Geometric Task Decomposition in a Multi-Agent Environment

Abstract

Task decomposition in a multi-agent environment is often performed online. This paper proposes a method for subtask allocation that can be performed before the agents are deployed, reducing the need for communication among agents during their mission. The proposed method uses a Voronoi diagram to partition the task-space among team members and includes two phases: static and dynamic. Static decomposition (performed in simulation before the start of the mission) repeatedly partitions the task-space by generating random diagrams and measuring the efficacy of the corresponding subtask allocation. If necessary, dynamic decomposition (performed in simulation after the start of a mission) modifies the result of a static decomposition (i.e. in case of resource limitations for some agents). Empirical results are reported for the problem of surveillance of an arbitrary region by a team of agents. 1 Introduction Multiagent teamwork is an active area of research and task decomposition among team members remains a challenge in multiagent environments. Some of the previous methods proposed for teamwork and task decomposition require periodic negotiations among team members (

Multi-robot dispatching in a geographically constrained environment

“…In a region-based scheme, a robot supervises its designated area, such as a Voronoi region [5]. In a task-based scheme, each task is bid by the robot with the minimum cost, such as the market-like approach mentioned in [6], the neural network approach by [7], and the use of Hungarian algorithm in [8].…”