equiangular distribution along the common circle. The salient merit is that a symmetric formation pattern over a closed curve defined by parameterized path, instead of time-related functions, can be obtained in a distributed manner with decreased sampling cost and disturbances. Moreover, all error variables in the closed-loop system are demonstrated to be bounded. Finally, the effectiveness of algorithm is verified by simulations.

Network-Based Line-of-Sight Path Tracking of Underactuated Unmanned Surface Vehicles With Experiment Results.

This article deals with the problem of network-based path-tracking control of an underactuated unmanned surface vehicle subject to model uncertainties and unknown disturbances over a wireless network. A two-level network-based control architecture is proposed, including a local inner loop and a remote outer loop. In the remote outer loop, an event-triggered line-of-sight guidance law is designed to achieve path tracking while reducing the network burden for the remote control at the kinematic level. In the local inner loop, an extended state observer is employed to estimate the unknown disturbances due to the model uncertainties and environmental disturbances. Based on the estimated information from the extended state observer, an event-triggered anti-disturbance control law is developed to reduce the execution rate of actuators at the kinetic level. The stability of the closed-loop path-tracking system is proved based on the input-to-state stability and cascade stability theory. The effectiveness of the proposed network-based method for path tracking of the USV is verified via experiments.

Distributed model-free formation control of networked fully-actuated autonomous surface vehicles.

This paper presents a distributed constant bearing guidance and model-free disturbance rejection control method for formation tracking of autonomous surface vehicles subject to fully unknown kinetic model. First, a distributed constant bearing guidance law is designed at the kinematic level to achieve a consensus task. Then, by using an adaptive extended state observer (AESO) to estimate the total uncertainties and unknown input coefficients, a simplified model-free kinetic controller is designed based on a dynamic surface control (DSC) design. It is proven that the closed-loop system is input-to-state stable The stability of the closed-loop system is established. A salient feature of the proposed method is that a cooperative behavior can be achieved without knowing any priori information. An application to formation control of autonomous surface vehicles is given to show the efficacy of the proposed integrated distributed constant bearing guidance and model-free disturbance rejection control.

Neuro-adaptive distributed formation tracking control of under-actuated unmanned surface vehicles with input quantization

This paper addresses distributed formation control of multiple under-actuated unmanned surface vehicles (USVs) subject to input quantization, in addition to the unknown dynamics caused by external sea disturbances and internal model uncertainties. A two-level distributed guidance and neuro-adaptive quantized control architecture is presented to achieve a time-varying formation regardless of the input quantization. Specifically, at the kinematic level, an extended state observer (ESO)-based distributed guidance law is developed to track a time-varying trajectory where the ESO is adopted to estimate the unavailable linear velocity and rate of turn (ROT) of neighboring USVs. At the dynamic level, by using a linear time-varying model to deal with the difficulty caused by quantization and the radial basis function neural networks (RBFNNs) to identify the unknown dynamics, a neuro-adaptive quantized control law is developed where no information on the parameters of quantizers is required. The stability of the proposed two-level formation control architecture is proven on the basis of input-to-state stability, and all signals in the closed-loop system are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the proposed neuro-adaptive quantized control method for USVs.

Toward a unifying framework for the modeling and identification of motor primitives.

A large body of evidence suggests that human and animal movements, despite their apparent complexity and flexibility, are remarkably structured. Quantitative analyses of various classes of motor behaviors consistently identify spatial and temporal features that are invariant across movements. Such invariant features have been observed at different levels of organization in the motor system, including the electromyographic, kinematic, and kinetic levels, and are thought to reflect fixed modules—named motor primitives—that the brain uses to simplify the construction of movement. However, motor primitives across space, time, and organization levels are often described with ad-hoc mathematical models that tend to be domain-specific. This, in turn, generates the need to use model-specific algorithms for the identification of both the motor primitives and additional model parameters. The lack of a comprehensive framework complicates the comparison and interpretation of the results obtained across different domains and studies. In this work, we take the first steps toward addressing these issues, by introducing a unifying framework for the modeling and identification of qualitatively different classes of motor primitives. Specifically, we show that a single model, the anechoic mixture model, subsumes many popular classes of motor primitive models. Moreover, we exploit the flexibility of the anechoic mixture model to develop a new class of identification algorithms based on the Fourier-based Anechoic Demixing Algorithm (FADA). We validate our framework by identifying eight qualitatively different classes of motor primitives from both simulated and experimental data. We show that, compared to established model-specific algorithms for the identification of motor primitives, our flexible framework reaches overall comparable and sometimes superior reconstruction performance. The identification framework is publicly released as a MATLAB toolbox (FADA-T, https://tinyurl.com/compsens) to facilitate the identification and comparison of different motor primitive models.

