Autonomous and Collective Intelligence for UAV Swarm in Target Search Scenario

Giacomossi, Luiz; Souza, Flávio Ramon Almeida de; Cortes, Raphael Gomes; Cortez, Huascar Mirko Montecinos; Ferreira, Caue; Marcondes, Cesar Augusto Cavalheiro; Loubach, Denis S.; Sbruzzi, Elton F.; Verri, Filipe Alves Neto; Marques, Johnny; Pereira, Lourenço Alves; Máximo, Marcos R. O. A.; Curtis, Vitor Venceslau

doi:10.1109/lars/sbr/wre54079.2021.9605450

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…Consequently, we selected the FSM technique to develop the decision-making module for the kamikaze. The FSMs are the most common model of computation for modeling decision-making architectures for simple AI [39], [41], due to its easy implementation and intuitive structure. In this technique, a state s represents a behavior for the agent.…”

Section: B High-level Decision-making Methodologymentioning

confidence: 99%

Cooperative Threat Engagement Using Drone Swarms

et al. 2023

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The ability of multiple manned and unmanned aircraft systems to cooperatively engage and disable an aerial threat plays a decisive role in modern warfare scenarios. In this paper, we apply key methods to enable the so-called cooperative threat engagement capability among multiple networked agents, e.g., a swarm of drones, with combat and communication capabilities. In particular, this research combines AI-based decision-making and control techniques for a swarm of loyal wingman drones to coordinate efficient defense actions in a cooperative and autonomous manner. We apply these concepts in a defense scenario that is modeled to analyze the loyal wingman concept, which we consider an interesting testbed for cooperative decision-making and low-level control techniques. The investigated methods were implemented in a realistic 3D UAV simulator for demonstration and evaluation. INDEX TERMSCooperative engagement capability, loyal wingman UAV, decision making, manned-unmanned teaming, sliding mode control.

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Section: B High-level Decision-making Methodologymentioning

confidence: 99%

Cooperative Threat Engagement Using Drone Swarms

et al. 2023

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“…The simulator [Giacomossi et al 2021b] has been enhanced to generate a new probability map during each new instance, which includes updated obstacles and a new location for the missing person. This dynamic probability map enables the drones to adapt their search patterns based on the latest information, enhancing their efficiency.…”

Section: Methodsmentioning

confidence: 99%

“…This involves designing environments, incorporating factors like obstacles, and limited visibility to mimic real-world search scenarios. For this, we utilize a 2D swarm simulator [Giacomossi et al 2021b] with the proposed scenario involving a UAV swarm in a forest region of approximately 60, 800 m 2 and dividing the area into (38 × 16 m) squares. The swarm assumes that the UAVs lack prior information about the missing target's position and must navigate around obstacles.…”

Section: Search and Rescue Scenariomentioning

confidence: 99%

Cooperative Decision-Making for Drone Swarms

Giacomossi Jr.,

Maximo,

Brancalion

2023

Anais Estendidos Do XV Simpósio Brasileiro De Robótica E XX Simpósio Latino-Americano De Robótica (SBR/LARS Estendido 2023)

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Unmanned Aerial Vehicles (UAVs) are being researched for their potential in applications like search and rescue, and defense missions. The goal is to enhance the intelligence, communication, and strategic organization. Decision-making techniques enable intelligent UAV decisions, freeing human commanders to focus on higher-level decisions. This research focuses on defense and search and rescue scenarios, and combines AI-based decision-making with UAVs. The study analyze the Loyal Wingman concept in a defense scenario. Also, we propose a solution for a drone swarm to cooperatively search for people in a rescue scenario. Our results demonstrate the effectiveness of distributed decision-making methods in solving problems in both scenarios.

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“…They compared their results to the more common swarm intelligence approach and found that their proposed evolutionary algorithm outperforms swarm intelligence-based approaches when the number of targets increase. In [177], the authors proposed a heuristics-based solution for increasing the intelligence of a group of UAVs by using a distributed intelligence approach for cooperatively searching for a target. They found out that distributed decision-making methods were more effective than an autonomous intelligence approach where the drones do not cooperate or act collectively.…”

Section: B Unmanned Aerial Vehicles (Uavs)mentioning

confidence: 99%