Posture migration algorithm framework applicable to multi-degree-of-freedom robot

A multi-legged robot, robot technology, applied in the field of robotics, can solve problems such as insufficient consideration

Active Publication Date: 2020-04-10
XIAMEN UNIV
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Problems solved by technology

[0004] However, when the existing population-based optimization methods solve the problem that the optimization function is constantly changing, that is, the so-called dynamic multi-objective optimization, they often use the method of re-initializing parameters or re-initializing the population. These strategies do not fully consider How to use pre-acquired knowledge to improve the quality and speed of pose generation in complex environments

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  • Posture migration algorithm framework applicable to multi-degree-of-freedom robot
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  • Posture migration algorithm framework applicable to multi-degree-of-freedom robot

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[0023] To further illustrate the various embodiments, the present invention is provided with accompanying drawings. These drawings are a part of the disclosure of the present invention, which are mainly used to illustrate the embodiments, and can be combined with related descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, those skilled in the art should understand other possible implementations and advantages of the present invention. Components in the figures are not drawn to scale, and similar component symbols are generally used to denote similar components.

[0024] The present invention will be further described in conjunction with the accompanying drawings and specific embodiments.

[0025] The invention discloses an algorithm frame of posture migration of a multi-degree-of-freedom robot. Among them, the pose optimization problem of a multi-DOF robot is a (dynamic) multi-objective optimization prob...

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Abstract

The invention discloses a posture migration algorithm framework applicable to a multi-degree-of-freedom robot, and relates to the field of robots. According to the attitude migration algorithm framework, attitude or action generation tasks of a robot in different environments are regarded as a multi-objective optimization problem; a robot posture (or action) obtained in a simple environment is used as a source domain; an attitude (or action) applicable to an unknown complex environment is used as a target domain; a high-quality initial population is generated by utilizing knowledge of the source domain during searching of an optimal solution of the target domain; thus, a robot attitude (or action) applicable to a complex environment is quickly generated by utilizing any population-based multi-target optimization algorithm. According to the invention, knowledge reuse can be carried out by using different transfer learning algorithms; and for any population-based multi-objective optimization algorithm, the algorithm framework provided by the invention can be effectively combined with the population-based multi-objective optimization algorithm without modification.

Description

technical field [0001] The invention relates to the field of robots, in particular to an attitude generation algorithm framework suitable for multi-degree-of-freedom robots to quickly adapt to complex environments. Background technique [0002] Pose optimization is an important topic in the field of robotics research. Existing methods mostly follow two strategies to obtain motion poses of multi-DOF robots. The first strategy is biologically inspired, and its research motivation lies in the fact that the movement patterns of humans and animals can skillfully combine many factors such as stability and environmental adaptability, and minimize energy consumption. Therefore, researchers hope to learn from the principles of human or animal motion posture formation and reproduce them on robots. However, due to the significant differences in kinematics and dynamics between humans and animals and robots, biological motion data cannot be directly applied to robots. [0003] The sec...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/15G06F17/16G06N3/00
CPCG06F17/15G06F17/16G06N3/006
Inventor 江敏徐姜琴郭诗辉
Owner XIAMEN UNIV
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