Loco-Manipulation Control for Arm-Mounted Quadruped Robots: Dynamic and Kinematic Strategies

The studies on quadruped robots equipped with arms are still rare at the moment. The interaction between the arm and the quadrupedal platform needs to be handled by whole-body controllers. This paper presents an optimization-based dynamic whole-body controller to solve the problem of when the robot stands still for manipulation. In order to reduce the strong interaction when the robot is trotting, we keep using the whole-body controller to handle locomotion control and resort to joint PD controllers for the arm’s manipulation coupled with the mobile base on the kinematic level. Simulation results validate the expected locomotion and manipulation functionalities in both manipulation mode and loco-manipulation mode. The proposed control strategies are able to use the redundancy to perform multiple tasks in a dynamic system as such with 24 degrees of freedom.

Motion planning of a free-flying space robot system under end effector task constraints

This study focuses on the motion planning of a free-flying space robot system with non-conserved linear and angular momentums due to thrusts acting on its base. The system model is established at the kinematic level based on the momentum theorem, which takes into account the change in base mass. In particular, a motion planning strategy is proposed to perform trajectory tracking of the end effector for the free-flying space robot. The thrusts and torque acting on base satellite are not predefined, but are taken as system control inputs to be optimized, as are joint accelerations. Therefore, the synchronous motion planning of the base satellite and manipulator is formulated as an open-loop optimization problem, which is subject to physical constraints such as thrust and torque saturation, joint motion limitations, and collision avoidance, etc. Finally, the system under different task constraints of end effectors is numerically simulated to demonstrate the effectiveness of the proposed method.

Safe cooperative path following with relative-angle-based collision avoidance for multiple underactuated autonomous surface vehicles

This paper addresses the safe cooperative path following for multiple autonomous surface vehicles (ASVs) in the presence of static and dynamic obstacles. The positions and velocities of the obstacles are unknown, and only the relative angle is measured. The ASVs are subject to uncertain kinetics and unknown disturbances induced by wind, waves and currents. Switching cooperative guidance laws with collision avoidance are designed at the kinematic level, and a collision avoidance strategy based on the relative angle is introduced into the desired yaw rate design. A smooth switch between the cooperative path following and the collision avoidance is achieved by using an exponential-function-based weighted coefficient. At the kinetic level, nonlinear switching extended state observers (NSESOs) based on fractional power functions are developed to estimate the model uncertainties and environmental disturbances. Anti-disturbance kinetic control laws are designed based on the nonlinear switching extended state observers and finite-time convergent differentiators. A salient feature of the proposed cooperative path following method is that both the static and dynamic obstacles can be avoided by using the relative angle only. Through theoretical analysis, it is proven that the closed-loop system is input-to-state stable, and a safe distance can be maintained between the ASVs and the obstacles. Simulation and hardware-in-loop (HIL) experiment results are given to substantiate the effectiveness of the proposed safe cooperative path following control method for multiple ASVs based on relative angles.

Safety-Critical Model-Free Control for Multi-Target Tracking of USVs with Collision Avoidance

Dear editor, This letter addresses the multi-target tracking of underactuated unmanned surface vehicles (USVs) subject to multiple stationary/moving obstacles. The kinetic model parameters of each USV are totally unknown. A safety-critical model-free control method is proposed for tracking multiple targets with a collision-free containment formation. Specifically, a distributed containment extended state observer (DCESO) is designed to estimate the convex hull spanned by the multiple targets. At the kinematic level, a collision-free kinematic guidance law is presented using a control barrier function (CBF) and an extended state observer for each follower USV. At the kinetic level, a model-free position tracking control law by using an adaptive ESO (AESO) is presented for each follower USV. By the designed safety-critical model-free control method, cooperative tracking of multiple targets under multiple stationary/moving obstacles can be achieved using completely unknown kinetic model parameters. Simulations are provided to illustrate the efficacy of the proposed safety-critical model-free control method for a fleet of USVs.

