| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 04012 | |
| Number of page(s) | 10 | |
| Section | Computer Vision, Robotic Systems, and Intelligent Control | |
| DOI | https://doi.org/10.1051/itmconf/20268404012 | |
| Published online | 06 April 2026 | |
Research Model on Motion Planning of Bench Dragon Based on Archimedean Spiral
1 School of Environmental and Municipal Engineering, Xi’an University of Architecture and Technology, Xi’an, China, 710055
2 School of Management, Xi’an University of Architecture and Technology, Xi’an, China, 710055
* Corresponding author’s email: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The bench dragon, a traditional folk activity in Zhejiang and Fujian, requires high team rhythm and section circling coordination. Optimizing the position, coordinate and speed of its front and rear sections is crucial to improving movement status and viewing effects. This study optimizes its trajectory based on the Archimedean spiral model: it digitally defines the trajectory via the spiral’s polar coordinate equation, obtains the dragon handle’s distance expression through arc length integration, and establishes a clockwise coiling position model with constant front-rear handle distance as a constraint 1. The handle’s relative position, coordinate objective function and speed equation (via differentiation) are derived, and instantaneous position/speed is solved by time-step algorithm. The Results show good fitting between calculated values and the spiral, verifying the model’s validity. The innovation lies in combining folk performance with spiral mathematical modeling for precise optimization, providing theoretical/practical support for optimal route selection.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

