Conflict-based strategy combined integrated optimal conflict avoidance algorithm

This paper presents a Conflict-Based Strategy - Combined Integrated Optimal Conflict Avoidance (CBS-CIOCA) algorithm for more efficient multi-robot path planning. The algorithm first refines the conflict types in the high-level model of the traditional CBS algorithm and introduces two conflict categories: avoidable conflicts and unavoidable conflicts. Next, the low-level model of the traditional CBS algorithm is improved, transforming the path search process into two distinct algorithms with different focuses. Finally, based on the different conflict categories, two optimized algorithms are proposed: a space-time A* algorithm enhanced by diagonal improvements and a dynamic adaptive space-time A* algorithm incorporating dynamic adaptive factors. Experimental results demonstrate that, compared to the traditional CBS algorithm, the CBS-CIOCA algorithm achieves maximum reductions of 97.37% and 94.99% in time and node expansion, respectively, in both traditional warehouse and fishbone-shaped warehouse environments, as well as 88.37% and 88.41% in a dynamic large-obstacle environment.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-02-15
DOI
https://doi.org/10.1038/s41598-025-89549-1
Citations
3
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
3.83
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Conflict-based strategy combined integrated optimal conflict avoidance algorithm

Hongwei Wen, Kejin Jia, Zhe Zhang, Yun Du et al.
3 citations
Scientific Reports
Robotic Path Planning Algorithms
3.83
article

Conflict-based strategy combined integrated optimal conflict avoidance algorithm

Hongwei Wen, Kejin Jia, Zhe Zhang, Yun Du, Cheng Peng, Yufei Gao
article en
3 citations

Abstract

This paper presents a Conflict-Based Strategy - Combined Integrated Optimal Conflict Avoidance (CBS-CIOCA) algorithm for more efficient multi-robot path planning. The algorithm first refines the conflict types in the high-level model of the traditional CBS algorithm and introduces two conflict categories: avoidable conflicts and unavoidable conflicts. Next, the low-level model of the traditional CBS algorithm is improved, transforming the path search process into two distinct algorithms with different focuses. Finally, based on the different conflict categories, two optimized algorithms are proposed: a space-time A* algorithm enhanced by diagonal improvements and a dynamic adaptive space-time A* algorithm incorporating dynamic adaptive factors. Experimental results demonstrate that, compared to the traditional CBS algorithm, the CBS-CIOCA algorithm achieves maximum reductions of 97.37% and 94.99% in time and node expansion, respectively, in both traditional warehouse and fishbone-shaped warehouse environments, as well as 88.37% and 88.41% in a dynamic large-obstacle environment.

Scientific ReportsVol. 15(1)
Hebei University of Science and Technology (CN)
Openalex Percentile: Top 8%
Robotic Path Planning Algorithms
3.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Conflict-based strategy combined integrated optimal conflict avoidance algorithm — Hongwei Wen, Kejin Jia, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS