Control of frontal plane body motion in human stepping

1997 ◽  
Vol 115 (2) ◽  
pp. 345-356 ◽  
Author(s):  
I. N. Lyon ◽  
B. L. Day
Keyword(s):  
Frontal Plane ◽  
Body Motion ◽  
Plane Body

318 Analysis of Frontal Plane Body Motion by Using Electric Skateboard

2012 ◽  
Vol 2012 (0) ◽  
pp. 454-459
Author(s):  
Motomichi SONOBE ◽  
Takuya NAGAMOTO ◽  
Junichi HINO ◽  
Yoshiki KATAOKA
Keyword(s):  
Frontal Plane ◽  
Body Motion ◽  
Plane Body

Dynamic locomotion synchronization of bipedal robot and human operator via bilateral feedback teleoperation

2019 ◽  
Vol 4 (35) ◽  
pp. eaav4282 ◽  
Author(s):  
Joao Ramos ◽  
Sangbae Kim
Keyword(s):  
Sagittal Plane ◽  
Frontal Plane ◽  
Humanoid Robots ◽  
Human Locomotion ◽  
Human Motion ◽  
Body Motion ◽  
Human Operator ◽  
Whole Body ◽  
Physical Endurance ◽  
Bipedal Robot

Despite remarkable progress in artificial intelligence, autonomous humanoid robots are still far from matching human-level manipulation and locomotion proficiency in real applications. Proficient robots would be ideal first responders to dangerous scenarios such as natural or man-made disasters. When handling these situations, robots must be capable of navigating highly unstructured terrain and dexterously interacting with objects designed for human workers. To create humanoid machines with human-level motor skills, in this work, we use whole-body teleoperation to leverage human control intelligence to command the locomotion of a bipedal robot. The challenge of this strategy lies in properly mapping human body motion to the machine while simultaneously informing the operator how closely the robot is reproducing the movement. Therefore, we propose a solution for this bilateral feedback policy to control a bipedal robot to take steps, jump, and walk in synchrony with a human operator. Such dynamic synchronization was achieved by (i) scaling the core components of human locomotion data to robot proportions in real time and (ii) applying feedback forces to the operator that are proportional to the relative velocity between human and robot. Human motion was sped up to match a faster robot, or drag was generated to synchronize the operator with a slower robot. Here, we focused on the frontal plane dynamics and stabilized the robot in the sagittal plane using an external gantry. These results represent a fundamental solution to seamlessly combine human innate motor control proficiency with the physical endurance and strength of humanoid robots.

scholarly journals Influence of Stance Width on Frontal Plane Postural Dynamics and Coordination in Human Balance Control

2010 ◽  
Vol 104 (2) ◽  
pp. 1103-1118 ◽  
Author(s):  
Adam D. Goodworth ◽  
Robert J. Peterka
Keyword(s):  
Frequency Response ◽  
Balance Control ◽  
Frontal Plane ◽  
Body Motion ◽  
Upper Body ◽  
Body Sway ◽  
Support Surface ◽  
Lower Body ◽  
Stimulus Amplitude ◽  
Postural System

The influence of stance width on frontal plane postural dynamics and coordination in human bipedal stance was studied. We tested the hypothesis that when subjects adopt a narrow stance width, they will rely heavily on nonlinear control strategies and coordinated counter-phase upper and lower body motion to limit center-of-mass (CoM) deviations from upright; as stance increases, the use of these strategies will diminish. Freestanding frontal plane body sway was evoked through continuous pseudorandom rotations of the support surface on which subjects stood with various stimulus amplitudes. Subjects were either eyes open (EO) or closed (EC) and adopted various stance widths. Upper body, lower body, and CoM kinematics were summarized using root-mean-square and peak-to-peak measures, and dynamic behavior was characterized using frequency-response and impulse-response functions. In narrow stance, CoM frequency-response function gains were reduced with increasing stimulus amplitude and in EO compared with EC; in wide stance, gain reductions were much less pronounced. Results show that the narrow stance postural system is nonlinear across stimulus amplitude in both EO and EC conditions, whereas the wide stance postural system is more linear. The nonlinearity in narrow stance is likely caused by an amplitude-dependent sensory reweighting mechanism. Finally, lower body and upper body sway were approximately in-phase at low frequencies (<1 Hz) and out-of-phase at high frequencies (>1 Hz) across all stance widths, and results were therefore inconsistent with the hypothesis that subjects made greater use of coordinated counter-phase upper and lower body motion in narrow compared with wide stance conditions.

