Path Planning of Multiple Unmanned Aerial Vehicles Based on RRT Algorithm

Kaur, Amritpal; Prasad, Mani Shankar

doi:10.1007/978-981-13-6577-5_70

Cited by 4 publications

(2 citation statements)

References 4 publications

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“…With the advancement of UAV research, new path-planning systems have been developed, each with its own set of benefits and drawbacks. This algorithm includes graph theory-based Voronoi diagram [15], field theory-based artificial potential field approach [16], sampling theory-based RRT [17], heuristic information-based A* algorithm [18], swarm intelligence-based optimization approaches [19][20][21], Graph based approaches not suited well for larger environments. II.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 99%

Autonomous UAV object Avoidance with Floyd-warshall differential evolution approach

YK¹,

NageswaraGuptha²

2022

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“…(1) The method of resolving the new trajectory based on path planning: the main idea of this method is to transform the obstacle avoidance problem into a path planning problem [4,5]. With the advances of research in this field, many significantly improved path planning algorithms have been proposed, including the Voronoi diagram (VD) [6] based on graph theory, artificial potential field (APF) [7,8] based on field theory, the RRT [9] algorithm based on sampling theory, the A * [10] algorithm based on heuristic information, and other algorithms based on swarm intelligence optimization theories [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Autonomous Obstacle Avoidance Algorithm for UAV Based on Circular Arc Trajectory

Jian-dong

Liang

Wang

et al. 2021

International Journal of Aerospace Engineering

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This paper proposes an innovative and efficient three-dimensional (3D) autonomous obstacle algorithm for unmanned aerial vehicles (UAVs) which works by generating circular arc trajectories to avoid obstacles. Firstly, information on irregular obstacles is obtained by an onboard detection system; this information is then transformed into standard convex bodies, which are used to generate circular arc avoidance trajectories, and the obstacle avoidance problem is turned into a trajectory tracking strategy. Then, on the basis of the geometric relationship between a UAV and obstacle modeling, the working mechanism of the avoidance algorithm is developed. The rules of obstacle detection, avoidance direction, and the criterion of avoidance success are defined for different obstacle types. Finally, numerical simulations of different obstacle scenarios show that the proposed algorithm can avoid static and dynamic obstacles effectively and can implement obstacle avoidance missions for UAVs well.

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Multi-UAVs for Bushfire Situational Awareness: a Comparison of Environment Traversal Algorithms

Zadeh

Zaslavsky

Loke

et al. 2021

2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing &Amp; Communications (GreenCom) An

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Path Planning of Multiple Unmanned Aerial Vehicles Based on RRT Algorithm

Cited by 4 publications

References 4 publications

Autonomous UAV object Avoidance with Floyd-warshall differential evolution approach

Autonomous UAV object Avoidance with Floyd-warshall differential evolution approach

Three-Dimensional Autonomous Obstacle Avoidance Algorithm for UAV Based on Circular Arc Trajectory

Multi-UAVs for Bushfire Situational Awareness: a Comparison of Environment Traversal Algorithms

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