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Hybrid Conflict-Driven Optimization for Multi-Robot Collaborative Transport Path Planning

Year: 2025

Type: conference-paper

Abstract: Aiming at the problems of path conflicts and efficiency optimization in multi-robot collaborative transportation in warehouse logistics, this paper proposes a Hybrid Conflict-Driven Optimization (HCDO) algorithm. This method combines Conflict-Based Search (CBS) with Integer Linear Programming (ILP), and introduces a mathematical optimization acceleration strategy in hierarchical conflict resolution. Simulation experiments show that compared with traditional CBS and Random Priority Scheduling (RPP), HCDO reduces the task completion time by 25.7% and improves the computational efficiency by 53.3% in a 20-robot scenario. The algorithm also exhibits good robustness in dynamic environments, with the number of conflicts reduced by 83.3% compared to RPP.

Source: International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC)

DOI: 10.1145/3745533.3745568

Authors: Lianhua Hu, Xiaofeng Yang

Institutions: Shenyang Urban Construction University, Shenyang Institute of Science and Technology

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W4413601725

FWCI:

Cites: 5

Cited by:

Related to: 10