Energy Efficient and Robust Balancing with Motion Primitive Switching

Balancing motions are usually designed using simplified models of the Center of Mass (CoM) and feedback control without accounting for energy efficiency. In order to tackle this shortcoming, we introduce a Motion Primitive switching methodology where samples of optimal motions (Motion Primitives) are chosen online based on a Euclidean distance metric. The chosen sample is used to provide reference trajectories, torques and ground reaction forces to be tracked. In order to satisfy all of the modeling assumptions while tracking the reference values, a Quadratic Program (QP) is solved online where the dynamics of the robot, friction, Center of Pressure and torque bounds are treated as constraints. Convergence to the desired trajectories is dictated by a Control Lyapunov Function constraint which is introduced in the QP. The methodology is evaluated on a four-link simulated robot where we show that switching between Motion Primitives provides energy efficient balancing motions for different disturbance situations. At the same time the methodology provides more efficient motions for different disturbance forces when compared to a nonswitching approach, where a Motion Primitive is chosen only once at the beginning.

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Active foot placement control ensures stable gait: Effect of constraints on foot placement and ankle moments

PLoS ONE ◽

10.1371/journal.pone.0242215 ◽

2020 ◽

Vol 15 (12) ◽

pp. e0242215

Author(s):

A. M. van Leeuwen ◽

J. H. van Dieën ◽

A. Daffertshofer ◽

S. M. Bruijn

Keyword(s):

Steady State ◽

Center Of Pressure ◽

Center Of Mass ◽

Reaction Force ◽

Stride Frequency ◽

Tight Control ◽

Foot Placement ◽

Ankle Moment ◽

Reaction Forces ◽

Moment Control

Step-by-step foot placement control, relative to the center of mass (CoM) kinematic state, is generally considered a dominant mechanism for maintenance of gait stability. By adequate (mediolateral) positioning of the center of pressure with respect to the CoM, the ground reaction force generates a moment that prevents falling. In healthy individuals, foot placement is complemented mainly by ankle moment control ensuring stability. To evaluate possible compensatory relationships between step-by-step foot placement and complementary ankle moments, we investigated the degree of (active) foot placement control during steady-state walking, and under either foot placement-, or ankle moment constraints. Thirty healthy participants walked on a treadmill, while full-body kinematics, ground reaction forces and EMG activities were recorded. As a replication of earlier findings, we first showed step-by-step foot placement is associated with preceding CoM state and hip ab-/adductor activity during steady-state walking. Tight control of foot placement appears to be important at normal walking speed because there was a limited change in the degree of foot placement control despite the presence of a foot placement constraint. At slow speed, the degree of foot placement control decreased substantially, suggesting that tight control of foot placement is less essential when walking slowly. Step-by-step foot placement control was not tightened to compensate for constrained ankle moments. Instead compensation was achieved through increases in step width and stride frequency.

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Effects of additional load at different heights on gait initiation: A statistical parametric mapping of center of pressure and center of mass behavior

PLoS ONE ◽

10.1371/journal.pone.0242892 ◽

2021 ◽

Vol 16 (6) ◽

pp. e0242892

Author(s):

Marcus Fraga Vieira ◽

Fábio Barbosa Rodrigues ◽

Alfredo de Oliveira Assis ◽

Eduardo de Mendonça Mesquita ◽

Thiago Santana Lemes ◽

...

Keyword(s):