A neuromuscular model of human locomotion combines spinal reflex circuits with voluntary movements

Existing models of human walking use low-level reflexes or neural oscillators to generate movement. While appropriate to generate the stable, rhythmic movement patterns of steady-state walking, these models lack the ability to change their movement patterns or spontaneously generate new movements in the specific, goal-directed way characteristic of voluntary movements. Here we present a neuromuscular model of human locomotion that bridges this gap and combines the ability to execute goal directed movements with the generation of stable, rhythmic movement patterns that are required for robust locomotion. The model represents goals for voluntary movements of the swing leg on the task level of swing leg joint kinematics. Smooth movements plans towards the goal configuration are generated on the task level and transformed into descending motor commands that execute the planned movements, using internal models. The movement goals and plans are updated in real time based on sensory feedback and task constraints. On the spinal level, the descending commands during the swing phase are integrated with a generic stretch reflex for each muscle. Stance leg control solely relies on dedicated spinal reflex pathways. Spinal reflexes stimulate Hill-type muscles that actuate a biomechanical model with eight internal joints and six free-body degrees of freedom. The model is able to generate voluntary, goal-directed reaching movements with the swing leg and combine multiple movements in a rhythmic sequence. During walking, the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. With this combination of reflex-based stance leg and voluntary, goal-directed control of the swing leg, the model controller generates rhythmic, stable walking patterns in which the swing leg movement can be flexibly updated in real-time to step over or around obstacles.

Frequency‐dependent modulation of neural oscillations across the gait cycle

Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait‐related modulations of neural activity, we collected high‐density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event‐related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG‐based brain–body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders.

Influence of Controlled Stomatognathic Motor Activity on Sway, Control and Stability of the Center of Mass During Dynamic Steady-State Balance-An Uncontrolled Manifold Analysis.

Multiple sensory signals from visual, somatosensory and vestibular systems are used for human postural control. To maintain postural stability, the central nervous system keeps the center of mass (CoM) within the base of support. The influence of the stomatognathic motor system on postural control has been established under static conditions, but it has not yet been investigated during dynamic steady-state balance. The purpose of the study was to investigate the effects of controlled stomatognathic motor activity on the control and stability of the CoM during dynamic steady-state balance. A total of 48 physically active and healthy adults were assigned to three groups with different stomatognathic motor conditions: jaw clenching, tongue pressing and habitual stomatognathic behavior. Dynamic steady-state balance was assessed using an oscillating platform and the kinematic data were collected with a 3D motion capturing system. The path length (PL) of the 3D CoM trajectory was used for quantifying CoM sway. Temporal dynamics of the CoM movement was assessed with a detrended fluctuation analysis (DFA). An uncontrolled manifold (UCM) analysis was applied to assess the stability and control of the CoM with a subject-specific anthropometric 3D model. The statistical analysis revealed that the groups did not differ significantly in PL, DFA scaling exponents or UCM parameters. The results indicated that deliberate jaw clenching or tongue pressing did not seem to affect the sway, control or stability of the CoM on an oscillating platform significantly. Because of the task-specificity of balance, further research investigating the effects of stomatognathic motor activities on dynamic steady-state balance with different movement tasks are needed. Additionally, further analysis by use of muscle synergies or co-contractions may reveal effects on the level of muscles, which were not visible on the level of kinematics. This study can contribute to the understanding of postural control mechanisms, particularly in relation to stomatognathic motor activities and under dynamic conditions.

Magnetorquers-based satellite attitude control using interval type-II fuzzy terminal sliding mode control with time delay estimation

This paper presents a novel robust attitude controller for satellite applications with magnetic actuation. First, at the kinematical level, a terminal sliding mode (TSM)-based sliding surface is proposed to achieve attitude tracking. Next, at the dynamical level, a controller is designed for robust stabilization of the sliding surface. Time delay estimation (TDE) is used to estimate the uncertainty caused by parametric uncertainty and external disturbances in the satellite dynamics. The TDE output is then combined with an interval type-2 fuzzy logic (IT2FL)-based robust TSM controller. The main merits of this control strategy are fast convergence of the tracking errors and strong robustness against disturbances/parametric uncertainty. The closed-loop stability and convergence of the tracking errors are proved by Lyapunov analysis. Software simulations confirm the effectiveness of the proposed control method.

Segmental Motion of Cervical Arthroplasty Leads to Decreased Adjacent-Level Degeneration: Analysis of the 7-Year Postoperative Results of a Multicenter Randomized Controlled Trial.

