Distributed Formation Estimation Via Pairwise Distance Measurements

Abstract

Continuously and reliably estimating the relative configuration of robotic swarms in real-time constitutes a core functionality when pursuing the autonomy of such a swarm. Relying on external positioning systems, such as GPS or motion tracking systems, can provide the required information, but significantly limits the generality of an approach. In this letter, we target formation estimation for autonomous flights of swarms of small UAVs, as they pose particularly challenging restrictions on onboard resources, while opening up a large variety of practical scenarios for a multi-robot setup. While state of the art has been addressing efficient formation estimation, scalability remains limited to only very few agents that can be handled in real-time, with the workload of each agent depending on the total number of agents in the swarm. Aiming for scalable multi-robot systems, here we propose a distributed formation estimation approach, where the computational load of each agent is decoupled from the swarm size. This approach is implemented in a setup with minimal communication effort, requiring only ego-motion estimates from each agent and pairwise distance measurements between them, constraining their configuration globally. Evaluations on swarms of up to 49 UAVs demonstrate the power of our approach to handle large swarms, while keeping the computational load bounded for individual agents and requiring only little data exchange between two robots.

Agile Formation Control of Drone Flocking Enhanced with Active Vision-based Relative Localization

“…External devices, such as GPS, motion capture system and UWB positioning system with anchors, are adopted to obtain absolute positions and deduce the relative positions between agents. The dependence on the external infrastructure of this approach restricts the deployment of the system to unknown environments [18]. Also, it is based on a centralized framework, so it cannot meet the requirements in fully distributed control of swarms [11].…”

“…UWB, one popular distance sensor, has been adopted widely in the literature. External UWB position system based on fixed anchors can estimate positions of agents in the common reference frame [18], but the requirement of the previous deployment of anchors means the framework can hardly be adopted in the unknown environment [8]. Efforts have been made to design an anchorfree UWB position scheme, such as UWB-IMU coupled approach [22], [23].…”

“…However, due to the single-dimensional distance measurement, the accuracy of relative localization relying barely on UWB is not satisfactory [22], [23]. To achieve better estimation, UWB measurements are fused together with measurements from other sensors, such as VIO [18], wheel encoder [24], and optical flow [25], [26].…”

Omni-swarm: A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swarms

“…Recently, researchers have started to develop a few approaches to perform decentralized relative state estimation on aerial swarms without other external localization devices. One of the most straightforward ideas is to utilize visual object detection among the aerial swarm to estimate the relative state [12]- [15]. Besides, fusing distance measturement from UWB and the odometries (usually provided by VIO) [12]- [17] is another viable approach.…”

“…2) Complicated initialization. The UWB-odometry fusion methods [12]- [15] require large motions to initialize the system. The complex initialization procedure may cause severe safety issues and even crashes.…”