scholarly journals Qualitative and Numerical Research of Body Motion in a Resisting Medium

2021 ◽  
Vol 20 ◽  
pp. 232-243
Author(s):  
Maxim V. Shamolin
Keyword(s):  
Circular Cylinder ◽  
Characteristic Time ◽  
External Surface ◽  
Frontal Plane ◽  
The Body ◽  
Body Motion ◽  
Resisting Medium ◽  
Parallel Motion ◽  
Resistant Medium ◽  
Numerical Research

Proposed activity presents next stage of the study of the problem of the plane-parallel motion of a rigid body interacting with a resistant medium through the frontal plane part of its external surface. Under constructing of the force acting of medium, we use the information on the properties of medium streamline fl w around in quasistationarity conditions (for instance, on the homogeneous circular cylinder input into the water). The medium motion is not studied, and we consider such problem in which the characteristic time of the body motion with respect to its center of masses is comparable with the characteristic time of motion of the center of masses itself.

Study on the Differences in the Results of Body Shape Test According to the Position of the Two Feet and the Usefulness of the Neck and Body Motion Image Test

2020 ◽  
Vol 9 (1) ◽  
pp. 22-26
Author(s):  
Wan Song Chang ◽  
◽  
Song Ja Kim ◽  
Seo Won Ryu ◽  
Duk Joon Lim ◽  
...  
Keyword(s):  
Body Shape ◽  
Body Motion ◽  
Image Test

Tire Rolling Kinematics Model for an Intelligent Tire Based on an Accelerometer

2020 ◽  
Vol 48 (4) ◽  
pp. 287-314
Author(s):  
Yan Wang ◽  
Zhe Liu ◽  
Michael Kaliske ◽  
Yintao Wei
Keyword(s):  
Elastic Deformation ◽  
Estimation Algorithm ◽  
Force Sensor ◽  
Euler Method ◽  
Rolling Contact ◽  
Body Motion ◽  
Identification Algorithm ◽  
Active Perception ◽  
Kinematics Model ◽  
Ring Model

ABSTRACT The idea of intelligent tires is to develop a tire into an active perception component or a force sensor with an embedded microsensor, such as an accelerometer. A tire rolling kinematics model is necessary to link the acceleration measured with the tire body elastic deformation, based on which the tire forces can be identified. Although intelligent tires have attracted wide interest in recent years, a theoretical model for the rolling kinematics of acceleration fields is still lacking. Therefore, this paper focuses on an explicit formulation for the tire rolling kinematics of acceleration, thereby providing a foundation for the force identification algorithms for an accelerometer-based intelligent tire. The Lagrange–Euler method is used to describe the acceleration field and contact deformation of rolling contact structures. Then, the three-axis acceleration vectors can be expressed by coupling rigid body motion and elastic deformation. To obtain an analytical expression of the full tire deformation, a three-dimensional tire ring model is solved with the tire–road deformation as boundary conditions. After parameterizing the ring model for a radial tire, the developed method is applied and validated by comparing the calculated three-axis accelerations with those measured by the accelerometer. Based on the features of acceleration, especially the distinct peak values corresponding to the tire leading and trailing edges, an intelligent tire identification algorithm is established to predict the tire–road contact length and tire vertical load. A simulation and experiments are conducted to verify the accuracy of the estimation algorithm, the results of which demonstrate good agreement. The proposed model provides a solid theoretical foundation for an acceleration-based intelligent tire.

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