无需基站和控制指令，用测距实现多机器人协同定位。
An Infrastructure-less, Control-Independent Solution to Relative Localisation of a Team of Mobile Robots using Ranging Measurements
- 基于多假设贝叶斯框架，仅依赖本地里程计和稀疏测距。
- 无需控制机器人运动即可保证团队可观测性，定位稳定可靠。
- 适合快速部署的野外机器人团队，尤其适用于通信受限场景。
多机器人协同定位在非结构化环境中的机器人集群、协作控制与导航任务中至关重要。在缺乏固定基础设施、部署需快速灵活且系统开销小的前提下，本文提出一种去中心化协同定位算法，完全无需参考锚点，也不依赖控制机器人运动来保证可观测性。该方法仅利用本地里程计、稀疏的异构间测距数据以及短距离通信，这些均在实际中广泛可用。算法采用多假设贝叶斯框架，维护所有可行解集合，在瞬时不可观测条件下仍具鲁棒性；通过信息共享，每个代理即使在部分连接状态下也能受益于全队估计。实验验证了其在动态和受限通信环境下的有效性。
原文摘要 · Abstract (English)
The ability to localise teams of robots is essential for applications ranging from robotic fleets in unstructured environments to cooperative control and navigation tasks. In such contexts, fixed infrastructure is often unavailable, deployments must be fast and flexible, and system requirements must be minimal. We present a decentralised cooperative localisation algorithm that addresses all these challenges at once. The method is anchor-less, fully decentralised, and, unlike most existing approaches, does not require controlling the robots motion to ensure team observability. It relies only on local odometry, sparse inter-agent ranging measurements, and short-range communication, all of which are widely available in practice. The algorithm adopts a multi-hypothesis Bayesian framework that maintains the entire set of feasible solutions, ensuring robustness under transient unobservable conditions. Moreover, through information sharing, each agent benefits from the estimates of the entire group, even in partially connected conditions.
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