Two Formal Gas Models for Multi-agent Sweeping and Obstacle Avoidance

Abstract

Abstract. The task addressed here is a dynamic search through a bounded region, while avoiding multiple large obstacles, such as buildings. In the case of limited sensors and communication, maintaining spatial coverage -especially after passing the obstacles -is a challenging problem. Here, we investigate two physics-based approaches to solving this task with multiple simulated mobile robots, one based on artificial forces and the other based on the kinetic theory of gases. The desired behavior is achieved with both methods, and a comparison is made between them. Because both approaches are physics-based, formal assurances about the multi-robot behavior are straightforward, and are included in the paper.

Edge Detection in Static and Dynamic Environments using Robot Swarms

“…For coping with this challenge, we applied the well-known mechanism of gas diffusion for spreading the robots across the environment during their motion. This mechanism facilities a better exploration with a maximized coverage [18]. We allow robots to start their task from a uniform spatial distribution.…”

Distributed Control of Multi-Robot Deployment Motion

“…Winfield presented a distributed method that deploys a group of mobile robots into a physically bounded region by random diffusion (Winfield, 2000). Kerr et al presented two physics-based approaches for multi-robot dynamic search through a bounded region while avoiding multiple large obstacles, one based on artificial forces, and the other based on the kinetic theory of gases (Kerr et al, 2005). By mimicking gas flow, the agents will be able to distribute themselves throughout the volume and navigate around the obstacles.…”

A Novel Deployment Algorithm Based on Fluid Dynamics Approach

“…A fluid dynamics approach for multi-robot chemical plume tracing is addressed in [10], where flow variables of a 'real' fluid are measured by a computational sensor grid and the flow direction is estimated for backward tracing. Another work [11] proposes two gas models, one of which uses a virtual force approach and the other uses akinetic approach. But the most relevant paper [12,13] was provided by MR Pac and AM Erkmen, in which they made a fluid dynamics model for mobile sensor networks, while networks are viewed as fluid body, and nodes as particles in fluid.…”