Multi-swarm Infrastructure for Swarm Versus Swarm Experimentation

Davis, Duane; Chung, Timothy H.; Clement, Michael R.; Day, Michael A.

doi:10.1007/978-3-319-73008-0_45

Cited by 3 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[30], authors used a swarm of submarines for exploring unmanned submarine where the main contribution is designing a swarm search that can work in ocean waves. Recently, Davis et al 33 used a distributed Reynolds flocking model 34 based on a single virtual leader that influences the other members. The system in ref.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Search Strategies and Specifications in a Swarm versus Swarm Context

Farid

Kamal²,

Egerton³

2021

Robotica

View full text Add to dashboard Cite

SUMMARY This paper proposes and evaluates swarming mechanisms of patrolling unmanned aerial vehicles (UAVs) that can collectively search a region for intruding UAVs. The main contributions include the development of multi-objective searching strategies and investigation of the required sensor configurations for the patrolling UAVs. Numerical results reveal that it is sometimes better to search through a region with a single swarm rather than multiple swarms deployed over sub-regions. Moreover, a large communication range does not necessarily improve search performances, and the patrolling swarm must have a speed close to the speed of the intruding UAVs to maximize the search performances.

show abstract

Section: Related Workmentioning

confidence: 99%

“…The system in ref. [33] applied this model to fixed-wing UAVs for motion planning. In our earlier work, 35 a multi-objective heuristic method was proposed for proper search planning in the 3D space.…”

Section: Related Workmentioning

confidence: 99%

Search Strategies and Specifications in a Swarm versus Swarm Context

Farid

Kamal²,

Egerton³

2021

Robotica

View full text Add to dashboard Cite

show abstract

“…The possibility of using robot swarms to conduct complex missions in built environments has become increasingly relevant (Davis et al, 2018;Chung et al, 2018;Skorobogatov et al, 2019). Recurring swarm related challenges include congestion management, GPS error, detection and avoidance of other vehicles, and difficulties in managing large-scale UAV takeoffs and landings.…”

Section: Introductionmentioning

confidence: 99%

Congestion Analysis for the DARPA OFFSET CCAST Swarm

Brown¹,

Adams²

2023

View full text Add to dashboard Cite

The Defense Advanced Research Projects Agency (DARPA) OFFensive Swam-Enabled Tactics program’s goal of launching 250 unmanned aerial and ground vehicles from a limited sized launch zone was a daunting challenge. The swarm’s aerial vehicles were primarily multirotor platforms, which can efficiently be launched en masse. Each field exercise expected the deployment of an even larger swarm. While the launch zone’s spatial area increased with each field exercise, the relative space for each vehicle was not necessarily increased, considering the increasing size of the swarm and the vehicles’ associated GPS error; however, safe mission deployment and execution were expected. At the same time, achieving the mission goals required maximizing the efficiency of the swarm’s performance by reducing congestion that blocked vehicles from completing tactic assignments. Congestion analysis conducted before the final field exercise focused on adjusting various constraints to optimize the swarm’s deployment without reducing safety. During the field exercise, data was collected that permitted analyzing the number and durations of individual vehicle blockages’ impact on the resulting congestion. After the field exercise, additional analyses used the mission plan to validate the use of simulation for analyzing congestion.

show abstract