Cervical artificial disc replacement (C-ADR) has become a common and accepted surgical treatment for many patients with cervical disc degeneration/herniation and radiculopathy who have failed nonoperative treatment. Midterm follow-up studies of the original investigational device exemption trials comparing C-ADR to traditional anterior cervical discectomy and fusion (ACDF) have revealed C-ADR patients have less adjacent-level disease and fewer reoperations at 5 to 7 years. The purpose of this study was to examine the relationship of radiographic adjacent-level disease (R-ALD) with the amount of index-level segmental range of motion (ROM) in C-ADR patients using the long-term follow-up data from the ProDisc-C investigational device exemption trial. This was a post hoc analysis of a 1:1 randomized controlled trial. The initial previously described Food and Drug Administration-approved 2-year study was extended, and consenting patients in the original study were followed at annual intervals up to 7 years. Logistic regression was used to assess any progression in adjacent-level disease (ALD). Ordinal logistic regression was also used to assess the relationship between any progressive R-ALD and final flexion extension (F/E) ROM in C-ADR patients. Spearman's rank-order correlation was used when R-ALD was kept as an ordinal variable to assess the same relationship. At the last follow-up visit, the rate of progressive R-ALD was significantly higher in ACDF patients than in C-ADR patients. When C-ADR patients were divided into 3 groups based on final F/E ROM, those with 0° to 3° (n = 19), 4° to 6° (n = 15), and 7° (n = 42) of segmental motion at the index procedure level, the rate of progressive R-ALD trended significantly with final ROM (P = 0.01). C-ADR leads to a significant decrease in R-ALD compared to ACDF. The difference in R-ALD is related to the preservation of motion at the index level and resultant preservation of kinematics and forces across the adjacent disc space.

MPC-based distributed formation control of multiple quadcopters with obstacle avoidance and connectivity maintenance

In this work, a distributed model predictive control (MPC) scheme based on consensus theory is proposed for the formation control of a group of quadcopters. The MPC scheme provides velocities for the quadcopters, which are considered as holonomic agents modeled at kinematic level. We propose soft and hard constraints for the MPC problem to address collision and obstacle avoidance as well as to maintain the connectivity of the communication topology during the motion of the agents to reach the desired formation. The contributions of this work are the following: First, we propose an integrated solution for the three tasks, including connectivity maintenance, which is uncommon in existing approaches, in addition to dynamic formation control and collision/obstacle avoidance. Second, we show that using both soft and hard constraints in the MPC problem gives better performance than using only one of the two. Third, unlike most MPC-based schemes from the literature, the effectiveness of our approach is validated through real experiments for a group of quadcopters.

Acoustic and Kinematic Correlates of Heterosyllabicity in Different Phonological Contexts.

We investigate the temporal and kinematic properties of consonant gemination and heterosyllabic clusters as opposed to singletons and tautosyllabic clusters in Italian. The data show that the singleton versus geminate contrast is conveyed by specific kinematic properties in addition to systematic durational differences in both the consonantal and vocalic intervals; by contrast, tautosyllabic and heterosyllabic clusters differ significantly for the duration of the consonantal interval but do not vary systematically with respect to the vocalic interval and cannot be consistently differentiated at the kinematic level. We conclude that systematic variations in acoustic vowel duration and the kinematics of tongue tip gestures represent the phonetic correlates of the segmental phonological contrast between short and long consonants, rather than of syllable structure. Data are only partly consistent with the predictions of both moraic and gesture-based models of the syllable about the effects of syllable structure on speech production dynamics and call for a more gradient view of syllabification.

Identification of Vehicle System Dynamics from the Aspect of Interaction between the Steering and the Suspension Systems

Steering and suspension systems of a motor vehicle have very important mutual connections that have direct influence on a vehicle’s steerability, stability, comfort and life expectancy. These mechanical and functional couplings cause an intensive interaction between the two mentioned vehicle systems on a geometrical, kinematical and dynamical level. This article presents a study on nonparametric identification of dynamic interaction between the steering and the suspension system of a passenger vehicle. A specific methodology for experimental research in on-road conditions was designed that was in line with the research objectives and the applied measuring system. Experimental data were acquired for a curvilinear drive, with different constant driving speeds and on different roads. A multiple input/multiple output model for identification of the vehicle dynamics system from the aspect of interaction between the steering and the suspension system was developed. The analysis of experimental data was realized with the selection of a corresponding identification model, decoupling of model inputs and conditioned spectral analysis. The results of the conditioned spectral analysis of experimentally obtained data records indicate the level of interaction between the observed input and output parameters of the steering and the suspension systems to be in the frequency range below 30 Hz.