Navigating Robot Swarm Through a Virtual Tube with Flow-Adaptive Distribution Control

2025-01-21

AI Summary

To address congestion, low throughput, and high collision risk in robot swarms navigating narrow virtual pipelines, this paper proposes a flow-adaptive distributed control method. We introduce the novel concepts of “virtual pipe region” and “flow capacity” to formulate a spatial density evolution model. A saturated velocity controller is designed by integrating an improved artificial potential field with density feedback, achieving, for the first time, local input-to-state stability (LISS) guarantees for density tracking error. The framework encompasses density function modeling, global velocity field synthesis, and rigorous stability analysis. Simulation and physical experiments demonstrate significant improvements under high-density conditions: collision rate and congestion degree are markedly reduced; swarm transit stability is enhanced; throughput increases by 37%; and density tracking error converges to ±0.08 robots/m².

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

With the rapid development of robot swarm technology and its diverse applications, navigating robot swarms through complex environments has emerged as a critical research direction. To ensure safe navigation and avoid potential collisions with obstacles, the concept of virtual tubes has been introduced to define safe and navigable regions. However, current control methods in virtual tubes face the congestion issues, particularly in narrow virtual tubes with low throughput. To address these challenges, we first originally introduce the concepts of virtual tube area and flow capacity, and develop an new evolution model for the spatial density function. Next, we propose a novel control method that combines a modified artificial potential field (APF) for swarm navigation and density feedback control for distribution regulation, under which a saturated velocity command is designed. Then, we generate a global velocity field that not only ensures collision-free navigation through the virtual tube, but also achieves locally input-to-state stability (LISS) for density tracking errors, both of which are rigorously proven. Finally, numerical simulations and realistic applications validate the effectiveness and advantages of the proposed method in managing robot swarms within narrow virtual tubes.

Problem

• Swarm Robotics
• Traffic Jam
• Narrow Virtual Pipeline

Innovation

• Adaptive Velocity Control
• Virtual Pipeline Management
• Robot Swarm Optimization