A Fuel Consumption Algorithm for Unmanned Aircraft Systems

Jameson, Terry

doi:10.21236/ada500380

Cited by 8 publications

(3 citation statements)

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“…Jakaria et al presented a formal model for verification of a resilient communication in a UAV swarm while maintaining safe flight trajectories for all the UAVs [1,19]. Jameson proposed a fuel consumption algorithm for UAVs that addresses the additional fuel requirements issue in the Aviation Weather Routing Tool (AWRT) developed by the Army Research Laboratory [20]. They developed a prototype algorithm that computes the ground speeds along the different mission segments, fuel consumed, and fuel remaining while rerouting during adverse weather conditions.…”

Section: Related Workmentioning

confidence: 99%

Automated Trajectory Synthesis for UAV Swarms Based on Resilient Data Collection Objectives

Jakaria¹,

Rahman²,

Anderson³

et al. 2020

Preprint

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The use of Unmanned Aerial Vehicles (UAVs) for collecting data from remotely located sensor systems is emerging. The data can be timesensitive and require to be transmitted to a data processing center. However, planning the trajectory of a collaborative UAV swarm depends on multi-fold constraints, such as data collection requirements, UAV maneuvering capacity, and budget limitation. Since a UAV may fail or be compromised, it is important to provide necessary resilience to such contingencies, thus ensuring data security. It is important to provide the UAVs with efficient spatio-temporal trajectories so that they can efficiently cover necessary data sources. In this work, we present Synth4UAV, a formal approach for automated synthesis of efficient trajectories for a UAV swarm by logically modeling the aerial space and data point topology, UAV moves, and associated constraints in terms of the turning and climbing angle, fuel usage, data collection point coverage, data freshness, and resiliency properties. We use efficient, logical formulas to encode and solve the complex model. The solution to the model provides the routing and maneuvering plan for each UAV, including the time to visit the points on the paths and corresponding fuel usage such that the necessary data points are visited while satisfying the resiliency requirements. We evaluate the proposed trajectory synthesizer, and the results show that the relationship among different parameters follow the requirements while the tool scales well with the problem size.

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Section: Related Workmentioning

confidence: 99%

Automated Trajectory Synthesis for UAV Swarms Based on Resilient Data Collection Objectives

Jakaria¹,

Rahman²,

Anderson³

et al. 2020

Preprint

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“…The UAV information consists of a set of properties for each UAV, which includes its starting position, initial stored fuel, fuel capacity, and fuel costs per step for flying (when the climbing angle is zero) and hovering/loitering. It is worth mentioning that these property values are synthetic and driven from practical sources, particularly considering HyDrone UAVs [28], [29], [30].…”

Section: B Case Studymentioning

confidence: 99%

Trajectory Synthesis for a UAV Swarm to Perform Resilient Requirement-Aware Surveillance: A Smart Grid-based Study

Rahman,

Masum,

Anderson

et al. 2019

Preprint

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A smart grid is a widely distributed engineering system with overhead transmission lines. Physical damage to these power lines, from natural calamities or technical failures, will disrupt the functional integrity of the grid. To ensure the continuation of the grid's operational flow when those phenomena happen, the grid operator must immediately take steps to nullify the impacts and repair the problems, even if those occur in hardly-reachable remote areas. Emerging unmanned aerial vehicles (UAVs) show great potential to replace traditional human patrols for regularly monitoring critical situations involving the safety of the grid. The critical lines can be monitored by a fleet of UAVs to ensure a resilient surveillance system. The proposed approach considers the n-1 contingency analysis to find the criticality of a transmission line. We propose a formal framework that verifies whether a given set of UAVs (i.e., a UAV swarm) can perform continuous surveillance of the grid satisfying various requirements, particularly the monitoring and resiliency specifications. The verification process ultimately provides a trajectory plan for the UAVs, including the refueling schedules. The resiliency requirement of inspecting a point on a line is expressed in terms of a k−property specifying that if k UAVs fail or compromised still there is a UAV to collect the data at the point within on time. We evaluate the proposed framework on synthetic data based on various IEEE test bus systems.

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“…We base our fuel consumption on distance (liters per grid). The cost function is implemented with rules derived from (Jameson 2009):…”

Section: Aviation Domain Model Implementationmentioning

confidence: 99%

Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding

Walker

Chan

Sturtevant

2017

ICAPS

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Recent work in multi-agent path planning has provided a number of optimal and suboptimal solvers that can efficiently find solutions to problems of growing complexity. Solvers based on Conflict-Based Search (CBS) combine single-agent solvers with shared constraints between agents to find feasible solutions. Suboptimal variants of CBS introduce alternate heuristics to avoid conflicts. In this paper we study the multi-agent planning problem in the context of non-holonomic vehicles planning on a lattice. We propose that in addition to using heuristics to avoid conflicts, we can plan using a hierarchy of movement constraints to efficiently avoid conflicts. We develop a new extension to the CBS algorithm, CBS with constraint layering (CBS+CL), which iteratively applies different movement constraint models during the CBS planning process. Our results show that this approach allows us to solve for about 2.4 times more agents in the same amount of time when compared to regular CBS without using a constraint hierarchy.

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A Fuel Consumption Algorithm for Unmanned Aircraft Systems

Cited by 8 publications

References 0 publications

Automated Trajectory Synthesis for UAV Swarms Based on Resilient Data Collection Objectives

Automated Trajectory Synthesis for UAV Swarms Based on Resilient Data Collection Objectives

Trajectory Synthesis for a UAV Swarm to Perform Resilient Requirement-Aware Surveillance: A Smart Grid-based Study

Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding

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