A Walking Gait for Robot NAO by Using the Essential Model

2021 ◽  
pp. 9-17
Author(s):  
Emanuel Marquez Acosta ◽  
Victor De-León-Gómez ◽  
Victor Santibañez
Keyword(s):  
Walking Gait

scholarly journals Sensory-Motor Mechanisms Increasing Falls Risk in Diabetic Peripheral Neuropathy

Medicina ◽  
2021 ◽  
Vol 57 (5) ◽  
pp. 457
Author(s):  
Neil D. Reeves ◽  
Giorgio Orlando ◽  
Steven J. Brown
Keyword(s):  
Peripheral Neuropathy ◽  
Diabetic Peripheral Neuropathy ◽  
Motor Nerve ◽  
Step Length ◽  
Falls Prevention ◽  
Motor Deficits ◽  
Falls Risk ◽  
Walking Gait ◽  
Risk Of Falls ◽  
Diabetes Patients

Diabetic peripheral neuropathy (DPN) is associated with peripheral sensory and motor nerve damage that affects up to half of diabetes patients and is an independent risk factor for falls. Clinical implications of DPN-related falls include injury, psychological distress and physical activity curtailment. This review describes how the sensory and motor deficits associated with DPN underpin biomechanical alterations to the pattern of walking (gait), which contribute to balance impairments underpinning falls. Changes to gait with diabetes occur even before the onset of measurable DPN, but changes become much more marked with DPN. Gait impairments with diabetes and DPN include alterations to walking speed, step length, step width and joint ranges of motion. These alterations also impact the rotational forces around joints known as joint moments, which are reduced as part of a natural strategy to lower the muscular demands of gait to compensate for lower strength capacities due to diabetes and DPN. Muscle weakness and atrophy are most striking in patients with DPN, but also present in non-neuropathic diabetes patients, affecting not only distal muscles of the foot and ankle, but also proximal thigh muscles. Insensate feet with DPN cause a delayed neuromuscular response immediately following foot–ground contact during gait and this is a major factor contributing to increased falls risk. Pronounced balance impairments measured in the gait laboratory are only seen in DPN patients and not non-neuropathic diabetes patients. Self-perception of unsteadiness matches gait laboratory measures and can distinguish between patients with and without DPN. Diabetic foot ulcers and their associated risk factors including insensate feet with DPN and offloading devices further increase falls risk. Falls prevention strategies based on sensory and motor mechanisms should target those most at risk of falls with DPN, with further research needed to optimise interventions.

scholarly journals Task space adaptation via the learning of gait controllers of magnetic soft millirobots

2021 ◽  
pp. 027836492110218
Author(s):  
Sinan O. Demir ◽  
Utku Culha ◽  
Alp C. Karacakol ◽  
Abdon Pena-Francesch ◽  
Sebastian Trimpe ◽  
...  
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Bayesian Optimization ◽  
Small Scale ◽  
Soft Robots ◽  
Modeling And Control ◽  
Walking Gait ◽  
Physical Experiments ◽  
Efficient Learning ◽  
Task Environments

Untethered small-scale soft robots have promising applications in minimally invasive surgery, targeted drug delivery, and bioengineering applications as they can directly and non-invasively access confined and hard-to-reach spaces in the human body. For such potential biomedical applications, the adaptivity of the robot control is essential to ensure the continuity of the operations, as task environment conditions show dynamic variations that can alter the robot’s motion and task performance. The applicability of the conventional modeling and control methods is further limited for soft robots at the small-scale owing to their kinematics with virtually infinite degrees of freedom, inherent stochastic variability during fabrication, and changing dynamics during real-world interactions. To address the controller adaptation challenge to dynamically changing task environments, we propose using a probabilistic learning approach for a millimeter-scale magnetic walking soft robot using Bayesian optimization (BO) and Gaussian processes (GPs). Our approach provides a data-efficient learning scheme by finding the gait controller parameters while optimizing the stride length of the walking soft millirobot using a small number of physical experiments. To demonstrate the controller adaptation, we test the walking gait of the robot in task environments with different surface adhesion and roughness, and medium viscosity, which aims to represent the possible conditions for future robotic tasks inside the human body. We further utilize the transfer of the learned GP parameters among different task spaces and robots and compare their efficacy on the improvement of data-efficient controller learning.

