用微型机器人集群绕障碍物搬运物体，靠遮挡机制建链式导航。
Occlusion-Based Object Transportation Around Obstacles With a Swarm of Miniature Robots
- 通过建立子目标链，让机器人在无视线时仍能导航
- 大规模集群可绕过凹凸障碍完成搬运任务
- 完全去中心化且无需通信，适合实际部署
群体机器人利用去中心化的自组织系统，从底层个体的有限能力中构建复杂集体行为。以往研究显示，基于遮挡的简单策略可在无遮挡条件下有效实现物体向目标位置的运输。但该策略要求物体与目标之间必须保持清晰视野。本文提出扩展该策略，允许机器人形成子目标，使任意成员均可扩大对目标的可见范围，最终在物体与目标间构成一条子目标链。新方法保持原始策略的完全去中心化和无通信特性，并在无物体场景中维持性能。在五组模拟实验中，我们验证了所提策略的泛化能力：足够规模的集群可在障碍物阻挡目标时完成运输任务，对不同起始位置具有鲁棒性，且能处理凹形与凸形障碍。
原文摘要 · Abstract (English)
Swarm robotics utilises decentralised self-organising systems to form complex collective behaviours built from the bottom-up using individuals that have limited capabilities. Previous work has shown that simple occlusion-based strategies can be effective in using swarm robotics for the task of transporting objects to a goal position. However, this strategy requires a clear line-of-sight between the object and the goal. In this paper, we extend this strategy by allowing robots to form sub-goals; enabling any member of the swarm to establish a wider range of visibility of the goal, ultimately forming a chain of sub-goals between the object and the goal position. We do so while preserving the fully decentralised and communication-free nature of the original strategy, while maintaining performance in object-free scenarios. In five sets of simulated experiments, we demonstrate the generalisability of our proposed strategy. Our finite-state machine allows a sufficiently large swarm to transport objects around obstacles that block the goal. The method is robust to varying starting positions and can handle both concave and convex shapes.
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