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The trajectory planning method for industrial robot work operation based on spline interpolation algorithm

Juchen Li & Dongsheng Ma

International Journal of Product Development2025https://doi.org/10.1504/ijpd.2025.149690article
AJG 1
Weight
0.50

What the paper says

To shorten industrial robots' trajectory running time and reduce operating errors, a spline interpolation algorithm-based method for industrial robot work trajectory planning is proposed. First, a trajectory planning function for industrial robots is constructed using B-spline curves. Second, based on the curvature extremum point segmentation B-spline, independent S-shaped velocity planning is performed. The Simpson integration method calculates the curve length and determines the time span. Then, the S-shaped speed planning strategy implements independent speed configuration for segmented trajectories of industrial robots, achieving smooth transition speed control. Finally, the Cartesian coordinates of the interpolation points for the industrial robot's trajectory are calculated to complete the running trajectory planning. Test results show the proposed method can shorten trajectory running time to within 2 seconds and reduce trajectory error to within 0.3 cm.

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https://doi.org/https://doi.org/10.1504/ijpd.2025.149690

Or copy a formatted citation

@article{juchen2025,
  title        = {{The trajectory planning method for industrial robot work operation based on spline interpolation algorithm}},
  author       = {Juchen Li & Dongsheng Ma},
  journal      = {International Journal of Product Development},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijpd.2025.149690},
}

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The trajectory planning method for industrial robot work operation based on spline interpolation algorithm

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.