Discrete element and finite element methods provide similar estimations for hip joint contact mechanics during walking gait

2021 ◽  
Vol 115 ◽  
pp. 110163
Author(s):  
Mao Li ◽  
Mikko S. Venäläinen ◽  
Shekhar S. Chandra ◽  
Rushabh Patel ◽  
Jurgen Fripp ◽  
...  
Keyword(s):  
Finite Element ◽  
Contact Mechanics ◽  
Hip Joint ◽  
Finite Element Methods ◽  
Discrete Element ◽  
Walking Gait ◽  
Joint Contact

A Comparison of the Birth Characteristics of Idiopathic Toe Walking and Toe Walking Gait Due to Medical Reasons

2016 ◽  
Vol 171 ◽  
pp. 290-293 ◽  
Author(s):  
Stephanie Baber ◽  
Joanne Michalitsis ◽  
Michael Fahey ◽  
Barry Rawicki ◽  
Terry Haines ◽  
...  
Keyword(s):  
Walking Gait ◽  
Idiopathic Toe Walking ◽  
Birth Characteristics ◽  
Toe Walking

Hybrid Control of the Berkeley Lower Extremity Exoskeleton (BLEEX)

2005 ◽  
Author(s):  
Lihua Huang ◽  
Ryan Ryan Steger ◽  
H. Kazerooni
Keyword(s):  
Position Control ◽  
Hybrid Control ◽  
System Sensitivity ◽  
Walking Gait ◽  
Mixed Control ◽  
Stance Control ◽  
Control Scheme ◽  
Load Carrying ◽  
Human Limb ◽  
Careful Design

The first functional load-carrying and energetically autonomous exoskeleton was demonstrated at U.C. Berkeley, walking at the average speed of 0.9 m/s (2 mph) while carrying a 34 kg (75 lb) payload. The original BLEEX sensitivity amplification controller, based on positive feedback, was designed to increase the closed loop system sensitivity to its wearer’s forces and torques without any direct measurement from the wearer. The controller was successful at allowing natural and unobstructed load support for the pilot. This article presents an improved control scheme we call “mixed” control that adds robustness to changing BLEEX backpack payload. The walking gait cycle is divided into stance control and swing control phases. Position control is used for the BLEEX stance leg (including torso and backpack) and the sensitivity amplification controller is used for the swing leg. The controller is also designed to smoothly transitions between these two schemes as the pilot walks. With mixed control, the controller does not require a good model of the BLEEX torso and payload, which is difficult to obtain and subject to change as payload is added and removed. As a tradeoff, the position control used in this method requires the human to wear seven inclinometers to measure human limb and torso angles. These additional sensors require careful design to securely fasten them to the human and increase the time to don (and doff) BLEEX.

Design of a 6-DOF Robotic Gait Training System With Closed-Chain Foot Initiated Kinematics Control

2015 ◽  
Author(s):  
Wei Liu ◽  
John Kovaleski ◽  
Marcus Hollis
Keyword(s):  
Three Dimensional ◽  
Computer Software ◽  
Gait Training ◽  
Gait Pattern ◽  
Training System ◽  
Normal Walking ◽  
Robot Assisted ◽  
Walking Gait ◽  
The Right ◽  
Joint Motions

Robotic assisted rehabilitation, taking advantage of neuroplasticity, has been shown to be helpful in regaining some degree of gait performance. Robot-applied movement along with voluntary efferent motor commands coordinated with the robot allows optimization of motion training. We present the design and characteristics of a novel foot-based 6-degree-of-freedom (DOF) robot-assisted gait training system where the limb trajectory mirrored the normal walking gait. The goal of this study was to compare robot-assisted gait to normal walking gait, where the limb moved independently without robotics. Motion analysis was used to record the three-dimensional kinematics of the right lower extremity. Walking motion data were determined and transferred to the robotic motion application software for inclusion in the robotic trials where the robot computer software was programmed to produce a gait pattern in the foot equivalent to the gait pattern recorded from the normal walking gait trial. Results demonstrated that ankle; knee and hip joint motions produced by the robot are consistent with the joint motions in walking gait. We believe that this control algorithm provides a rationale for use in future rehabilitation, targeting robot-assisted training in people with neuromuscular disabilities such as stroke.

The elastic contact influences on passive walking gaits

Robotica ◽  
2010 ◽  
Vol 29 (5) ◽  
pp. 787-796 ◽  
Author(s):  
Feng Qi ◽  
Tianshu Wang ◽  
Junfeng Li
Keyword(s):  
Coulomb Friction ◽  
Dynamic Models ◽  
Contact Stiffness ◽  
Contact Forces ◽  
Hertz Contact ◽  
Walking Gait ◽  
Routes To Chaos ◽  
Coulomb Friction Law ◽  
Contact Parameters ◽  
Passive Model

SUMMARYThis paper presents a new planar passive dynamic model with contact between the feet and the ground. The Hertz contact law and the approximate Coulomb friction law were introduced into this human-like model. In contrast to McGeer's passive dynamic models, contact stiffness, contact damping, and coefficients of friction were added to characterize the walking model. Through numerical simulation, stable period-one gait and period-two gait cycles were found, and the contact forces were derived from the results. After investigating the effects of the contact parameters on walking gaits, we found that changes in contact stiffness led to changes in the global characteristics of the walking gait, but not in contact damping. The coefficients of friction related to whether the model could walk or not. For the simulation of the routes to chaos, we found that a small contact stiffness value will lead to a delayed point of bifurcation, meaning that a less rigid surface is easier for a passive model to walk on. The effects of contact damping and friction coefficients on routes to chaos were quite small.

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