A modular robotic trajectory optimization method

By using a modular robot trajectory optimization method and the Grey Wolf optimization algorithm to optimize the joint trajectory of the modular robot, the problem of existing robots being unable to adapt to complex tasks is solved, the task completion rate and resource utilization efficiency are improved, and the module lifespan is extended.

CN119458360BActive Publication Date: 2026-06-02BEIJING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING UNIV OF POSTS & TELECOMM
Filing Date
2024-12-12
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing space robots, due to their fixed connections, joint arrangements, and degrees of freedom, struggle to adapt to complex and diverse on-orbit tasks, resulting in a limited range of trajectory optimization performance adjustments that affect operation time and accuracy.

Method used

A modular robot trajectory optimization method is adopted. Through the Grey Wolf optimization algorithm framework, a modular robot motion distribution vector encoding is designed, a trajectory optimization model is established, and the joint trajectory is optimized to adapt to different task requirements.

Benefits of technology

Modular robot trajectory optimization was achieved, making it suitable for diverse task environments, improving resource utilization efficiency, enhancing robot reliability and task completion, and extending module lifespan.

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Abstract

The embodiment of the application provides a modular robot trajectory optimization method, realizes joint trajectory optimization of a modular robot, and comprises the following steps: obtaining a modular robot kinematic chain matrix and a desired end motion trajectory of the modular robot; obtaining a current motion degree of freedom number of the modular robot according to the modular robot kinematic chain matrix; obtaining a motion distribution vector of the modular robot according to the current motion degree of freedom number of the modular robot; designing a modular robot trajectory optimization method according to the desired end motion trajectory of the modular robot and the motion distribution vector of the modular robot; and obtaining an optimal joint trajectory of the modular robot by encoding the motion distribution vector of the modular robot based on a grey wolf optimization algorithm framework. According to the technical scheme provided by the embodiment of the application, joint trajectory optimization with small end trajectory error, small total motion energy consumption and balanced energy consumption among modules of the modular robot can be realized.
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