首页 /研究 /Multi-Robot Virtual Structure Switching and Formation Changing Strategy in an Unknown Occluded Environment
SWARM

Multi-Robot Virtual Structure Switching and Formation Changing Strategy in an Unknown Occluded Environment

Dibyendu Roy, Arijit Chowdhury, Madhubanti Maitra, Samar Bhattacharya

发表年份
2018
引用次数
24

摘要

This paper presents a switching strategy of a region-based shape controller for a swarm-robotic framework to overcome the traditional obstacle-avoidance problem in the virtual structure methodology. In this control approach, initially, the robots move as a group inside a circular region which we conceive to be the initial virtual structure, while preserving a specific pattern, say a triangular formation, among them. In order to avoid static/dynamic obstacles, while approaching towards the target without any prior knowledge about the environment, the virtual-circle is allowed to shrink up to a certain limit. The shrinking phenomena of the virtual circle will depend upon the number of agents within the circle and the distance between two the nearest obstacles sensed by the agents through which the swarm should be able to pass. If the situation demands, the structure may assume the shape of an ellipse of equivalent area continually throughout the path described by the swarm encapsulated within the variable structure. To achieve this, two-layer hierarchical control strategy has been proposed. Moreover, if the shape of the virtual structure changes, the formation of the swarm inside the region may also change. To make the inter-agent formation flexible inside the newly formed virtual structure, a spanning-tree-assisted-shape-matching algorithm has been employed for accommodating all the agents inside the virtual region which helps in the formation change in the agents as well. Finally, simulation results and stability analysis of the controllers are provided to demonstrate our proposed technique.

关键词

RobotComputer scienceHuman–computer interactionArtificial intelligenceComputer vision

相关论文

查看 SWARM 分类全部论文