Gravity Compensation and Feedback of Ground Reaction Forces for Biped Balance Control

Ito, Satoshi; Nishio, Satoshi; Fukumoto, Yukiomi; Matsushita, Kojiro; Sasaki, Minoru

doi:10.1155/2017/5980275

Cited by 8 publications

(3 citation statements)

References 38 publications

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“…In DSP, zero moment point moves from the supporting foot to the other supporting foot in the walking. This action is called a gait cycle and repeated in walking (S. Ito, S. Nishio, et al, 2017). Hence, the reference zero moment point trajectory can be utilized for a generation the walking pattern shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

Simulation and Experimental Walking Pattern Generation for Two Types of Degrees of Freedom Bipedal Locomotion Robot

Kareem

Ali

2020

jcoeng

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Humanoids or bipedal robots are other kinds of robots that have legs. The balance of humanoids is the general problem in these types when the other in the support phase and the leg in the swing phase. In this work, the walking pattern generation is studied by MATLAB for two types of degrees of freedom, 10 and 17 degrees of freedom. Besides, the KHR-2HV simulation model is used to simulate the experimental results by Webots. Similarly, Arduino and LOBOT LSC microcontrollers are used to program the bipedal robot. After the several methods for programming the bipedal robot by Arduino microcontroller, LOBOT LSC-32 driver model is the better than PCA 96685 Driver-16 channel servo driver for programming the bipedal walking robot. The results showed that this driver confirms the faster response than the Arduino microcontroller in walking the bipedal robot. The walking pattern generation results showed that the step height for 17 degrees of freedom bipedal robot increases approximately (20%) than 10 degrees of freedom bipedal robot, which decreases the step period by about (7%). Also, the time interval of the double support phase for 17 degrees of freedom bipedal robot increases approximately (11%) with decreases step length approximately (33% on X-axis) and (16% on Z-axis).

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Section: Resultsmentioning

confidence: 99%

Simulation and Experimental Walking Pattern Generation for Two Types of Degrees of Freedom Bipedal Locomotion Robot

Kareem

Ali

2020

jcoeng

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“…The objective is used for learning a feedforward compensative zero moment point CZMP trajectory from estimated ZMP errors during cyclic motions by using ZMP principles. Satoshi Ito et al considered the balance control of a humanoid robot on the sloped ground or under a constant external force [7]. The proposed adaptive posture changes and realized a control method with the feedback of the GRF.…”

Section: Introductionmentioning

confidence: 99%

Robust Stability Control of Inverted Pendulum Model for Bipedal Walking Robot

Kareem

Ali

2020

NJES

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This paper proposes robust control for three models of the linear inverted pendulum (one mass linear inverted pendulum model, two masses linear inverted pendulum model and three masses linear inverted pendulum model) which represents the upper, middle and lower body of a bipedal walking robot. The bipedal walking robot is built of light-weight and hard Aluminum sheets with 2 mm thickness. The minimum phase system and non-minimum phase system are studied and investigated for inverted pendulum models. The bipedal walking robot is programmed by Arduino microcontroller UNO. A MATLAB Simulink system is built to embrace the theoretical work. The results showed that one linear inverted pendulum is the worst performance, worst noise rejection and the worst set point tracking to the zero moment point. But two masses linear inverted pendulum models and three masses linear inverted pendulum model have a better performance, a better high-frequency noise rejection characteristic and better set-point tracking to the zero moment point.

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“…In this case, the detection was confined to the sagittal plane. Yılmaz et al, 24 Ito et al, 25 Zhang et al, 26 and Joe et al 27 proposed a posture-control algorithm that adjusts the orientation of the pitch angle of the upper body to adapt to different slope walking surfaces and ensures robot stability.…”

Section: Introductionmentioning

confidence: 99%

Posture control for humanoid robot on uneven ground and slopes using inertial sensors

Chiang

Wang

2014

Advances in Mechanical Engineering

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We designed a stable gait pattern and posture-control balance system to enable a biped humanoid robot to maintain balance and avoid falling when walking on uneven ground or slopes. In this study, we first examined the problem of gait generation and the balance of a humanoid robot and then proposed a posture-control balance system using the inertial sensors of a gyroscope and accelerometer to sense the tilt angle of the robot according to the environment. To process the data obtained by the sensors, the mean filter was applied to eliminate the noise in the data, and the complementary filter was used to properly combine the data from both the gyroscope and accelerometer. The system further modifies the gait and posture of the robot based on the results obtained through a fuzzy system to attain the angle of balance and stabilization. A robot with an open platform was used to test the implementation of the proposed algorithm, and the experimental results demonstrated that the robot could successfully maintain balance when walking uphill and downhill on uneven surfaces. Moreover, because only one parameter needs to be adjusted when applying the balance-control system, the system can be easily extended to any related humanoid robot.

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Gravity Compensation and Feedback of Ground Reaction Forces for Biped Balance Control

Cited by 8 publications

References 38 publications

Simulation and Experimental Walking Pattern Generation for Two Types of Degrees of Freedom Bipedal Locomotion Robot

Simulation and Experimental Walking Pattern Generation for Two Types of Degrees of Freedom Bipedal Locomotion Robot

Robust Stability Control of Inverted Pendulum Model for Bipedal Walking Robot

Posture control for humanoid robot on uneven ground and slopes using inertial sensors

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