FlowPlanner

Welcome to the FlowPlanner repository!

Han Liu, Yu Jin, Mingyue Cui, Boyang Li, Tianjiang Hu; Kai Huang, "From Edge to Edge: A Flow-Inspired Scheduling Planner for Multi-Robot Systems”, IEEE Transactions on Automation Science and Engineering (T-ASE), 2026.

[IEEE Xplore] [arxiv] [BiliBili]

📜 Introduction

Trajectory planning is crucial in multi-robot systems, particularly in environments with numerous obstacles. While extensive research has been conducted in this field, the challenge of coordinating multiple robots to flow collectively from one side of the map to the other—such as in crossing missions through obstacle-rich spaces—has received limited attention. This paper focuses on this directional traversal scenario by introducing a real-time scheduling scheme that enables multi-robot systems to move from edge to edge, emulating the smooth and efficient flow of water. Inspired by network flow optimization, our scheme decomposes the environment into a flow-based network structure, enabling the efficient allocation of robots to paths based on real-time congestion levels. The proposed scheduling planner operates on top of existing collision avoidance algorithms, aiming to minimize overall traversal time by balancing detours and waiting times. Simulation results demonstrate the effectiveness of the proposed scheme in achieving fast and coordinated traversal. Furthermore, real-world flight tests with ten drones validate its practical feasibility. This work contributes a flow-inspired, real-time scheduling planner tailored for directional multi-robot traversal in complex, obstacle-rich environments.

System overview

📍Demos

test_flow_f-94.8_batch.mp4

test_flow_clutter.119.1.2.mp4

🛠️ Quick start

Requirements

• Gurobi Install Gurobi Optimizer

• json, itertools, matplotlib, numpy, networkx,...

Run the script directly.

git clone https://github.com/chengji253/FlowPlanner
cd FlowPlanner/main_code
python3 Simu_ORCA_flow.py

⚓ ORCA Python Environment

We provide a clean ORCA Python environment that you can use as a foundation to build your own planner.

https://github.com/chengji253/RVO2-python

We would like to thank the authors of the RVO2 Library.