Dispersion and Line Formation in Artificial Swarm Intelligence
This work addresses the need for efficient coordination in swarm robotics for tasks like sensing, exploration, and surveillance, but it is incremental as it builds on existing virtual spring damper models.
The paper tackles the problem of shape formation in artificial swarm systems by developing a dynamic model based on a virtual spring damper and algorithms for dispersion and line formation using only neighbor distance estimation, resulting in methods that enable leaderless dispersion and leader-based line formation.
One of the major motifs in collective or swarm intelligence is that, even though individuals follow simple rules, the resulting global behavior can be complex and intelligent. In artificial swarm systems, such as swarm robots, the goal is to use systems that are as simple and cheap as possible, deploy many of them, and coordinate them to conduct complex tasks that each individual cannot accomplish. Shape formation in artificial intelligence systems is usually required for specific task-oriented performance, including 1) forming sensing grids, 2) exploring and mapping in space, underwater, or hazardous environments, and 3) forming a barricade for surveillance or protecting an area or a person. This paper presents a dynamic model of an artificial swarm system based on a virtual spring damper model and algorithms for dispersion without a leader and line formation with an interim leader using only the distance estimation among the neighbors.