Time Series ◽

Center Of Pressure ◽

Center Of Mass ◽

Statistical Parametric Mapping ◽

Gait Initiation ◽

Experimental Conditions ◽

Distributed Load ◽

Uniformly Distributed Load ◽

Reaction Forces ◽

Controlled Object

The purpose of this study was to investigate the effects of different vertical positions of an asymmetrical load on the anticipatory postural adjustments phase of gait initiation. Sixty-eight college students (32 males, 36 females; age: 23.65 ± 3.21 years old; weight: 69.98 ± 8.15 kg; height: 1.74 ± 0.08 m) were enrolled in the study. Ground reaction forces and moments were collected using two force platforms. The participants completed three trials under each of the following random conditions: no-load (NL), waist uniformly distributed load (WUD), shoulder uniformly distributed load (SUD), waist stance foot load (WST), shoulder stance foot load (SST), waist swing foot load (WSW), and shoulder swing foot load (SSW). The paired Hotelling’s T-square test was used to compare the experimental conditions. The center of pressure (COP) time series were significantly different for the SUD vs. NL, SST vs. NL, WST vs. NL, and WSW vs. NL comparisons. Significant differences in COP time series were observed for all comparisons between waist vs. shoulder conditions. Overall, these differences were greater when the load was positioned at the shoulders. For the center of mass (COM) time series, significant differences were found for the WUD vs. NL and WSW vs. NL conditions. However, no differences were observed with the load positioned at the shoulders. In conclusion, only asymmetrical loading at the waist produced significant differences, and the higher the extra load, the greater the effects on COP behavior. By contrast, only minor changes were observed in COM behavior, suggesting that the changes in COP (the controller) behavior are adjustments to maintain the COM (controlled object) unaltered.

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Human kinematic, kinetic and EMG data during different walking and stair ascending and descending tasks

Scientific Data ◽

10.1038/s41597-019-0323-z ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 5

Author(s):

Tiziana Lencioni ◽

Ilaria Carpinella ◽

Marco Rabuffetti ◽

Alberto Marzegan ◽

Maurizio Ferrarin

Keyword(s):

Lower Limb ◽

Center Of Pressure ◽

Center Of Mass ◽

Simulation Models ◽

Human Locomotion ◽

Surface Emg ◽

Whole Body ◽

Bipedal Robots ◽

Lower Limb Muscles ◽

Reaction Forces

AbstractThis paper reports the kinematic, kinetic and electromyographic (EMG) dataset of human locomotion during level walking at different velocities, toe- and heel-walking, stairs ascending and descending. A sample of 50 healthy subjects, with an age between 6 and 72 years, is included. For each task, both raw data and computed variables are reported including: the 3D coordinates of external markers, the joint angles of lower limb in the sagittal, transversal and horizontal anatomical planes, the ground reaction forces and torques, the center of pressure, the lower limb joint mechanical moments and power, the displacement of the whole body center of mass, and the surface EMG signals of the main lower limb muscles. The data reported in the present study, acquired from subjects with different ages, represents a valuable dataset useful for future studies on locomotor function in humans, particularly as normative reference to analyze pathological gait, to test the performance of simulation models of bipedal locomotion, and to develop control algorithms for bipedal robots or active lower limb exoskeletons for rehabilitation.

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Active foot placement control ensures stable gait: Effect of constraints on foot placement and ankle moments

10.1101/2020.06.10.143867 ◽

2020 ◽

Cited By ~ 1

Author(s):

A.M. van Leeuwen ◽

J.H. van Dieën ◽

A. Daffertshofer ◽

S.M. Bruijn

Keyword(s):

Steady State ◽

Center Of Pressure ◽

Center Of Mass ◽

Reaction Force ◽

Stride Frequency ◽

Tight Control ◽

Foot Placement ◽

Ankle Moment ◽

Reaction Forces ◽

Moment Control

AbstractStep-by-step foot placement control, relative to the center of mass (CoM) kinematic state, is generally considered a dominant mechanism for maintenance of gait stability. By adequate (mediolateral) positioning of the center of pressure with respect to the CoM, the ground reaction force generates a moment that prevents falling. In healthy individuals, foot placement is complemented mainly by ankle moment control ensuring stability. To evaluate possible compensatory relationships between step-by-step foot placement and complementary ankle moments, we investigated the degree of (active) foot placement control during steady-state walking, and under either foot placement-, or ankle moment constraints. Thirty healthy participants walked on a treadmill, while full-body kinematics, ground reaction forces and EMG activities were recorded. As a replication of earlier findings, we first showed step-by-step foot placement is associated with preceding CoM state and hip ab-/adductor activity during steady-state walking. Tight control of foot placement appears to be important at normal walking speed because there was a limited change in the degree of foot placement control despite the presence of a foot placement constraint. At slow speed, the degree of foot placement control decreased substantially, suggesting that tight control of foot placement is less essential when walking slowly. Step-by-step foot placement control was not tightened to compensate for constrained ankle moments. Instead compensation was achieved through increases in step width and stride frequency.

