Asynchronous Adaptive Sampling and Reduced-Order Modeling of Dynamic Processes by Robot Teams via Intermittently Connected Networks

Rovina, Hannes; Salam, Tahiya; Kantaros, Yiannis; Hsieh, M. Ani

doi:10.1109/iros45743.2020.9341636

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…In particular, ensuring the availability of comms links between all robots [6,7,8] or via dedicated relay robots [9,10,11] are well-researched objectives. More recently, intermittent connectivity has been considered as a more flexible objective, and several works present pathplanning methods which ensure intermittent connectivity by requiring robots meet infinitely often [12,13,14] in a known environment. During exploration, maintaining connectivity (even intermittently) poses unique advantages as large-scale exploration and connectivity are opposing objectives [3,15].…”

Section: A Related Workmentioning

confidence: 99%

ACHORD: Communication-Aware Multi-Robot Coordination With Intermittent Connectivity

Silva

Clark

Thangavelu

et al. 2022

IEEE Robot. Autom. Lett.

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Communication is an important capability for multi-robot exploration because (1) inter-robot communication (comms) improves coverage efficiency and (2) robot-tobase comms improves situational awareness. Exploring commsrestricted (e.g., subterranean) environments requires a multirobot system to tolerate and anticipate intermittent connectivity, and to carefully consider comms requirements, otherwise mission-critical data may be lost. In this paper, we describe and analyze ACHORD (Autonomous & Collaborative High-Bandwidth Operations with Radio Droppables), a multi-layer networking solution which tightly co-designs the network architecture and high-level decision-making for improved comms. ACHORD provides bandwidth prioritization and timely and reliable data transfer despite intermittent connectivity. Furthermore, it exposes low-layer networking metrics to the application layer to enable robots to autonomously monitor, map, and extend the network via droppable radios, as well as restore connectivity to improve collaborative exploration. We evaluate our solution with respect to the comms performance in several challenging underground environments including the DARPA SubT Finals competition environment. Our findings support the use of data stratification and flow control to improve bandwidth-usage. * denotes equal contribution.

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Section: A Related Workmentioning

confidence: 99%

ACHORD: Communication-Aware Multi-Robot Coordination With Intermittent Connectivity

Silva

Clark

Thangavelu

et al. 2022

IEEE Robot. Autom. Lett.

View full text Add to dashboard Cite

show abstract

Computational Sensing, Understanding, and Reasoning: An Artificial Intelligence Approach to Physics-Informed World Modeling

Moya,

Badías,

González

et al. 2023

Arch Computat Methods Eng

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Distributed Coverage Control for Spatial Processes Estimation With Noisy Observations

Mantovani,

Pratissoli,

Sabattini

2024

IEEE Robot. Autom. Lett.

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The present study addresses the challenge of effectively deploying a multi-robot team to optimally cover a domain with unknown density distribution. Specifically, we propose a distribute coverage-based control algorithm that enables a group of autonomous robots to simultaneously learn and estimate a spatial field over the domain. Additionally, we consider a scenario where the robots are deployed in a noisy environment or equipped with noisy sensors. To accomplish this, the control strategy utilizes Gaussian Process Regression (GPR) to construct a model of the monitored spatial process in the environment. Our strategy tackles the computational limits of Gaussian processes (GPs) when dealing with large data sets. The control algorithm filters the set of samples, limiting the GP training data to those that are relevant to improving the process estimate, avoiding excessive computational complexity and managing the noise in the observations. To evaluate the effectiveness of our proposed algorithm, we conducted several simulations and real platform experiments.

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Asynchronous Adaptive Sampling and Reduced-Order Modeling of Dynamic Processes by Robot Teams via Intermittently Connected Networks

Cited by 3 publications

References 27 publications

ACHORD: Communication-Aware Multi-Robot Coordination With Intermittent Connectivity

ACHORD: Communication-Aware Multi-Robot Coordination With Intermittent Connectivity

Computational Sensing, Understanding, and Reasoning: An Artificial Intelligence Approach to Physics-Informed World Modeling

Distributed Coverage Control for Spatial Processes Estimation With Noisy Observations

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