A 6R industrial robot structure parameter optimization method

By introducing average dexterity and energy consumption indicators into the design of industrial robots, the structural parameters of the 6R industrial robot are optimized, solving the problem of insufficient flexibility and dynamic performance of robotic arms in existing technologies, and achieving the effect of compact structure, high flexibility and low energy consumption.

CN117182968BActive Publication Date: 2026-07-21ZHEJIANG JINHUA JINCHUANG INTELLIGENT MFG RES INST CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG JINHUA JINCHUANG INTELLIGENT MFG RES INST CO LTD
Filing Date
2023-09-27
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

In the current industrial robot design process, only the workspace and kinematic performance are considered, failing to guarantee the flexibility and dynamic performance of the robotic arm. Moreover, the kinematic and dynamic performance may not be optimal in a single task scenario, and energy consumption is not fully optimized.

Method used

A 6R industrial robot structural parameter optimization method is adopted. Under given workspace constraints, the structural parameters of the robotic arm are optimized by combining average flexibility and energy consumption indicators, and a genetic algorithm is used to optimize the structural parameters, ensuring that the structure is compact, highly flexible and low in energy consumption.

Benefits of technology

This technology enables industrial robots that meet workspace constraints while having a more compact structure, higher flexibility, and lower energy consumption, making them suitable for single-task applications.

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Abstract

The application discloses a 6R industrial robot structure parameter optimization method, N working points are randomly generated in a given working space; path planning is carried out according to a starting point, the working points and the cycle of the starting point, and working tracks are determined; the size parameter range is determined under the condition of meeting the constraint condition, and the mechanical arm structure parameters are initialized; the performance indexes of each individual are calculated according to the given initialization population; the individuals in the population are evaluated according to the finally given structure parameter optimization evaluation function, and the individuals are selected to carry out population evolution operation; the working space index under the given working space is used to ensure that the optimized robot working space can cover the given working space, so that the robot structure size is as compact as possible; the average flexibility index under the working track is used to make the structure as compact as possible and the operability of the robot better, and the energy consumption index under the working track is used to optimize the energy consumption in the operation process.
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