A Clustering Approach to Path Planning for Big Groups

Abstract

The article introduces a new method of planning paths for big groups in dynamic environments represented by a graph of vertices and edges, where the edge weight as well as the graph topology may change, but the method is also applicable to environments with a different representation. The utilization of clustering enables the use of a computed path for a group of agents. In this way, a speed-up and memory savings are achieved at a cost of some path sub-optimality. Examples of proper applications of the suggested approach are crowd simulation in urban environments or path-planning-based tasks in molecular biology. The experiments showed good behaviour of the method to speed-up, relative error and online computation.