Analytical PDE based trajectory planning for Unmanned Air Vehicles in dynamic hostile environments

Radmanesh, Mohammadreza; Guentert, Paul H.; Kumar, Manish; Cohen, Kelly

doi:10.23919/acc.2017.7963608

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…While problem complexity increases, the computation time also increases [56]. In the existing studies, the algorithms such Floyd Warshall, fuzzy logic were consuming more time to find the object path while size of the problem increased [57]. With the implementation of evolutionary algorithms, the consuming time and error rate are decreased, and objects are avoided which helps the UAV to travel in safety path.…”

Section: Resultsmentioning

confidence: 99%

Autonomous UAV object Avoidance with Floyd-warshall differential evolution approach

YK¹,

NageswaraGuptha²

2022

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Unmanned Aerial Vehicles (UAVs) are recently focused with significant research attention from commercial to military industries. Due to its wide range of applications such as traffic monitoring, surveillance, aerial photograph and rescue mission, many research studies were conducted related to UAV development. UAV are commonly called as ‘drones’ used to suit dull, dangerous and dirty missions that can be suited by manned aircraft. UAV can be controlled either remotely or using automation approaches so that it can be travelled into predefined path. To make the autonomous UAV, the most complex issue that is faced by UAV is obstacle / object avoidance. Obstacle detection and avoidance are important for UAV and it is the complex problem to solve due to the payload restriction. This will limit the sensor count mounted on the vehicle. Radar was used to find the distance between the object and vehicle. This can help to detect and track the moving objects speed and direction towards the vehicle. This paper considered the object avoidance problem as path planning problem. There were many path planning methods related to UAV which formulates the path planning as an optimization problem to avoid the obstacles. With the consideration, this paper proposed an efficient and optimal approach called Floyd Warshall- Differential evolution (FWDE) approach to detect the frontal obstacles of UAV. Finally, statistical analysis of the simulated environment reveals that the proposed evolutionary method can efficiently avoid both static and dynamic objects for UAVs. This efficient avoidance algorithm for UAV can be experimented with simulation environment with three kinds of scenarios having different number of cells. The obtained accuracy and recall value of the proposed system is 95.21% and 91.56%.

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Section: Resultsmentioning

confidence: 99%

Autonomous UAV object Avoidance with Floyd-warshall differential evolution approach

YK¹,

NageswaraGuptha²

2022

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“…The UAV is considered as a fluid particle in a flow. The equations of fluid flow govern the motion of the UAV from the initial point to the final point in an optimal fashion [26]. The equations governing the fluid motions and the solution method are provided in this section.…”

Section: Approach Based On Partial Differential Equations and Fluid Fmentioning

confidence: 99%

“…The postprocessing, as explained in Sec. 5 [26], is carried out to ensure the path can be followed by the UAV under its kino-dynamic constraints. Potential functions f, originated from the fluid analogy, is designed to represent the higher potentials at the starting point and lower potential at the goal locations.…”

Section: Approach Based On Partial Differential Equations and Fluid Fmentioning

confidence: 99%

Partial Differential Equation-Based Trajectory Planning for Multiple Unmanned Air Vehicles in Dynamic and Uncertain Environments

Radmanesh

Kumar

French

2020

Journal of Dynamic Systems, Measurement, and Control

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This paper proposes a physics-inspired method for unmanned aerial vehicle (UAV) trajectory planning in three dimensions using partial differential equations (PDEs) for application in dynamic hostile environments. The proposed method exploits the dynamical property of fluid flowing through a porous medium. This method evaluates risk to generate porosity values throughout the computational domain. The trajectory that encounters the highest porosity values determines the trajectory from the point of origin to the goal position. The best trajectory is found using the reaction of the fluid in porous media by the way of streamlines obtained by numerically solving the PDEs representing the fluid flow. Constraints due to UAV dynamics, obstacles, and predefined way points are applied to the problem after solving for the best trajectory to find the optimal and feasible trajectory. This method shows near-optimality and much reduced computational effort when compared to the other typical numerical optimization methods.

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Recursive Tangent Algorithm for Path Planning in Autonomous Systems

Shetty

Jonnalagadda

Cherukuri

2020

Hybrid Intelligent Systems

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Analytical PDE based trajectory planning for Unmanned Air Vehicles in dynamic hostile environments

Cited by 6 publications

References 8 publications

Autonomous UAV object Avoidance with Floyd-warshall differential evolution approach

Autonomous UAV object Avoidance with Floyd-warshall differential evolution approach

Partial Differential Equation-Based Trajectory Planning for Multiple Unmanned Air Vehicles in Dynamic and Uncertain Environments

Recursive Tangent Algorithm for Path Planning in Autonomous Systems

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