Behavior tree for autonomous drones in smart manufacturing

智能制造中自主无人机的行为树

• 批准号: 2867698
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2867698
• 关键词: Behavior; tree; autonomous; drones; smart

Unmanned aerial vehicles (UAV) have been successfully applied to many outdoor tasks: surveillance, security, transportation, entertainment, etc. for a long time commercially and scientifically. Recently, the focus of UAVs operating inside warehouses has increased in both academia and industry. With the coming smart automation trend, drones will play the same role as autonomous mobile platforms, manipulators in improving operational productivity in factories. UAVs utilize the aerial space to perform the necessary tasks, such as monitoring, inventory management, inspection and maintenance, to maximize the plant's productivity.There are 3 main research challenges for development and deployment of UAVs in smart factories: (1) The autonomous operation of a a multiple UAV system in an information-rich network environment; (2) The safeness of the UAVs system with respect to people and incidents; (3) The optimization of the efficiency of the UAVs system. The drones should be able to change the operating mode according to real situations and handle them quickly. When operating in a smart factory, the amount of information exchanged between systems is rapidly enhanced. Taking advantage of this makes multi-UAV systems suitable for solving these problems. To accelerate the development of an autonomous multi-drone system in smart factory environments maximising productivity, this research aims to develop a planning tool for autonomous systems of unmanned aerial vehicles based on the behavior tree framework. The proposed research will contribute to the topic of drone system control in a smart factory environment. In this environment, the amount of information is exchanged quickly. This creates certain advantages as well as disadvantages that need to be taken into account when putting the drone system into operation. The study focuses on solving 3 specific problems and will have the following expected scientific contributions: (1) A planning framework for a system of agents (drones and servers) to perform tasks in an autonomous manner; (2) Extending and applying safety elements to the planning tool for a multi-agents system and (3) Developing safety and autonomy-based reinforcement learning for the planning framework.This project is strongly aligned with Warwick's Global Research Priorities on Innovative Manufacturing and Future Materials (especially Industry 4.0) and the sustainable development strategies in WMG, including Digital Technologies, Materials and Manufacturing, and Energy. This fits well within the research themes led by the supervisors, consequently, will boost their leadership in the fields.

无人机（Unmanned Aerial Vehicles，UAV）在商业和科学上已经成功地应用于许多户外任务：监视、安全、运输、娱乐等。最近，无人机在仓库内操作的焦点在学术界和工业界都有所增加。随着智能自动化趋势的到来，无人机将在提高工厂运营生产力方面发挥与自主移动的平台、机械手相同的作用。无人机利用空中空间执行必要的任务，如监控、库存管理、检查和维护，以最大限度地提高工厂的生产率。智能工厂中无人机的开发和部署面临3个主要研究挑战：（1）在信息丰富的网络环境中多无人机系统的自主操作;（2）无人机系统对人员和事件的安全性;（3）无人机系统效率的优化。无人机应能根据真实的情况改变运行模式，并迅速处理。当在智能工厂中运行时，系统之间交换的信息量迅速增加。利用这一点使得多无人机系统适合解决这些问题。为了加速智能工厂环境中自主多无人机系统的开发，最大限度地提高生产力，本研究旨在开发一种基于行为树框架的无人机自主系统规划工具。拟议的研究将有助于智能工厂环境中的无人机系统控制主题。在这种环境下，信息量迅速交换。这产生了某些优点以及在将无人机系统投入运行时需要考虑的缺点。本研究主要解决三个具体问题，并将有以下预期的科学贡献：（1）一个代理系统的规划框架（无人机和服务器）以自主方式执行任务;（2）将安全元素扩展并应用于多代理系统的规划工具;（3）开发安全性和自主性-基于强化学习的规划框架。该项目与沃里克的创新制造和未来材料全球研究重点密切相关（特别是工业4.0）和WMG的可持续发展战略，包括数字技术，材料和制造以及能源。这与主管领导的研究主题非常吻合，因此，将提高他们在该领域的领导地位。