Bid Prediction for Multi-Robot Exploration with Disrupted Communications

Woosley, Bradley; Nieto-Granda, Carlos; Rogers, John G.; Fung, Nicholas; Schang, Arthur

doi:10.1109/ssrr53300.2021.9597871

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…al. [15] which provide a robust approach to dealing with disrupted communications between members of a team of autonomous agents doing search or reconnaissance operations. The methodology employed leverages a well-defined "auction" scheme where each robot creates a partition of exploration area or "frontier" and auction is set up in order to parse up and distribute these frontiers to each robot.…”

Section: Multi-robot Approachesmentioning

confidence: 99%

Delivering on the promise of autonomous agents in the battlefield

Fossaceca¹

2023

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V

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As the Army begins to deliver on the promise of autonomous agents including unmanned ground and air vehicles and other intelligent agents the focus has shifted from functionality to robustness and resilience. Intelligent systems must not only be capable of performing specific tasks, but they must also do it in a manner that is resilient to the dynamism of real-world environments and adapt to the unexpected including adversaries. This paper surveys some of the recent research and breakthroughs towards robust and resilient autonomy, some of the keys to achieving systems that learn rapidly in new environments, and that demonstrate the ability deal with uncertainty through various means including leveraging human knowledge to greatly speed up the learning process.

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Section: Multi-robot Approachesmentioning

confidence: 99%

Delivering on the promise of autonomous agents in the battlefield

Fossaceca¹

2023

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V

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“…To minimize the completion time, robots in the fleet must be able to reliably exchange information about the environment with each other with minimum delay. However, in many harsh environments, such as those of critical missions, communications can be delayed, disrupted, or even non-existent due to interference from the environment or from limitations of the robotic platform [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

CARA: Connectivity-Aware Relay Algorithm for Multi-Robot Expeditions

Abu-Aisheh

Bronzino

Salaün

et al. 2022

Sensors

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The exploration of unknown environments is an essential application of multi-robot systems, particularly in critical missions, such as hazard detection and search and rescue. These missions share the need to reach full coverage of the explorable space in the shortest time possible. To minimize the completion time, robots in the fleet must be able to reliably exchange information about the environment with one another. One of the main methods to expand coverage is by placing relays. Existing relay-placement algorithms tend to either require prior knowledge of the environment, or they rely on maintaining specific distances between the relays and the rest of the robots. These approaches lack flexibility and adaptability to the environment. This paper introduces the “Connectivity-Aware Relay Algorithm” (CARA), a dynamic context-aware relay-placement algorithm that does not require any prior knowledge of the environment. We compare CARA against a state-of-the-art distance-based relay-placement algorithm. Our results demonstrate that CARA outperformed the state-of-the-art algorithm in terms of the time to completion by a factor of 10 as it placed, on average, half the number of relays.

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