Robot Swarm Control Based on Smoothed Particle Hydrodynamics for Obstacle-Unaware Navigation

TL;DR

This paper presents a novel robot swarm control method using smoothed particle hydrodynamics to enable obstacle-unaware navigation by predicting collisions from velocity data, improving robustness and efficiency.

Contribution

Introduces an indirect obstacle detection approach with SPH for robot swarms, allowing navigation without explicit obstacle sensing, a novel solution for obstacle-unaware environments.

Findings

Enhanced navigation accuracy in obstacle-rich environments

Improved pattern formation robustness

Quantitative validation shows superior performance

Abstract

Robot swarms hold immense potential for performing complex tasks far beyond the capabilities of individual robots. However, the challenge in unleashing this potential is the robots' limited sensory capabilities, which hinder their ability to detect and adapt to unknown obstacles in real-time. To overcome this limitation, we introduce a novel robot swarm control method with an indirect obstacle detector using a smoothed particle hydrodynamics (SPH) model. The indirect obstacle detector can predict the collision with an obstacle and its collision point solely from the robot's velocity information. This approach enables the swarm to effectively and accurately navigate environments without the need for explicit obstacle detection, significantly enhancing their operational robustness and efficiency. Our method's superiority is quantitatively validated through a comparative analysis, showcasing its significant navigation and pattern formation improvements under obstacle-unaware conditions.