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Effects of additional load at different heights on gait initiation: a statistical parametric mapping of center of pressure and center of mass behavior

10.1101/2020.11.12.380261 ◽

2020 ◽

Author(s):

Marcus Fraga Vieira ◽

Fábio Barbosa Rodrigues ◽

Alfredo de Oliveira Assis ◽

Eduardo de Mendonça Mesquita ◽

Thiago Santana Lemes ◽

...

Keyword(s):

Time Series ◽

Center Of Pressure ◽

Center Of Mass ◽

Statistical Parametric Mapping ◽

Gait Initiation ◽

Experimental Conditions ◽

Distributed Load ◽

Uniformly Distributed Load ◽

Reaction Forces ◽

Controlled Object

AbstractThe purpose of this study was to investigate the effects of different vertical positions of an asymmetrical load on the anticipatory postural adjustments phase of gait initiation. Sixty-eight college students (32 males, 36 females; age: 23.65 ± 3.21 years old; weight: 69.98 ± 8.15 kg; height: 1.74 ± 0.08 m) were enrolled in the study. Ground reaction forces and moments were collected using two force platforms. The participants completed three trials under each of the following random conditions: no-load (NL), waist uniformly distributed load (WUD), shoulder uniformly distributed load (SUD), waist stance foot load (WST), shoulder stance foot load (SST), waist swing foot load (WSW), and shoulder swing foot load (SSW). The paired Hotelling’s T-square test was used to compare the experimental conditions. The center of pressure (COP) time series were significantly different for the SUD vs. NL, SST vs. NL, WST vs. NL, and WSW vs. NL comparisons. Significant differences in COP time series were observed for all comparisons between waist vs. shoulder conditions. Overall, these differences were greater when the load was positioned at the shoulders. For the center of mass (COM) time series, significant differences were found for the WUD vs. NL and WSW vs. NL conditions. However, no differences were observed with the load positioned at the shoulders. In conclusion, only asymmetrical loading at the waist produced significant differences, and the higher the extra load, the greater the effects on COP behavior. By contrast, only minor changes were observed in COM behavior, suggesting that the changes in COP (the controller) behavior are adjustments to maintain the COM (controlled object) unaltered.

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Estimation of Three-Dimensional Lower Limb Kinetics Data during Walking Using Machine Learning from a Single IMU Attached to the Sacrum

Sensors ◽

10.3390/s20216277 ◽

2020 ◽

Vol 20 (21) ◽

pp. 6277

Author(s):

Myunghyun Lee ◽

Sukyung Park

Keyword(s):

Center Of Pressure ◽

Center Of Mass ◽

Three Dimensional ◽

Lower Limbs ◽

Three Dimensions ◽

Measurement Unit ◽

Ann Model ◽

Joint Torques ◽

Reaction Forces ◽

Mean Square Errors

Kinetics data such as ground reaction forces (GRFs) are commonly used as indicators for rehabilitation and sports performance; however, they are difficult to measure with convenient wearable devices. Therefore, researchers have attempted to estimate accurately unmeasured kinetics data with artificial neural networks (ANNs). Because the inputs to an ANN affect its performance, they must be carefully selected. The GRF and center of pressure (CoP) have a mechanical relationship with the center of mass (CoM) in the three dimensions (3D). This biomechanical characteristic can be used to establish an appropriate input and structure of an ANN. In this study, an ANN for estimating gait kinetics with a single inertial measurement unit (IMU) was designed; the kinematics of the IMU placed on the sacrum as a proxy for the CoM kinematics were applied based on the 3D spring mechanics. The walking data from 17 participants walking at various speeds were used to train and validate the ANN. The estimated 3D GRF, CoP trajectory, and joint torques of the lower limbs were reasonably accurate, with normalized root-mean-square errors (NRMSEs) of 6.7% to 15.6%, 8.2% to 20.0%, and 11.4% to 24.1%, respectively. This result implies that the biomechanical characteristics can be used to estimate the complete three-dimensional gait data with an ANN model and a single IMU.

