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Human body motion capture data-based humanoid robot gait planning method

A humanoid robot and human motion technology, applied in the field of intelligent robots, can solve problems such as large amount of calculation and inability to calculate in real time

Inactive Publication Date: 2017-07-07
BEIJING UNIV OF TECH
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Problems solved by technology

Since this method needs to establish a high-precision humanoid robot kinematics and dynamics model, it often brings a large amount of calculation and cannot be calculated in real time, especially in the case of complex models, and even unsolvable situations

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  • Human body motion capture data-based humanoid robot gait planning method
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  • Human body motion capture data-based humanoid robot gait planning method

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Embodiment Construction

[0050] The method will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0051] Since this method is to apply the human body motion data to the humanoid robot, the reliability of the data is particularly important. It is recommended to use well-known motion capture databases at home and abroad, such as the motion capture database of the Carnegie Mellon University Motion Laboratory, KIT human motion database, HDM05 motion database, etc. The motion capture data format provided by these databases is usually .bvh or .amc combined with .asf data format. The .bvh file is the combination of the data file .amc and the skeleton file .asf, which contains the information of both, and the provided skeleton structure conforms to figure 2 The topology shown. The .amc file defines the Euler angle (XYZ) of each frame of the "child joint" local coordinate system corresponding to the .asf file relative to the "parent joint" local coordinate ...

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Abstract

The invention relates to a human body motion capture data-based humanoid robot gait planning method. The method includes the following steps that: human body gait modes are extracted, angle curves of the six degrees of freedom of a single leg are obtained, wherein the human body gait modes include hip joint roll, hip joint pitch, hip joint yaw, knee joint pitch, ankle joint pitch and ankle joint roll; format conversion and mathematical optimization are performed on the human body gait mode data, so that the data can be applied to a human simulating robot; and a ZMP control algorithm is introduced to finely adjust the joint angles of a humanoid robot to improve the robustness of the humanoid robot. With the human body motion capture data-based humanoid robot gait planning method of the invention adopted, the gait planning difficulty of the humanoid robot can be simplified, the humanoid property and stability of the gait of the humanoid robot can be improved, and a foundation can be provided for the complex action planning of the humanoid robot. Compared with a traditional humanoid robot gait planning method, the human body motion capture data-based humanoid robot gait planning method has outstanding advantages and has a bright prospect.

Description

technical field [0001] The invention belongs to the field of intelligent robots, and the main content is to apply the gait pattern of the human body to the humanoid robot based on the motion capture data of the human body, so as to realize the stable walking of the humanoid robot. Background technique [0002] At present, the research on humanoid robots has been more and more sought after, and various countries have invested a considerable amount of manpower and material resources in research. One of the research focuses of humanoid robots in various countries is how to realize the stable walking of humanoid robots. The pros and cons of humanoid robot gait walking can reflect the research level of humanoid robot to a certain extent. [0003] At present, many humanoid robot gait planning methods can be roughly divided into the following categories: [0004] ① Gait planning method based on simplified model. The main idea of ​​this method is to ignore some physical character...

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 龚道雄邵杰李赟程
Owner BEIJING UNIV OF TECH
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