Study of Bipedal Robot Walking Motion in Low Gravity: Investigation and Analysis

Omer, Aiman; Hashimoto, Kenji; Lim, Hun-ok; Takanishi, Atsuo

doi:10.5772/58731

Cited by 17 publications

(14 citation statements)

References 18 publications

(21 reference statements)

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“…Moreover, the base was assumed fixed, making it two serial-link manipulators in which one manipulator is moved 180° out of phase with the other one [ 61 – 64 ]. The average thigh clearance given in the literature for a man is 0.78 in, and for women, 0.90 in [ 65 , 66 ]. The end-effector position and orientation were derived from the Denavit-Hartenberg (D-H) notation [ 57 , 59 , 67 , 68 ].…”

Section: Methodsmentioning

confidence: 99%

fNIRS-based Neurorobotic Interface for gait rehabilitation

Khan

Naseer

Qureshi

et al. 2018

J NeuroEngineering Rehabil

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BackgroundIn this paper, a novel functional near-infrared spectroscopy (fNIRS)-based brain-computer interface (BCI) framework for control of prosthetic legs and rehabilitation of patients suffering from locomotive disorders is presented.MethodsfNIRS signals are used to initiate and stop the gait cycle, while a nonlinear proportional derivative computed torque controller (PD-CTC) with gravity compensation is used to control the torques of hip and knee joints for minimization of position error. In the present study, the brain signals of walking intention and rest tasks were acquired from the left hemisphere’s primary motor cortex for nine subjects. Thereafter, for removal of motion artifacts and physiological noises, the performances of six different filters (i.e. Kalman, Wiener, Gaussian, hemodynamic response filter (hrf), Band-pass, finite impulse response) were evaluated. Then, six different features were extracted from oxygenated hemoglobin signals, and their different combinations were used for classification. Also, the classification performances of five different classifiers (i.e. k-Nearest Neighbour, quadratic discriminant analysis, linear discriminant analysis (LDA), Naïve Bayes, support vector machine (SVM)) were tested.ResultsThe classification accuracies obtained from SVM using the hrf were significantly higher (p < 0.01) than those of the other classifier/ filter combinations. Those accuracies were 77.5, 72.5, 68.3, 74.2, 73.3, 80.8, 65, 76.7, and 86.7% for the nine subjects, respectively.ConclusionThe control commands generated using the classifiers initiated and stopped the gait cycle of the prosthetic leg, the knee and hip torques of which were controlled using the PD-CTC to minimize the position error. The proposed scheme can be effectively used for neurofeedback training and rehabilitation of lower-limb amputees and paralyzed patients.

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Section: Methodsmentioning

confidence: 99%

fNIRS-based Neurorobotic Interface for gait rehabilitation

Khan

Naseer

Qureshi

et al. 2018

J NeuroEngineering Rehabil

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“…When the model has smooth feet and base made from PLA only, the maximum height it can overcome is 19 (mm), this corresponds to a factor of K ro ¼ 0.17 calculated from equation (8). The same model but with FilaFlex pads on the feet and the base overcomes a height of 37 (mm) which corresponds to K ro ¼ 0.34.…”

Section: Results From the Experimentsmentioning

confidence: 99%

“…As a result, the robot can attack and overcome high obstacles with the feet. Such optimization of the dimensions of the robot also improves the dimensionless coefficient K ro (8), because by preserving the size of the robot the possibility of overcoming a higher obstacle h 0 < h S max is increased.…”

Section: Geometric Proportions Of the Links Of The Robotmentioning

confidence: 99%

“…It is developed a 3-D model of the robot with a round smooth base and flat feet. The angular velocity of the drive shaft (8) (Figure 1) is determined using the catalogue data of the used GM22 gearmotor with gear ratio i ¼ 298 and the gear ratio of the gear mechanism i ¼ 4. The resulting angular velocity 60 ( /s) is set as the velocity constant of the virtual motor.…”

Section: Description Of the Simulationmentioning

confidence: 99%

“…There exist two-legged robots that allow for movement while maintaining static stability. [6][7][8] Design solutions with a minimum number of mechanical components are considered. 9,10 In Jeon et al, 11 a low-budget two-legged robot with three degrees of freedom and static stability is presented.…”

Section: Introductionmentioning

confidence: 99%

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Design and kinematics of a 3-D printed walking robot “Big Foot”, overcoming obstacles

Chavdarov

Naydenov

2019

International Journal of Advanced Robotic Systems

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The proposed study presents an original concept for the design of a walking robot with a minimum number of motors. The robot has a simple design and control system, successfully moves by walking, avoids or overcomes obstacles using only two independently controlled motors. Described are basic geometric and kinematic dependencies related to its movement. It is proposed optimization of basic dimensions of the robot in order to reduce energy losses when moving on flat terrain. Developed and produced is a 3-D printed prototype of the robot. Simulation and experiments for overcoming an obstacle are presented. Trajectories and instantaneous velocities centers of links from the robot are experimentally determined. The phases of walking and the stages of overcoming an obstacle are described. The theoretical and experimental results are compared. The suggested dimensional optimization approaches to reduce energy loss and experimental determination of the instant center of rotation are also applicable to other walking robots.

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