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Transfer and generalization of learned manipulation between unimanual and bimanual tasks

Scientific Reports ◽

10.1038/s41598-021-87988-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Trevor Lee-Miller ◽

Marco Santello ◽

Andrew M. Gordon

Keyword(s):

Learning Transfer ◽

Center Of Pressure ◽

Center Of Mass ◽

Pressure Point ◽

Torque Generation ◽

Before And After ◽

Object Center ◽

High Level ◽

Bimanual Grasping ◽

Partial Learning

AbstractSuccessful object manipulation, such as preventing object roll, relies on the modulation of forces and centers of pressure (point of application of digits on each grasp surface) prior to lift onset to generate a compensatory torque. Whether or not generalization of learned manipulation can occur after adding or removing effectors is not known. We examined this by recruiting participants to perform lifts in unimanual and bimanual grasps and analyzed results before and after transfer. Our results show partial generalization of learned manipulation occurred when switching from a (1) unimanual to bimanual grasp regardless of object center of mass, and (2) bimanual to unimanual grasp when the center of mass was on the thumb side. Partial generalization was driven by the modulation of effectors’ center of pressure, in the appropriate direction but of insufficient magnitude, while load forces did not contribute to torque generation after transfer. In addition, we show that the combination of effector forces and centers of pressure in the generation of compensatory torque differ between unimanual and bimanual grasping. These findings highlight that (1) high-level representations of learned manipulation enable only partial learning transfer when adding or removing effectors, and (2) such partial generalization is mainly driven by modulation of effectors’ center of pressure.

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Purcell’s Three-Link Swimmer: Assessment of Geometry and Gaits for Optimal Displacement and Efficiency

Mathematics ◽

10.3390/math9101088 ◽

2021 ◽

Vol 9 (10) ◽

pp. 1088

Author(s):

Cristina Nuevo-Gallardo ◽

José Emilio Traver ◽

Inés Tejado ◽

Blas M. Vinagre

Keyword(s):

Reynolds Number ◽

Multiobjective Optimization ◽

The Other ◽

Optimal Method ◽

Optimal Velocity ◽

Motion Primitives ◽

Motion Primitive ◽

Control Objective ◽

Optimal Efficiency ◽

The One

This paper studies the displacement and efficiency of a Purcell’s three-link microswimmer in low Reynolds number regime, capable of moving by the implementation of a motion primitive or gait. An optimization is accomplished attending to the geometry of the swimmer and the motion primitives, considering the shape of the gait and its amplitude. The objective is to find the geometry of the swimmer, amplitude and shape of the gaits which make optimal the displacement and efficiency, in both an individual way and combined (the last case will be referred to as multiobjective optimization). Three traditional gaits are compared with two primitives proposed by the authors and other three gaits recently defined in the literature. Results demonstrate that the highest displacement is obtained by the Tam and Hosoi optimal velocity gait, which also achieves the best efficiency in terms of energy consumption. The rectilinear and Tam and Hosoi optimal efficiency gaits are the second optimum primitives. Regarding the multiobjective optimization and considering the two criteria with the same weight, the optimum gaits turn out to be the rectilinear and Tam and Hosoi optimal efficiency gaits. Thus, the conclusions of this study can help designers to select, on the one hand, the best swimmer geometry for a desired motion primitive and, on the other, the optimal method of motion for trajectory tracking for such a kind of Purcell’s swimmers depending on the desired control objective.

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