Towards Large-Scale Scalable MAV Swarms with ROS2 and UWB-based Situated Communication

Queralta, Jorge Peña; Yu, Xianjia; Li, Qingqing; Westerlund, Tomi

doi:10.48550/arxiv.2104.09274

Cited by 1 publication

(1 citation statement)

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“…Scalability can be considered a key parameter when a system is deployed in larger areas or for a large number of nodes [13], [29]. When talking about real time systems the rate of update in the nodes is very important, but the number of nodes in the system will limit the frequency of communication [30].…”

Section: A Tof and Tdoamentioning

confidence: 99%

Towards Large-Scale Relative Localization in Multi-Robot Systems with Dynamic UWB Role Allocation

Morón¹,

Queralta²,

Westerlund³

2022

Preprint

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Ultra-wideband (UWB) ranging has emerged as a key radio technology for robot positioning and relative localization in multi-robot systems. Multiple works are now advancing towards more scalable systems, but challenges still remain. This paper proposes a novel approach to relative localization in multirobot systems where the roles of the UWB nodes are dynamically allocated between active nodes (using time-of-flight for ranging estimation to other active nodes) and passive nodes (using timedifference-of-arrival for estimating range differences with respect to pairs of active nodes). We adaptively update UWB roles based on the location of the robots with respect to the convex envelope defined by active nodes, and introducing constraints in the form of localization frequency and accuracy requirements. We demonstrate the applicability of the proposed approach and show that the localization errors remain comparable to fixed-role systems. Then, we show how the navigation of an autonomous drone is affected by the changes in the localization system, obtaining significantly better trajectory tracking accuracy than when relying in passive localization only. Our results pave the way for UWB-based localization in large-scale multi-robot deployments, for either relative positioning or for applications in GNSS-denied environments.

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Section: A Tof and Tdoamentioning

confidence: 99%