Swarm algorithm development for automated warehouse solutions

自动化仓库解决方案的群体算法开发

• 批准号: 2108858
• 金额: --
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2108858
• 关键词: Swarm; algorithm; development; automated; warehouse

There has been plenty of research about swarm robotics that shows how useful swarm algorithms can solve complex problems using simple rules, decentralised control and a group of robots. However, there has been a lack of research into transitioning swarming systems out of the laboratory. Many possible real-world application areas have been suggested such as search and rescue [1], construction [2] or space exploration [3]. Closing the reality gap will require novel implementation methods including human-swarm interaction and consideration of how users think of swarms. This project aims to remove the need for complex pre-existing infrastructure or programming in warehouses with automated storage and retrieval systems (AS/RS). Without these expensive and complicated features, an AS/RS could be implemented in areas where it is currently unavailable such as SMEs, charitable donations storage or high street shops. These are typically limited in space and have large fluctuations in demand making the stock difficult to manipulate and organise efficiently. They also have a limited workforce available for stock sorting which means their systems can be inefficient, slow and inaccurate. Swarm robotics can: scale up and down to different spaces; adapt to changing tasks; and be robust against single agent failures. The swarm can do this without any specific pre-programming or interference from human helpers during the task. A swarm warehouse is also a potentially cheaper solution than a classic AS/RS because the individual agents are less complex in both programming and technology (as long as it is balanced with the hardware cost of having multiple robots). With these advantages, a swarm AS/RS has the potential to perform similar tasks to the ones that are currently implemented to improve efficiency in automated warehouses but need less dedicated control and infrastructure. This is expected to increase the application areas for the technology where the workforce is limited but there is a large difference in stock room types, tasks and sizes.The work for this project will mainly be focused on developing and designing algorithms for a swarm warehouse AS/RS. This will be informed by interviews with potential users of the technology which will include an investigation into public opinion of swarms in the workplace. The final part of the project will be physical testing of the swarming algorithms, using the Toshiba swarm test-bed. A successful algorithm will do the same or better performance than a centralised system with global information at the storage and retrieval tasks described.

有大量关于群体机器人的研究表明，群体算法可以使用简单的规则、分散的控制和一组机器人来解决复杂的问题。然而，缺乏对实验室外过渡群体系统的研究。提出了许多可能的实际应用领域，如搜索和救援[1]，建筑[2]或空间探索[3]。缩小现实差距需要新颖的实现方法，包括人群交互和考虑用户如何看待群体。该项目旨在消除对具有自动存储和检索系统（AS/RS）的仓库中复杂的预先存在的基础设施或编程的需求。如果没有这些昂贵和复杂的功能，AS/RS可以在目前无法使用的领域实施，例如中小企业，慈善捐赠存储或高街商店。这些仓库通常空间有限，需求波动很大，使库存难以有效操纵和组织。他们的库存分拣人员也有限，这意味着他们的系统可能效率低下、速度缓慢且不准确。蜂群机器人可以：扩大和缩小到不同的空间；适应不断变化的任务；并对单个代理的失败保持健壮。蜂群可以做到这一点，而不需要任何特定的预编程，也不需要在任务过程中受到人类助手的干扰。群仓库也是一种潜在的比经典AS/RS更便宜的解决方案，因为单个代理在编程和技术方面都不那么复杂（只要它与拥有多个机器人的硬件成本相平衡）。有了这些优势，集群AS/RS有潜力执行与目前实现的自动化仓库类似的任务，以提高效率，但需要更少的专用控制和基础设施。预计这将增加该技术的应用领域，这些领域的劳动力有限，但在库房类型、任务和规模方面存在很大差异。本项目的工作将主要集中在开发和设计集群仓库AS/RS的算法上。这将通过与该技术的潜在用户的访谈来了解，其中将包括对工作场所蜂群的公众舆论的调查。该项目的最后一部分将是使用东芝蜂群试验台对蜂群算法进行物理测试。在存储和检索任务中，一个成功的算法将比具有全局信息的集中式系统具有相同或更好的性能。