Abstract
In this paper, a method of biped walking on a slope is studied, taking the NAO humanoid robot as research object. Firstly, we adopt the 3D linear inverted pendulum mode (3D-LIPM) to generate walking pattern, and obtain the reference trajectory of the center of mass (CoM). Then the Denavit-Hatenberg (D-H) parameters of the leg chain are determined based on the analysis of the NAO leg configuration. Finally in the process of walking, an extended Kalman filter (EKF) via fusing sensor data is used to estimate the robot’s CoM motion, in addition, an inverse kinematics (IK) controller is implemented which regulates the CoM position state in real time based on position tracking errors. On a slope with given angle, walking uphill and downhill experiments are conducted. The experimental results show that for the NAO humanoid robot, the deviation of walking direction can be controlled within 2 cm, so that it can keep walking stability for a long distance.
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Acknowledgment
This work is supported by Foshan Science and Technology Project (FSTP) of China (2015AG10019) and it is also supported by Characteristic Innovation Project of Guangdong College (2015KTSCX149).
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Yuan, Q., Xi, Z., Lu, Q., Lin, Z. (2017). Method and Experiment of the NAO Humanoid Robot Walking on a Slope Based on CoM Motion Estimation and Control. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10464. Springer, Cham. https://doi.org/10.1007/978-3-319-65298-6_15
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DOI: https://doi.org/10.1007/978-3-319-65298-6_15
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