首页 /研究 /Swarm and Multi-agent Time-based A* Path Planning for Lighter-Than-Air Systems
SWARM

Swarm and Multi-agent Time-based A* Path Planning for Lighter-Than-Air Systems

Jason Gibson, Tristan Schuler, Loy McGuire, Daniel M. Lofaro, Donald Sofge

发表年份
2020
引用次数
26

摘要

This work develops and implements a multi-agent time-based path-planning method using A*. The purpose of this work is to create methods in which multi-agent systems can coordinate actions and complete them at the same time. We utilized A* with constraints defined by a dynamic model of each agent. The model for each agent is updated during each time step and the resulting control is determined. This results in a translational path that each of the agents is physically capable of completing in synchrony. The resulting path is given to the agents as a sequence of waypoints. Periodic updates of the path are calculated, utilizing real-world position and velocity information, as the agents complete the task to account for external disturbances. Our methodology is tested in a dynamic simulation environment as well as on real-world lighter-than-air robotic agents.

关键词

Path (computing)Motion planningComputer sciencePosition (finance)Multi-agent systemSwarm behaviourSequence (biology)Task (project management)Work (physics)Robot

相关论文

查看 SWARM 分类全部论文