Real-time foot attitude estimation for a humanoid robot based on inertial sensors and force sensor

Author(s):  
Jianxi Li ◽  
Qiang Huang ◽  
Weimin Zhang ◽  
Zhangguo Yu ◽  
Kejie Li
Sensors ◽  
2013 ◽  
Vol 13 (11) ◽  
pp. 15138-15158 ◽  
Author(s):  
José Guerrero-Castellanos ◽  
Heberto Madrigal-Sastre ◽  
Sylvain Durand ◽  
Lizeth Torres ◽  
German Muñoz-Hernández

2010 ◽  
Vol 44-47 ◽  
pp. 3781-3784
Author(s):  
Rui Hua Chang ◽  
Xiao Dong Mu ◽  
Xiao Wei Shen

An attitude estimation method is presented for a robot using low-cost solid-state inertial sensors. The attitude estimates are obtained from a complementary filter by combining the measurements from the integration of a tri-axis gyro and an aiding system mechanized using a tri-axis accelerometer and a tri-axis magnetometer. The results show that the estimation error is less than 1 degree compare to the reference attitude. It is a simple, yet effective method for attitude estimation, suitable for real-time implementation on a robot.


Author(s):  
Tingting Yin ◽  
Zhong Yang ◽  
Youlong Wu ◽  
Fangxiu Jia

The high-precision roll attitude estimation of the decoupled canards relative to the projectile body based on the bipolar hall-effect sensors is proposed. Firstly, the basis engineering positioning method based on the edge detection is introduced. Secondly, the simplified dynamic relative roll model is established where the feature parameters are identified by fuzzy algorithms, while the high-precision real-time relative roll attitude estimation algorithm is proposed. Finally, the trajectory simulations and grounded experiments have been conducted to evaluate the advantages of the proposed method. The positioning error is compared with the engineering solution method, and it is proved that the proposed estimation method has the advantages of the high accuracy and good real-time performance.


2010 ◽  
Vol 7 (10) ◽  
pp. 322-337 ◽  
Author(s):  
Rami D. Abousleiman ◽  
Osamah A. Rawashdeh ◽  
Mohammad-Reza Siadat

2021 ◽  
Vol 70 ◽  
pp. 1-12
Author(s):  
Meiyan Zhang ◽  
Qisong Wang ◽  
Dan Liu ◽  
Boqi Zhao ◽  
Jiaze Tang ◽  
...  

Author(s):  
Pierluigi Carcagnì ◽  
Dario Cazzato ◽  
Marco Del Coco ◽  
Pier Luigi Mazzeo ◽  
Marco Leo ◽  
...  

AbstractIn thiswork, a real-time system able to automatically recognize soft-biometric traits is introduced and used to improve the capability of a humanoid robot to interact with humans. In particular the proposed system is able to estimate gender and age of humans in images acquired from the embedded camera of the robot. This knowledge allows the robot to properly react with customized behaviors related to the gender/age of the interacting individuals. The system is able to handle multiple persons in the same acquired image, recognizing the age and gender of each person in the robot’s field of view. These features make the robot particularly suitable to be used in socially assistive applications.


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